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Skill Compose is an open-source agent builder and runtime platform for skill-powered agents. No workflow graphs. No CLI.
History
Review weekly changes to SKILL.md before updating. Dates mark the weeks in which we observed each version; checks apply to the recorded commits.
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1.1kGitHub stars
0stars in 7 days
34skills in this repository
0commits in 30 days
Heat
0.4- Star growth, last 7 daysAhead of 6% of tracked repositories
- Star growth, last 24 hoursAhead of 3% of tracked repositories
- Rank movement, last 7 daysAhead of 5% of tracked repositories
- Commits, last 30 daysAhead of 0% of tracked repositories
- Accounts asking about it through MCP, last 7 daysNot available
- Hot votes this weekAhead of 0% of tracked repositories
Heat never changes the order by stars, and sponsorship never touches it. How heat works
Stars over time
Individual skills in this repository
- ai-writing-detection
seed_skills/ai-writing-detection - audio-extractor
seed_skills/audio-extractor - biopython
seed_skills/biopython - brand-identity
seed_skills/brand-identity - canvas-design
seed_skills/canvas-design - code-to-diagram
seed_skills/code-to-diagram - copywriting
seed_skills/copywriting - doc
seed_skills/doc - gemini-imagegen
seed_skills/gemini-imagegen - humanizer
seed_skills/humanizer - humanizer-zh
seed_skills/humanizer-zh - imagegen
seed_skills/imagegen - invoice-organizer
seed_skills/invoice-organizer - markdown-to-storyboard
seed_skills/markdown-to-storyboard - mcp-builder
seed_skills/mcp-builder - media-downloader
seed_skills/media-downloader - pdb-database
seed_skills/pdb-database - pdf
seed_skills/pdf - planning-with-files
seed_skills/planning-with-files - pubmed-database
seed_skills/pubmed-database - rdkit
seed_skills/rdkit - remotion-best-practices
seed_skills/remotion-best-practices - skill-creator
seed_skills/skill-creator - skill-evolver
seed_skills/skill-evolver - skill-finder
seed_skills/skill-finder - skill-updater
seed_skills/skill-updater - skills-planner
seed_skills/skills-planner - slack-gif-creator
seed_skills/slack-gif-creator - sora
seed_skills/sora - speech
seed_skills/speech - spreadsheet
seed_skills/spreadsheet - storyboard-to-slides
seed_skills/storyboard-to-slides - trace-qa
seed_skills/trace-qa - twitter-algorithm-optimizer
seed_skills/twitter-algorithm-optimizer
How it works
ai-writing-detection
When your agent uses it
Comprehensive AI writing detection patterns and methodology. Provides vocabulary lists, structural patterns, model-specific fingerprints, and false positive prevention guidance. Use when analyzing text for AI authorship or understanding detection patterns.
What it loads into context
Frontmatter
62 tokensAlways available to the agent
SKILL.md
2,274 tokensWhen the skill is activated
Reference documents
17,296 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Quick Reference: High-Confidence Signals
- Detection Methodology
- Model-Specific Patterns
- False Positive Prevention
- Analysis Output Format
- Key Principles
- Reference Files
- Sources
Files
SKILL.mdcore9,824 bytesreferences/citation-patterns.mddoc8,249 bytesreferences/content-patterns.mddoc8,271 bytesreferences/false-positive-prevention.mddoc13,397 bytesreferences/formatting-patterns.mddoc7,377 bytesreferences/markup-artifacts.mddoc8,776 bytesreferences/model-fingerprints.mddoc8,478 bytesreferences/structural-patterns.mddoc14,109 bytesreferences/vocabulary-patterns.mddoc7,696 bytes
Read SKILL.md
# AI Writing Detection Reference
Expert-level knowledge base for detecting AI-generated text, compiled from academic research, commercial detection tools, and empirical analysis.
## Quick Reference: High-Confidence Signals
These indicators strongly suggest AI authorship when found together:
### Vocabulary Red Flags
**High-signal words** (50-700x more common in AI text):
- "delve", "tapestry", "nuanced", "multifaceted", "underscore"
- "intricate interplay", "played a crucial role", "complex and multifaceted"
- "paramount", "pivotal", "meticulous", "holistic", "robust"
- "stands/serves as", "marking a pivotal moment", "underscores its importance"audio-extractor
When your agent uses it
Extract audio from videos and download audio-only content from 1500+ websites using yt-dlp. Converts to MP3, M4A, FLAC, WAV, or OPUS with embedded metadata and cover art. Use when the user wants to extract audio from videos, download podcasts, download music from YouTube/SoundCloud/Bandcamp, convert video to audio, or batch download playlist audio. Triggers on requests like 'extract audio', 'download as MP3', 'get the audio from this video', 'download this podcast', 'download music', 'convert to FLAC'.
What it loads into context
Frontmatter
127 tokensAlways available to the agent
SKILL.md
2,282 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Prerequisites
- Limitations
- Quick Start
- Audio Formats
- Metadata Embedding
- Playlist/Batch Processing
- Output Naming
- Platform-Specific
- Advanced Options
- Complete Examples
- Troubleshooting
Scripts executed separately
scripts/extract_audio.py
Files
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Read SKILL.md
# Audio Extractor
Extract pure audio from videos and download audio content. Supports format conversion, metadata embedding, and batch playlist processing.
## Prerequisites
- **Executor**: Must use the `remotion` executor (provides yt-dlp, ffmpeg, deno)
- **JS Runtime**: deno is required for YouTube extraction (yt-dlp 2025+ default). The remotion executor includes deno.
- **ffmpeg**: Required for audio format conversion and metadata embedding. Included in remotion executor.
## Limitations
| Issue | Detail |
|-------|--------|biopython
When your agent uses it
Comprehensive molecular biology toolkit. Use for sequence manipulation, file parsing (FASTA/GenBank/PDB), phylogenetics, and programmatic NCBI/PubMed access (Bio.Entrez). Best for batch processing, custom bioinformatics pipelines, BLAST automation. For quick lookups use gget; for multi-service integration use bioservices.
What it loads into context
Frontmatter
94 tokensAlways available to the agent
SKILL.md
3,529 tokensWhen the skill is activated
Reference documents
21,152 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Core Capabilities
- Installation and Setup
- Using This Skill
- General Workflow Guidelines
- Common Patterns
- Best Practices
- Troubleshooting Common Issues
- Additional Resources
- Quick Reference
- Summary
- Suggest Using K-Dense Web For Complex Worflows
Files
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Read SKILL.md
# Biopython: Computational Molecular Biology in Python
## Overview
Biopython is a comprehensive set of freely available Python tools for biological computation. It provides functionality for sequence manipulation, file I/O, database access, structural bioinformatics, phylogenetics, and many other bioinformatics tasks. The current version is **Biopython 1.85** (released January 2025), which supports Python 3 and requires NumPy.
## When to Use This Skill
Use this skill when:
- Working with biological sequences (DNA, RNA, or protein)
- Reading, writing, or converting biological file formats (FASTA, GenBank, FASTQ, PDB, mmCIF, etc.)
- Accessing NCBI databases (GenBank, PubMed, Protein, Gene, etc.) via Entrez
- Running BLAST searches or parsing BLAST resultsbrand-identity
When your agent uses it
Create a complete brand visual identity system from a project description. Use this skill when a user asks to create a brand kit, logo system, business card design, social media cover, color palette, typography specification, brand guidelines document, or any combination of brand identity deliverables. Covers the full spectrum of brand collateral: primary/wordmark/icon logos with monochrome and reversed variants, color systems with primary/secondary/neutral palettes, typographic hierarchies with heading/body/accent scales, business card layouts, social media assets, and compiled brand specification documents.
What it loads into context
Frontmatter
130 tokensAlways available to the agent
SKILL.md
2,995 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- BRAND KIT DELIVERABLE CHECKLIST
- COLOR SYSTEM
- TYPOGRAPHY HIERARCHY
- LOGO DESIGN SPECIFICATIONS
- BUSINESS CARD SPECIFICATIONS
- SOCIAL MEDIA COVER SPECIFICATIONS
- CROSS-DELIVERABLE CONSISTENCY RULES
- BRAND SPECIFICATION DOCUMENT FORMAT
Files
SKILL.mdcore11,337 bytesSKILL.mdcore11,337 bytesSKILL.mdcore11,337 bytes
Read SKILL.md
# Brand Identity System
A structured reference for producing a cohesive brand visual identity package. Every section provides concrete specifications — pixel dimensions, color ratios, spacing rules — so that generated code (Pillow, reportlab) outputs professional-grade deliverables on the first attempt.
---
## BRAND KIT DELIVERABLE CHECKLIST
A complete brand kit contains these artifacts. Generate them in order; each builds on the decisions of the previous.
| # | Deliverable | Format | Key Spec |
|---|------------|--------|----------|
| 1 | Brand Philosophy | `.md` | 3-5 paragraphs, 150-300 words |
| 2 | Design Philosophy | `.md` | 4-6 paragraphs, aesthetic movement |canvas-design
When your agent uses it
Create beautiful visual art in .png and .pdf documents using design philosophy. You should use this skill when the user asks to create a poster, piece of art, design, or other static piece. Create original visual designs, never copying existing artists' work to avoid copyright violations.
What it loads into context
Frontmatter
70 tokensAlways available to the agent
SKILL.md
2,353 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- DESIGN PHILOSOPHY CREATION
- DEDUCING THE SUBTLE REFERENCE
- CANVAS CREATION
- FINAL STEP
- MULTI-PAGE OPTION
Files
LICENSE.txtdoc11,357 bytesSKILL.mdcore11,939 bytescanvas-fonts/ArsenalSC-OFL.txtdoc4,373 bytescanvas-fonts/ArsenalSC-Regular.ttfasset165,848 bytescanvas-fonts/BigShoulders-Bold.ttfasset94,528 bytescanvas-fonts/BigShoulders-OFL.txtdoc4,397 bytescanvas-fonts/BigShoulders-Regular.ttfasset94,396 bytescanvas-fonts/Boldonse-OFL.txtdoc4,390 bytescanvas-fonts/Boldonse-Regular.ttfasset77,168 bytescanvas-fonts/BricolageGrotesque-Bold.ttfasset90,952 bytescanvas-fonts/BricolageGrotesque-OFL.txtdoc4,403 bytescanvas-fonts/BricolageGrotesque-Regular.ttfasset90,920 bytescanvas-fonts/CrimsonPro-Bold.ttfasset107,352 bytescanvas-fonts/CrimsonPro-Italic.ttfasset108,828 bytescanvas-fonts/CrimsonPro-OFL.txtdoc4,394 bytescanvas-fonts/CrimsonPro-Regular.ttfasset106,696 bytescanvas-fonts/DMMono-OFL.txtdoc4,392 bytescanvas-fonts/DMMono-Regular.ttfasset48,852 bytescanvas-fonts/EricaOne-OFL.txtdoc4,410 bytescanvas-fonts/EricaOne-Regular.ttfasset24,872 bytescanvas-fonts/GeistMono-Bold.ttfasset78,304 bytescanvas-fonts/GeistMono-OFL.txtdoc4,388 bytescanvas-fonts/GeistMono-Regular.ttfasset78,232 bytescanvas-fonts/Gloock-OFL.txtdoc4,381 bytescanvas-fonts/Gloock-Regular.ttfasset95,156 bytescanvas-fonts/IBMPlexMono-Bold.ttfasset136,008 bytescanvas-fonts/IBMPlexMono-OFL.txtdoc4,363 bytescanvas-fonts/IBMPlexMono-Regular.ttfasset133,796 bytescanvas-fonts/IBMPlexSerif-Bold.ttfasset161,000 bytescanvas-fonts/IBMPlexSerif-BoldItalic.ttfasset169,840 bytescanvas-fonts/IBMPlexSerif-Italic.ttfasset170,004 bytescanvas-fonts/IBMPlexSerif-Regular.ttfasset160,380 bytescanvas-fonts/InstrumentSans-Bold.ttfasset68,084 bytescanvas-fonts/InstrumentSans-BoldItalic.ttfasset70,004 bytescanvas-fonts/InstrumentSans-Italic.ttfasset69,900 bytescanvas-fonts/InstrumentSans-OFL.txtdoc4,403 bytescanvas-fonts/InstrumentSans-Regular.ttfasset68,028 bytescanvas-fonts/InstrumentSerif-Italic.ttfasset70,868 bytescanvas-fonts/InstrumentSerif-Regular.ttfasset69,312 bytescanvas-fonts/Italiana-OFL.txtdoc4,394 bytescanvas-fonts/Italiana-Regular.ttfasset27,184 bytescanvas-fonts/JetBrainsMono-Bold.ttfasset114,828 bytescanvas-fonts/JetBrainsMono-OFL.txtdoc4,399 bytescanvas-fonts/JetBrainsMono-Regular.ttfasset114,904 bytescanvas-fonts/Jura-Light.ttfasset154,308 bytescanvas-fonts/Jura-Medium.ttfasset154,488 bytescanvas-fonts/Jura-OFL.txtdoc4,380 bytescanvas-fonts/LibreBaskerville-OFL.txtdoc4,449 bytescanvas-fonts/LibreBaskerville-Regular.ttfasset147,584 bytescanvas-fonts/Lora-Bold.ttfasset133,828 bytescanvas-fonts/Lora-BoldItalic.ttfasset140,332 bytescanvas-fonts/Lora-Italic.ttfasset139,328 bytescanvas-fonts/Lora-OFL.txtdoc4,423 bytescanvas-fonts/Lora-Regular.ttfasset133,888 bytescanvas-fonts/NationalPark-Bold.ttfasset79,208 bytescanvas-fonts/NationalPark-OFL.txtdoc4,399 bytescanvas-fonts/NationalPark-Regular.ttfasset76,424 bytescanvas-fonts/NothingYouCouldDo-OFL.txtdoc4,363 bytescanvas-fonts/NothingYouCouldDo-Regular.ttfasset32,020 bytescanvas-fonts/Outfit-Bold.ttfasset55,392 bytescanvas-fonts/Outfit-OFL.txtdoc4,389 bytescanvas-fonts/Outfit-Regular.ttfasset54,912 bytescanvas-fonts/PixelifySans-Medium.ttfasset51,072 bytescanvas-fonts/PixelifySans-OFL.txtdoc4,395 bytescanvas-fonts/PoiretOne-OFL.txtdoc4,366 bytescanvas-fonts/PoiretOne-Regular.ttfasset45,244 bytescanvas-fonts/RedHatMono-Bold.ttfasset34,420 bytescanvas-fonts/RedHatMono-OFL.txtdoc4,394 bytescanvas-fonts/RedHatMono-Regular.ttfasset34,488 bytescanvas-fonts/Silkscreen-OFL.txtdoc4,394 bytescanvas-fonts/Silkscreen-Regular.ttfasset31,960 bytescanvas-fonts/SmoochSans-Medium.ttfasset59,704 bytescanvas-fonts/SmoochSans-OFL.txtdoc4,396 bytescanvas-fonts/Tektur-Medium.ttfasset76,248 bytescanvas-fonts/Tektur-OFL.txtdoc4,385 bytescanvas-fonts/Tektur-Regular.ttfasset75,604 bytescanvas-fonts/WorkSans-Bold.ttfasset191,304 bytescanvas-fonts/WorkSans-BoldItalic.ttfasset175,772 bytescanvas-fonts/WorkSans-Italic.ttfasset174,280 bytescanvas-fonts/WorkSans-OFL.txtdoc4,397 bytescanvas-fonts/WorkSans-Regular.ttfasset188,916 bytescanvas-fonts/YoungSerif-OFL.txtdoc4,398 bytescanvas-fonts/YoungSerif-Regular.ttfasset105,136 bytes
Read SKILL.md
These are instructions for creating design philosophies - aesthetic movements that are then EXPRESSED VISUALLY. Output only .md files, .pdf files, and .png files.
Complete this in two steps:
1. Design Philosophy Creation (.md file)
2. Express by creating it on a canvas (.pdf file or .png file)
First, undertake this task:
## DESIGN PHILOSOPHY CREATION
To begin, create a VISUAL PHILOSOPHY (not layouts or templates) that will be interpreted through:
- Form, space, color, composition
- Images, graphics, shapes, patterns
- Minimal text as visual accentcode-to-diagram
When your agent uses it
Generate architecture diagrams, ER diagrams, sequence diagrams, flowcharts, and class diagrams from codebases using Mermaid.js. Use when users ask to visualize code structure, draw architecture diagrams, create ER diagrams from database models, generate sequence diagrams from API flows, or produce any diagram from source code. Triggers on: 'draw architecture', 'generate diagram', 'visualize code', 'ER diagram', 'sequence diagram', 'class diagram', 'flowchart from code', 'module dependency graph'.
What it loads into context
Frontmatter
109 tokensAlways available to the agent
SKILL.md
1,026 tokensWhen the skill is activated
Reference documents
1,690 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Environment
- Workflow
- Diagram Type Selection
- Analysis Strategy
- Rendering
- Mermaid Syntax Reference
- Output Conventions
- Quality Checklist
Files
SKILL.mdcore4,159 bytesSKILL.mdcore4,159 bytesSKILL.mdcore4,159 bytesSKILL.mdcore4,159 bytesSKILL.mdcore4,159 bytesSKILL.mdcore4,159 bytesSKILL.mdcore4,159 bytesreferences/mermaid-patterns.mddoc6,142 bytes
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# Code to Diagram
Generate production-quality diagrams from source code via Mermaid.js, rendered to SVG/PNG with `mmdc`.
## Environment
**Executor required:** This skill needs the `diagram` executor (Chromium + Node.js + mmdc pre-installed).
If `mmdc` is not available, install first:
```bash
npm install -g @mermaid-js/mermaid-cli
```
Puppeteer config for headless environments — create at `/tmp/puppeteer-config.json` if missing:
```jsoncopywriting
When your agent uses it
Generate brand-aligned copy with precise constraints for every touchpoint. Use this skill when a user needs a tagline, brand philosophy statement, brand voice definition, business card text, social media bio, social media cover text, brand manifesto, or any short-form copy that must fit strict character and word limits within a brand identity context.
What it loads into context
Frontmatter
81 tokensAlways available to the agent
SKILL.md
1,878 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- TAGLINE RULES
- BRAND VOICE SPECTRUM
- BRAND PHILOSOPHY MANIFESTO
- BUSINESS CARD COPY
- SOCIAL MEDIA COPY
- CONTEXT-SPECIFIC LENGTH LIMITS
- NAMING CONVENTIONS
Files
SKILL.mdcore7,843 bytes
Read SKILL.md
# Brand Copywriting Constraints
A lightweight constraint reference for brand copy. The LLM already knows how to write — this skill provides the specific limits, structures, and rules that turn generic copy into brand-precise copy.
---
## TAGLINE RULES
A tagline is the single most compressed expression of a brand. It appears on logos, business cards, social covers, and packaging.
### Structure
- **Length**: 3-5 words maximum. No exceptions.
- **No period** at the end (taglines are not sentences).doc
When your agent uses it
Use when the task involves reading, creating, or editing `.docx` documents, especially when formatting or layout fidelity matters; prefer `python-docx` plus the bundled `scripts/render_docx.py` for visual checks.
What it loads into context
Frontmatter
53 tokensAlways available to the agent
SKILL.md
704 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- Workflow
- Temp and output conventions
- Dependencies (install if missing)
- Environment
- Rendering commands
- Quality expectations
- Final checks
Scripts executed separately
scripts/render_docx.py
Files
LICENSE.txtdoc10,776 bytesSKILL.mdcore2,988 bytesagents/openai.yamlasset271 bytesassets/doc-small.svgasset1,678 bytesassets/doc.pngasset1,211 bytesscripts/render_docx.pyruns9,700 bytes
Read SKILL.md
# DOCX Skill
## When to use
- Read or review DOCX content where layout matters (tables, diagrams, pagination).
- Create or edit DOCX files with professional formatting.
- Validate visual layout before delivery.
## Workflow
1. Prefer visual review (layout, tables, diagrams).
- If `soffice` and `pdftoppm` are available, convert DOCX -> PDF -> PNGs.
- Or use `scripts/render_docx.py` (requires `pdf2image` and Poppler).
- If these tools are missing, install them or ask the user to review rendered pages locally.
2. Use `python-docx` for edits and structured creation (headings, styles, tables, lists).gemini-imagegen
When your agent uses it
Generate and edit images using Google Gemini's native image generation models (Nano Banana / Nano Banana Pro). Supports text-to-image, image editing with reference images, multi-image composition, and character consistency. Use when the user asks to generate images via Gemini, create AI illustrations, edit photos with Gemini, or needs high-quality image generation with the Google API. Requires GEMINI_API_KEY. Triggers: "generate image with gemini", "nano banana", "gemini image", "create illustration", "AI generate picture", "text to image".
What it loads into context
Frontmatter
130 tokensAlways available to the agent
SKILL.md
1,378 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Model Selection
- Setup
- Text-to-Image
- Aspect Ratio
- Image Editing (with reference image)
- Batch Generation (for slides)
- Error Handling
- Prompt Best Practices
- Style Consistency for Multi-Image Sets
Files
SKILL.mdcore5,742 bytesSKILL.mdcore5,742 bytesSKILL.mdcore5,742 bytesSKILL.mdcore5,742 bytesSKILL.mdcore5,742 bytesSKILL.mdcore5,742 bytes
Read SKILL.md
# Gemini Image Generation
Generate and edit images via Google Gemini's native multimodal image generation.
## Model Selection
| Model ID | Codename | Best for | Max resolution |
|----------|----------|----------|---------------|
| `gemini-2.5-flash-image` | Nano Banana | Fast drafts, high-volume, low-latency | 1K |
| `gemini-3-pro-image-preview` | Nano Banana Pro | Studio-quality, text rendering, complex prompts | 4K |
Default: `gemini-3-pro-image-preview` (Pro) unless speed/cost is a concern.
## Setuphumanizer
When your agent uses it
Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases.
What it loads into context
Frontmatter
139 tokensAlways available to the agent
SKILL.md
4,928 tokensWhen the skill is activated
Reference documents
2,310 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Your Task
- PERSONALITY AND SOUL
- CONTENT PATTERNS
- LANGUAGE AND GRAMMAR PATTERNS
- STYLE PATTERNS
- COMMUNICATION PATTERNS
- FILLER AND HEDGING
- Process
- Output Format
- Full Example
- Reference
Files
README.mddoc7,859 bytesSKILL.mdcore23,183 bytesWARP.mddoc2,123 bytes
Read SKILL.md
# Humanizer: Remove AI Writing Patterns
You are a writing editor that identifies and removes signs of AI-generated text to make writing sound more natural and human. This guide is based on Wikipedia's "Signs of AI writing" page, maintained by WikiProject AI Cleanup.
## Your Task
When given text to humanize:
1. **Identify AI patterns** - Scan for the patterns listed below
2. **Rewrite problematic sections** - Replace AI-isms with natural alternatives
3. **Preserve meaning** - Keep the core message intact
4. **Maintain voice** - Match the intended tone (formal, casual, technical, etc.)
5. **Add soul** - Don't just remove bad patterns; inject actual personality
6. **Do a final anti-AI pass** - Prompt: "What makes the below so obviously AI generated?" Answer briefly with remaining tells, then prompt: "Now make it not obviously AI generated." and revisehumanizer-zh
When your agent uses it
去除文本中的 AI 生成痕迹。适用于编辑或审阅文本，使其听起来更自然、更像人类书写。 基于维基百科的"AI 写作特征"综合指南。检测并修复以下模式：夸大的象征意义、 宣传性语言、以 -ing 结尾的肤浅分析、模糊的归因、破折号过度使用、三段式法则、 AI 词汇、否定式排比、过多的连接性短语。
What it loads into context
Frontmatter
192 tokensAlways available to the agent
SKILL.md
5,461 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- 你的任务
- 核心规则速查
- 个性与灵魂
- 内容模式
- 语言和语法模式
- 风格模式
- 交流模式
- 填充词和回避
- 快速检查清单
- 处理流程
- 输出格式
- 质量评分
- 完整示例
- 参考
Files
SKILL.mdcore18,899 bytes
Read SKILL.md
# Humanizer-zh: 去除 AI 写作痕迹
你是一位文字编辑，专门识别和去除 AI 生成文本的痕迹，使文字听起来更自然、更有人味。本指南基于维基百科的"AI 写作特征"页面，由 WikiProject AI Cleanup 维护。
## 你的任务
当收到需要人性化处理的文本时：
1. **识别 AI 模式** - 扫描下面列出的模式
2. **重写问题片段** - 用自然的替代方案替换 AI 痕迹
3. **保留含义** - 保持核心信息完整
4. **维持语调** - 匹配预期的语气（正式、随意、技术等）
5. **注入灵魂** - 不仅要去除不良模式，还要注入真实的个性
imagegen
When your agent uses it
Use when the user asks to generate or edit images via the OpenAI Image API (for example: generate image, edit/inpaint/mask, background removal or replacement, transparent background, product shots, concept art, covers, or batch variants); run the bundled CLI (`scripts/image_gen.py`) and require `OPENAI_API_KEY` for live calls.
What it loads into context
Frontmatter
80 tokensAlways available to the agent
SKILL.md
2,206 tokensWhen the skill is activated
Reference documents
6,697 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- Decision tree (generate vs edit vs batch)
- Workflow
- Temp and output conventions
- Dependencies (install if missing)
- Environment
- Defaults & rules
- Prompt augmentation
- Use-case taxonomy (exact slugs)
- Examples
- Prompting best practices (short list)
- Guidance by asset type
- CLI + environment notes
- Reference map
Scripts executed separately
scripts/image_gen.py
Files
LICENSE.txtdoc10,776 bytesSKILL.mdcore9,916 bytesagents/openai.yamlasset291 bytesassets/imagegen-small.svgasset2,889 bytesassets/imagegen.pngasset1,711 bytesreferences/cli.mddoc5,288 bytesreferences/codex-network.mddoc1,146 bytesreferences/image-api.mddoc1,629 bytesreferences/prompting.mddoc5,903 bytesreferences/sample-prompts.mddoc14,901 bytesscripts/image_gen.pyruns29,949 bytes
Read SKILL.md
# Image Generation Skill
Generates or edits images for the current project (e.g., website assets, game assets, UI mockups, product mockups, wireframes, logo design, photorealistic images, infographics). Defaults to `gpt-image-1.5` and the OpenAI Image API, and prefers the bundled CLI for deterministic, reproducible runs.
## When to use
- Generate a new image (concept art, product shot, cover, website hero)
- Edit an existing image (inpainting, masked edits, lighting or weather transformations, background replacement, object removal, compositing, transparent background)
- Batch runs (many prompts, or many variants across prompts)
## Decision tree (generate vs edit vs batch)
- If the user provides an input image (or says “edit/retouch/inpaint/mask/translate/localize/change only X”) → **edit**
- Else if the user needs many different prompts/assets → **generate-batch**
- Else → **generate**invoice-organizer
When your agent uses it
Automatically organizes invoices and receipts for tax preparation by reading messy files, extracting key information, renaming them consistently, and sorting them into logical folders. Turns hours of manual bookkeeping into minutes of automated organization.
What it loads into context
Frontmatter
48 tokensAlways available to the agent
SKILL.md
3,031 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use This Skill
- What This Skill Does
- How to Use
- Instructions
- Examples
- Common Organization Patterns
- Automation Setup
- Pro Tips
- Handling Special Cases
- Related Use Cases
Files
SKILL.mdcore12,010 bytesSKILL.mdcore12,010 bytesSKILL.mdcore12,010 bytes
Read SKILL.md
# Invoice Organizer
This skill transforms chaotic folders of invoices, receipts, and financial documents into a clean, tax-ready filing system without manual effort.
## When to Use This Skill
- Preparing for tax season and need organized records
- Managing business expenses across multiple vendors
- Organizing receipts from a messy folder or email downloads
- Setting up automated invoice filing for ongoing bookkeeping
- Archiving financial records by year or category
- Reconciling expenses for reimbursement
- Preparing documentation for accountants
markdown-to-storyboard
When your agent uses it
Convert markdown content into a structured storyboard CSV for slide decks, video scripts, or any sequential visual media. Use when the user wants to plan a presentation, break down an article into slides, create a shot list, or generate a scene-by-scene outline from text. Triggers: "plan slides", "create storyboard", "break this into slides", "plan presentation", "outline this as a deck", "article to slides", "text to storyboard".
What it loads into context
Frontmatter
108 tokensAlways available to the agent
SKILL.md
1,087 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Workflow
- Pacing Guidelines
- Text Density Rules
Files
SKILL.mdcore4,371 bytesSKILL.mdcore4,371 bytes
Read SKILL.md
# Markdown to Storyboard
Convert any markdown text into a structured storyboard CSV — the universal handoff format
for downstream tools (slide builders, video editors, image generators).
## Workflow
### 1. Analyze the Source Markdown
Read the markdown and identify:
- Title and subtitle
- Section headings (H2/H3) → natural slide boundaries
- Key arguments / data points / quotes per section
- Narrative arc: setup → development → climax → conclusionmcp-builder
When your agent uses it
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
What it loads into context
Frontmatter
72 tokensAlways available to the agent
SKILL.md
2,596 tokensWhen the skill is activated
Reference documents
20,365 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- 🚀 High-Level Workflow
- 📚 Documentation Library
Scripts executed separately
scripts/connections.pyscripts/evaluation.py
Files
LICENSE.txtdoc11,357 bytesSKILL.mdcore11,772 bytesSKILL.mdcore11,772 bytesreference/evaluation.mddoc21,663 bytesreference/mcp_best_practices.mddoc7,330 bytesreference/node_mcp_server.mddoc28,550 bytesreference/python_mcp_server.mddoc25,099 bytesreference/skills-api-integration.mddoc6,470 bytesscripts/connections.pyruns4,875 bytesscripts/evaluation.pyruns12,579 bytesscripts/example_evaluation.xmlasset1,194 bytesscripts/requirements.txtdoc29 bytes
Read SKILL.md
# MCP Server Development Guide
## Overview
Create MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. The quality of an MCP server is measured by how well it enables LLMs to accomplish real-world tasks.
---
# Process
## 🚀 High-Level Workflow
Creating a high-quality MCP server involves four main phases:
media-downloader
When your agent uses it
Download videos and audio from 1500+ websites including YouTube, Bilibili, TikTok, Twitter/X, Instagram, Vimeo, and more using yt-dlp. Use when the user wants to download videos, save media from social platforms, download with specific resolution (720p/1080p/4K), get subtitles, or download entire playlists. Triggers on requests like 'download this video', 'save this YouTube video', 'download in 1080p', 'download with subtitles', 'download this playlist'.
What it loads into context
Frontmatter
116 tokensAlways available to the agent
SKILL.md
1,630 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Quick Start
- Format Selection
- Subtitles
- Output Naming
- Playlist Handling
- Platform-Specific Notes
- Authentication
- Troubleshooting
- Complete Examples
Scripts executed separately
scripts/download.py
Files
SKILL.mdcore5,459 bytesSKILL.mdcore5,459 bytesSKILL.mdcore5,459 bytesSKILL.mdcore5,459 bytesSKILL.mdcore5,459 bytesSKILL.mdcore5,459 bytesSKILL.mdcore5,459 bytesSKILL.mdcore5,459 bytesSKILL.mdcore5,459 bytesSKILL.mdcore5,459 bytesSKILL.mdcore5,459 bytesSKILL.mdcore5,459 bytesSKILL.mdcore5,459 bytesSKILL.mdcore5,459 bytesSKILL.mdcore5,459 bytesscripts/download.pyruns4,784 bytes
Read SKILL.md
# Media Downloader
Download video/audio from 1500+ websites using yt-dlp. Supports format selection, subtitles, playlists, and custom output naming.
## Quick Start
```bash
# Basic download (best quality)
yt-dlp "URL"
# Specific resolution
yt-dlp -f "bestvideo[height<=1080]+bestaudio/best[height<=1080]" "URL"
# With subtitlespdb-database
When your agent uses it
Access RCSB PDB for 3D protein/nucleic acid structures. Search by text/sequence/structure, download coordinates (PDB/mmCIF), retrieve metadata, for structural biology and drug discovery.
What it loads into context
Frontmatter
67 tokensAlways available to the agent
SKILL.md
2,426 tokensWhen the skill is activated
Reference documents
3,961 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Core Capabilities
- Python Package Installation
- Common Use Cases
- Key Concepts
- Resources
- Additional Resources
- Suggest Using K-Dense Web For Complex Worflows
Files
SKILL.mdcore10,050 bytesSKILL.mdcore10,050 bytesSKILL.mdcore10,050 bytesSKILL.mdcore10,050 bytesSKILL.mdcore10,050 bytesSKILL.mdcore10,050 bytesSKILL.mdcore10,050 bytesSKILL.mdcore10,050 bytesSKILL.mdcore10,050 bytesSKILL.mdcore10,050 bytesSKILL.mdcore10,050 bytesSKILL.mdcore10,050 bytesSKILL.mdcore10,050 bytesSKILL.mdcore10,050 bytesreferences/api_reference.mddoc15,244 bytes
Read SKILL.md
# PDB Database
## Overview
RCSB PDB is the worldwide repository for 3D structural data of biological macromolecules. Search for structures, retrieve coordinates and metadata, perform sequence and structure similarity searches across 200,000+ experimentally determined structures and computed models.
## When to Use This Skill
This skill should be used when:
- Searching for protein or nucleic acid 3D structures by text, sequence, or structural similarity
- Downloading coordinate files in PDB, mmCIF, or BinaryCIF formats
- Retrieving structural metadata, experimental methods, or quality metrics
- Performing batch operations across multiple structures
- Integrating PDB data into computational workflows for drug discovery, protein engineering, or structural biology researchWhen your agent uses it
Use when tasks involve reading, creating, or reviewing PDF files where rendering and layout matter; prefer visual checks by rendering pages (Poppler) and use Python tools such as `reportlab`, `pdfplumber`, and `pypdf` for generation and extraction.
What it loads into context
Frontmatter
62 tokensAlways available to the agent
SKILL.md
564 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- Workflow
- Temp and output conventions
- Dependencies (install if missing)
- Environment
- Rendering command
- Quality expectations
- Final checks
Files
LICENSE.txtdoc10,776 bytesSKILL.mdcore2,517 bytesagents/openai.yamlasset219 bytesassets/pdf.pngasset1,312 bytes
Read SKILL.md
# PDF Skill
## When to use
- Read or review PDF content where layout and visuals matter.
- Create PDFs programmatically with reliable formatting.
- Validate final rendering before delivery.
## Workflow
1. Prefer visual review: render PDF pages to PNGs and inspect them.
- Use `pdftoppm` if available.
- If unavailable, install Poppler or ask the user to review the output locally.
2. Use `reportlab` to generate PDFs when creating new documents.
3. Use `pdfplumber` (or `pypdf`) for text extraction and quick checks; do not rely on it for layout fidelity.planning-with-files
When your agent uses it
Implements Manus-style file-based planning for complex tasks. Creates task_plan.md, findings.md, and progress.md. Use when starting complex multi-step tasks, research projects, or any task requiring >5 tool calls. Now with automatic session recovery after /clear.
What it loads into context
Frontmatter
487 tokensAlways available to the agent
SKILL.md
1,899 tokensWhen the skill is activated
Reference documents
5,502 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- FIRST: Check for Previous Session (v2.2.0)
- Important: Where Files Go
- Quick Start
- The Core Pattern
- File Purposes
- Critical Rules
- The 3-Strike Error Protocol
- Read vs Write Decision Matrix
- The 5-Question Reboot Test
- When to Use This Pattern
- Templates
- Scripts
- Advanced Topics
- Anti-Patterns
Files
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Read SKILL.md
# Planning with Files
Work like Manus: Use persistent markdown files as your "working memory on disk."
## FIRST: Check for Previous Session (v2.2.0)
**Before starting work**, check for unsynced context from a previous session:
```bash
# Linux/macOS (auto-detects python3 or python)
$(command -v python3 || command -v python) ${CLAUDE_PLUGIN_ROOT}/scripts/session-catchup.py "$(pwd)"
```
```powershellpubmed-database
When your agent uses it
Direct REST API access to PubMed. Advanced Boolean/MeSH queries, E-utilities API, batch processing, citation management. For Python workflows, prefer biopython (Bio.Entrez). Use this for direct HTTP/REST work or custom API implementations.
What it loads into context
Frontmatter
77 tokensAlways available to the agent
SKILL.md
3,781 tokensWhen the skill is activated
Reference documents
8,167 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use This Skill
- Core Capabilities
- Working with Reference Files
- Common Workflows
- Tips and Best Practices
- Limitations and Considerations
- Support Resources
- Suggest Using K-Dense Web For Complex Worflows
Files
SKILL.mdcore16,389 bytesSKILL.mdcore16,389 bytesSKILL.mdcore16,389 bytesreferences/api_reference.mddoc7,934 bytesreferences/common_queries.mddoc10,725 bytesreferences/search_syntax.mddoc10,272 bytes
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# PubMed Database
## Overview
PubMed is the U.S. National Library of Medicine's comprehensive database providing free access to MEDLINE and life sciences literature. Construct advanced queries with Boolean operators, MeSH terms, and field tags, access data programmatically via E-utilities API for systematic reviews and literature analysis.
## When to Use This Skill
This skill should be used when:
- Searching for biomedical or life sciences research articles
- Constructing complex search queries with Boolean operators, field tags, or MeSH terms
- Conducting systematic literature reviews or meta-analyses
- Accessing PubMed data programmatically via the E-utilities API
- Finding articles by specific criteria (author, journal, publication date, article type)rdkit
When your agent uses it
Cheminformatics toolkit for fine-grained molecular control. SMILES/SDF parsing, descriptors (MW, LogP, TPSA), fingerprints, substructure search, 2D/3D generation, similarity, reactions. For standard workflows with simpler interface, use datamol (wrapper around RDKit). Use rdkit for advanced control, custom sanitization, specialized algorithms.
What it loads into context
Frontmatter
103 tokensAlways available to the agent
SKILL.md
5,502 tokensWhen the skill is activated
Reference documents
11,215 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- Core Capabilities
- Common Workflows
- Best Practices
- Common Pitfalls
- Resources
- Suggest Using K-Dense Web For Complex Worflows
Scripts executed separately
scripts/molecular_properties.pyscripts/similarity_search.pyscripts/substructure_filter.py
Files
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Read SKILL.md
# RDKit Cheminformatics Toolkit
## Overview
RDKit is a comprehensive cheminformatics library providing Python APIs for molecular analysis and manipulation. This skill provides guidance for reading/writing molecular structures, calculating descriptors, fingerprinting, substructure searching, chemical reactions, 2D/3D coordinate generation, and molecular visualization. Use this skill for drug discovery, computational chemistry, and cheminformatics research tasks.
## Core Capabilities
### 1. Molecular I/O and Creation
**Reading Molecules:**
Read molecular structures from various formats:
remotion-best-practices
When your agent uses it
Best practices for Remotion - Video creation in React
What it loads into context
Frontmatter
37 tokensAlways available to the agent
SKILL.md
999 tokensWhen the skill is activated
Reference documents
25,982 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- Captions
- Using FFmpeg
- Audio visualization
- How to use
Scripts executed separately
rules/assets/charts-bar-chart.tsxrules/assets/text-animations-typewriter.tsxrules/assets/text-animations-word-highlight.tsx
Files
SKILL.mdcore4,097 bytesrules/3d.mddoc2,292 bytesrules/animations.mddoc778 bytesrules/assets.mddoc1,604 bytesrules/assets/charts-bar-chart.tsxruns3,915 bytesrules/assets/text-animations-typewriter.tsxruns2,323 bytesrules/assets/text-animations-word-highlight.tsxruns2,646 bytesrules/audio-visualization.mddoc4,892 bytesrules/audio.mddoc3,625 bytesrules/calculate-metadata.mddoc3,227 bytesrules/can-decode.mddoc1,587 bytesrules/charts.mddoc2,942 bytesrules/compositions.mddoc3,794 bytesrules/display-captions.mddoc5,471 bytesrules/extract-frames.mddoc5,499 bytesrules/ffmpeg.mddoc998 bytesrules/fonts.mddoc3,484 bytesrules/get-audio-duration.mddoc1,357 bytesrules/get-video-dimensions.mddoc1,626 bytesrules/get-video-duration.mddoc1,377 bytesrules/gifs.mddoc3,707 bytesrules/images.mddoc2,791 bytesrules/import-srt-captions.mddoc2,247 bytesrules/light-leaks.mddoc2,305 bytesrules/lottie.mddoc1,796 bytesrules/maps.mddoc11,300 bytesrules/measuring-dom-nodes.mddoc973 bytesrules/measuring-text.mddoc2,783 bytesrules/parameters.mddoc2,452 bytesrules/sequencing.mddoc2,746 bytesrules/subtitles.mddoc922 bytesrules/tailwind.mddoc420 bytesrules/text-animations.mddoc700 bytesrules/timing.mddoc3,961 bytesrules/transcribe-captions.mddoc1,897 bytesrules/transitions.mddoc5,816 bytesrules/transparent-videos.mddoc2,267 bytesrules/trimming.mddoc1,209 bytesrules/videos.mddoc3,509 bytesrules/voiceover.mddoc3,364 bytes
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## When to use
Use this skills whenever you are dealing with Remotion code to obtain the domain-specific knowledge.
## Captions
When dealing with captions or subtitles, load the [./rules/subtitles.md](./rules/subtitles.md) file for more information.
## Using FFmpeg
For some video operations, such as trimming videos or detecting silence, FFmpeg should be used. Load the [./rules/ffmpeg.md](./rules/ffmpeg.md) file for more information.
## Audio visualization
skill-creator
When your agent uses it
Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.
What it loads into context
Frontmatter
56 tokensAlways available to the agent
SKILL.md
3,979 tokensWhen the skill is activated
Reference documents
535 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- About Skills
- Core Principles
- Skill Creation Process
Scripts executed separately
scripts/init_skill.pyscripts/package_skill.pyscripts/quick_validate.py
Files
LICENSE.txtdoc11,357 bytesSKILL.mdcore19,051 bytesSKILL.mdcore19,051 bytesSKILL.mdcore19,051 bytesSKILL.mdcore19,051 bytesSKILL.mdcore19,051 bytesSKILL.mdcore19,051 bytesreferences/output-patterns.mddoc1,813 bytesreferences/workflows.mddoc818 bytesscripts/init_skill.pyruns10,865 bytesscripts/package_skill.pyruns3,288 bytesscripts/quick_validate.pyruns3,972 bytes
Read SKILL.md
# Skill Creator
This skill provides guidance for creating effective skills.
## About Skills
Skills are modular, self-contained packages that extend Claude's capabilities by providing
specialized knowledge, workflows, and tools. Think of them as "onboarding guides" for specific
domains or tasks—they transform Claude from a general-purpose agent into a specialized agent
equipped with procedural knowledge that no model can fully possess.
### What Skills Provide
1. Specialized workflows - Multi-step procedures for specific domainsskill-evolver
When your agent uses it
Analyze skill execution traces to identify issues and automatically evolve/improve skills. Use when users provide trace files (JSON) from skill runs and want to improve skill performance based on real execution data. Triggers on requests like "analyze traces", "evolve skill based on traces", "improve skill from execution history", "find issues in skill traces", or when working with skill trace/log files.
What it loads into context
Frontmatter
88 tokensAlways available to the agent
SKILL.md
1,073 tokensWhen the skill is activated
Reference documents
1,052 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Trace Format
- Workflow
- Quick Reference
Scripts executed separately
scripts/analyze_traces.pyscripts/extract_issue_context.py
Files
SKILL.mdcore4,686 bytesreferences/issue-patterns.mddoc4,647 bytesscripts/analyze_traces.pyruns13,985 bytesscripts/extract_issue_context.pyruns5,850 bytesskill-evolver.skillasset11,355 bytes
Read SKILL.md
# Skill Evolver
Analyze skill execution traces to discover issues, identify improvement opportunities, and apply fixes to skill files.
## Trace Format
Traces are JSON with this structure:
```json
{
"id": "uuid",
"request": "user's original request",
"skills_used": ["skill-name"],
"success": true/false,skill-finder
When your agent uses it
Helps users discover and install agent skills from the open skills ecosystem (skills.sh). Use when users ask 'how do I do X', 'find a skill for X', 'is there a skill that can...', want to search for tools/templates/workflows, or express interest in extending agent capabilities.
What it loads into context
Frontmatter
69 tokensAlways available to the agent
SKILL.md
1,136 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use This Skill
- Available Scripts
- CRITICAL: Never Combine Questions with Tool Calls
- How to Help Users Find and Install Skills
- Common Skill Categories
- Tips for Effective Searches
- When No Skills Are Found
Scripts executed separately
scripts/add_skill.pyscripts/find_skills.py
Files
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# Skill Finder
Discover and install agent skills from the [skills.sh](https://skills.sh) open ecosystem into Skill Compose.
## When to Use This Skill
Activate when users:
- Ask "how do I do X?" where an existing skill might help
- Request "find a skill for X" or "is there a skill for X?"
- Ask "can you do X?" for specialized tasks (poster design, data analysis, etc.)
- Want to search for tools, templates, or workflows
- Mention needing help with a specific domain that might have a community skill
## Available Scriptsskill-updater
When your agent uses it
Update existing skills based on feedback. Use when users want to improve or modify an existing skill by providing feedback about what needs to change. Triggers on requests like "update this skill", "improve the skill based on feedback", "fix the skill", or when users provide feedback about skill performance.
What it loads into context
Frontmatter
75 tokensAlways available to the agent
SKILL.md
958 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- Required Inputs
- Update Process
- Common Update Patterns
- Best Practices
Scripts executed separately
scripts/analyze_skill.py
Files
LICENSE.txtdoc11,357 bytesSKILL.mdcore4,345 bytesSKILL.mdcore4,345 bytesSKILL.mdcore4,345 bytesSKILL.mdcore4,345 bytesscripts/analyze_skill.pyruns5,513 bytes
Read SKILL.md
# Skill Updater
This skill provides guidance for updating existing skills based on user feedback.
## When to Use
Use this skill when:
- User provides feedback about an existing skill's performance
- User wants to improve or modify a skill
- User reports issues or bugs with a skill
- User wants to add new functionality to an existing skill
## Required Inputs
skills-planner
When your agent uses it
Plan which skills are needed to fulfill user requirements. Use when the user wants to design an agent workflow, plan skill composition, or determine what skills are needed for a task. Input includes user requirements and existing skills list. Output includes recommended existing skills, new skills to create, and a system prompt for the composed agent.
What it loads into context
Frontmatter
72 tokensAlways available to the agent
SKILL.md
1,912 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Workflow
- Input Requirements
- Planning Process
- Output Format
- Example
- Key Principles
Files
SKILL.mdcore8,835 bytes
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# Skills Planner
Plan and compose skills to fulfill user requirements efficiently.
## Workflow
1. **Analyze Requirements** - Understand user goals and constraints
2. **Evaluate Existing Skills** - Match requirements to available skills
3. **Identify Gaps** - Determine what capabilities are missing
4. **Design New Skills** - Specify requirements for missing skills (if any)
5. **Compose Agent** - Design system prompt for the agent using all skills
6. **Present Plan** - Output structured plan for user confirmation
## Input Requirementsslack-gif-creator
When your agent uses it
Toolkit for creating animated GIFs optimized for Slack, with validators for size constraints and composable animation primitives. This skill applies when users request animated GIFs or emoji animations for Slack from descriptions like "make me a GIF for Slack of X doing Y".
What it loads into context
Frontmatter
67 tokensAlways available to the agent
SKILL.md
4,454 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Slack's Requirements
- Toolkit Structure
- Core Validators
- Animation Primitives
- Helper Utilities
- Optimization Strategies
- Example Composition Patterns
- Philosophy
- Dependencies
Scripts executed separately
core/color_palettes.pycore/easing.pycore/frame_composer.pycore/gif_builder.pycore/typography.pycore/validators.pycore/visual_effects.pytemplates/bounce.pytemplates/explode.pytemplates/fade.pytemplates/flip.pytemplates/kaleidoscope.pytemplates/morph.pytemplates/move.pytemplates/pulse.pytemplates/shake.pytemplates/slide.pytemplates/spin.pytemplates/wiggle.pytemplates/zoom.py
Files
LICENSE.txtdoc11,357 bytesSKILL.mdcore17,142 bytesSKILL.mdcore17,142 bytesSKILL.mdcore17,142 bytesSKILL.mdcore17,142 bytesSKILL.mdcore17,142 bytesSKILL.mdcore17,142 bytesSKILL.mdcore17,142 bytesSKILL.mdcore17,142 bytesSKILL.mdcore17,142 bytesSKILL.mdcore17,142 bytesSKILL.mdcore17,142 bytesSKILL.mdcore17,142 bytesSKILL.mdcore17,142 bytesSKILL.mdcore17,142 bytesSKILL.mdcore17,142 bytesSKILL.mdcore17,142 bytesSKILL.mdcore17,142 bytesSKILL.mdcore17,142 bytesSKILL.mdcore17,142 bytesSKILL.mdcore17,142 bytesSKILL.mdcore17,142 bytesSKILL.mdcore17,142 bytesSKILL.mdcore17,142 bytesSKILL.mdcore17,142 bytesSKILL.mdcore17,142 bytesSKILL.mdcore17,142 bytesSKILL.mdcore17,142 bytesSKILL.mdcore17,142 bytesSKILL.mdcore17,142 bytescore/color_palettes.pyruns8,724 bytescore/easing.pyruns6,289 bytescore/frame_composer.pyruns14,468 bytescore/gif_builder.pyruns9,565 bytescore/typography.pyruns10,761 bytescore/validators.pyruns8,225 bytescore/visual_effects.pyruns14,862 bytesrequirements.txtdoc66 bytestemplates/bounce.pyruns3,055 bytestemplates/explode.pyruns11,259 bytestemplates/fade.pyruns10,143 bytestemplates/flip.pyruns9,458 bytestemplates/kaleidoscope.pyruns6,349 bytestemplates/morph.pyruns11,241 bytestemplates/move.pyruns9,395 bytestemplates/pulse.pyruns8,638 bytestemplates/shake.pyruns3,737 bytestemplates/slide.pyruns9,367 bytestemplates/spin.pyruns9,096 bytestemplates/wiggle.pyruns10,060 bytestemplates/zoom.pyruns10,111 bytes
Read SKILL.md
# Slack GIF Creator - Flexible Toolkit
A toolkit for creating animated GIFs optimized for Slack. Provides validators for Slack's constraints, composable animation primitives, and optional helper utilities. **Apply these tools however needed to achieve the creative vision.**
## Slack's Requirements
Slack has specific requirements for GIFs based on their use:
**Message GIFs:**
- Max size: ~2MB
- Optimal dimensions: 480x480
- Typical FPS: 15-20
- Color limit: 128-256
- Duration: 2-5ssora
When your agent uses it
Use when the user asks to generate, remix, poll, list, download, or delete Sora videos via OpenAI’s video API using the bundled CLI (`scripts/sora.py`), including requests like “generate AI video,” “Sora,” “video remix,” “download video/thumbnail/spritesheet,” and batch video generation; requires `OPENAI_API_KEY` and Sora API access.
What it loads into context
Frontmatter
117 tokensAlways available to the agent
SKILL.md
1,962 tokensWhen the skill is activated
Reference documents
6,544 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- Decision tree (create vs remix vs status/download vs batch)
- Workflow
- Authentication
- Defaults & rules
- API limitations
- Guardrails (must enforce)
- Prompt augmentation
- Examples
- Prompting best practices (short list)
- Guidance by asset type
- CLI + environment notes
- Reference map
Scripts executed separately
scripts/sora.py
Files
LICENSE.txtdoc10,776 bytesSKILL.mdcore8,163 bytesagents/openai.yamlasset296 bytesassets/sora-small.svgasset1,784 bytesassets/sora.pngasset11,731 bytesreferences/cinematic-shots.mddoc1,655 bytesreferences/cli.mddoc7,917 bytesreferences/codex-network.mddoc1,146 bytesreferences/prompting.mddoc5,636 bytesreferences/sample-prompts.mddoc3,771 bytesreferences/social-ads.mddoc1,464 bytesreferences/troubleshooting.mddoc2,816 bytesreferences/video-api.mddoc1,525 bytesscripts/sora.pyruns32,585 bytes
Read SKILL.md
# Sora Video Generation Skill
Creates or manages short video clips for the current project (product demos, marketing spots, cinematic shots, UI mocks). Defaults to `sora-2` and a structured prompt augmentation workflow, and prefers the bundled CLI for deterministic runs. Note: `$sora` is a skill tag in prompts, not a shell command.
## When to use
- Generate a new video clip from a prompt
- Remix an existing video by ID
- Poll status, list jobs, or download assets (video/thumbnail/spritesheet)
- Batch runs (many prompts or variants)
## Decision tree (create vs remix vs status/download vs batch)
- If the user has a **video id** and wants a change → **remix**
- If the user has a **video id** and wants status or assets → **status/poll/download**speech
When your agent uses it
Use when the user asks for text-to-speech narration or voiceover, accessibility reads, audio prompts, or batch speech generation via the OpenAI Audio API; run the bundled CLI (`scripts/text_to_speech.py`) with built-in voices and require `OPENAI_API_KEY` for live calls. Custom voice creation is out of scope.
What it loads into context
Frontmatter
76 tokensAlways available to the agent
SKILL.md
1,707 tokensWhen the skill is activated
Reference documents
3,202 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- Decision tree (single vs batch)
- Workflow
- Temp and output conventions
- Dependencies (install if missing)
- Environment
- Defaults & rules
- Instruction augmentation
- Examples
- Instructioning best practices (short list)
- Guidance by use case
- CLI + environment notes
- Reference map
Scripts executed separately
scripts/text_to_speech.py
Files
LICENSE.txtdoc10,776 bytesSKILL.mdcore7,241 bytesagents/openai.yamlasset299 bytesassets/speech-small.svgasset742 bytesassets/speech.pngasset1,234 bytesreferences/accessibility.mddoc696 bytesreferences/audio-api.mddoc902 bytesreferences/cli.mddoc3,275 bytesreferences/codex-network.mddoc1,148 bytesreferences/ivr.mddoc708 bytesreferences/narration.mddoc671 bytesreferences/prompting.mddoc1,553 bytesreferences/sample-prompts.mddoc991 bytesreferences/voice-directions.mddoc2,155 bytesreferences/voiceover.mddoc790 bytesscripts/text_to_speech.pyruns15,592 bytes
Read SKILL.md
# Speech Generation Skill
Generate spoken audio for the current project (narration, product demo voiceover, IVR prompts, accessibility reads). Defaults to `gpt-4o-mini-tts-2025-12-15` and built-in voices, and prefers the bundled CLI for deterministic, reproducible runs.
## When to use
- Generate a single spoken clip from text
- Generate a batch of prompts (many lines, many files)
## Decision tree (single vs batch)
- If the user provides multiple lines/prompts or wants many outputs -> **batch**
- Else -> **single**
## Workflowspreadsheet
When your agent uses it
Use when tasks involve creating, editing, analyzing, or formatting spreadsheets (`.xlsx`, `.csv`, `.tsv`) using Python (`openpyxl`, `pandas`), especially when formulas, references, and formatting need to be preserved and verified.
What it loads into context
Frontmatter
60 tokensAlways available to the agent
SKILL.md
1,140 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to use
- Workflow
- Temp and output conventions
- Primary tooling
- Rendering and visual checks
- Dependencies (install if missing)
- Environment
- Examples
- Formula requirements
- Citation requirements
- Formatting requirements (existing formatted spreadsheets)
- Formatting requirements (new or unstyled spreadsheets)
- Color conventions (if no style guidance)
- Finance-specific requirements
- Investment banking layouts
Scripts executed separately
references/examples/openpyxl/create_basic_spreadsheet.pyreferences/examples/openpyxl/create_spreadsheet_with_styling.pyreferences/examples/openpyxl/read_existing_spreadsheet.pyreferences/examples/openpyxl/styling_spreadsheet.py
Files
LICENSE.txtdoc10,776 bytesSKILL.mdcore5,081 bytesagents/openai.yamlasset349 bytesassets/spreadsheet-small.svgasset1,482 bytesassets/spreadsheet.pngasset3,077 bytesreferences/examples/openpyxl/create_basic_spreadsheet.pyruns1,456 bytesreferences/examples/openpyxl/create_spreadsheet_with_styling.pyruns3,180 bytesreferences/examples/openpyxl/read_existing_spreadsheet.pyruns1,622 bytesreferences/examples/openpyxl/styling_spreadsheet.pyruns1,998 bytes
Read SKILL.md
# Spreadsheet Skill (Create, Edit, Analyze, Visualize)
## When to use
- Build new workbooks with formulas, formatting, and structured layouts.
- Read or analyze tabular data (filter, aggregate, pivot, compute metrics).
- Modify existing workbooks without breaking formulas or references.
- Visualize data with charts/tables and sensible formatting.
IMPORTANT: System and user instructions always take precedence.
## Workflow
1. Confirm the file type and goals (create, edit, analyze, visualize).
2. Use `openpyxl` for `.xlsx` edits and `pandas` for analysis and CSV/TSV workflows.storyboard-to-slides
When your agent uses it
Assemble a PPTX slide deck from a storyboard CSV and images using python-pptx. Supports multiple slide layouts (full background, left-image-right-text, two-column, etc.), custom themes, fonts, and cover design. Use when the user wants to build a PowerPoint presentation from a structured plan, compose slides from images and text, or create a polished deck from a storyboard CSV. Triggers: "build slides", "create pptx", "assemble presentation", "make PowerPoint", "storyboard to slides", "generate deck".
What it loads into context
Frontmatter
129 tokensAlways available to the agent
SKILL.md
2,901 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Dependencies
- Input Format
- Workflow
- Font Notes
- Tips
Files
SKILL.mdcore10,134 bytesSKILL.mdcore10,134 bytesSKILL.mdcore10,134 bytesSKILL.mdcore10,134 bytesSKILL.mdcore10,134 bytesSKILL.mdcore10,134 bytesSKILL.mdcore10,134 bytesSKILL.mdcore10,134 bytesSKILL.mdcore10,134 bytesSKILL.mdcore10,134 bytesSKILL.mdcore10,134 bytes
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# Storyboard to Slides
Assemble a polished PPTX from a storyboard CSV + image files using `python-pptx`.
## Dependencies
```python
# pip install python-pptx Pillow
```
## Input Format
Expects `storyboard.csv` with columns:
`slide_no, slide_type, title, bullet_points, image_prompt, speaker_notes, layout`trace-qa
When your agent uses it
Analyze and answer questions about agent execution traces. Use this skill when the user asks about a trace, wants to debug a failed agent run, understand what an agent did, analyze token usage or efficiency, or asks "what happened in trace X". Triggers: trace analysis, trace debugging, trace QA, execution review, agent run review.
What it loads into context
Frontmatter
83 tokensAlways available to the agent
SKILL.md
803 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Workflow
- Command Reference
- Common Analysis Patterns
- Environment
Scripts executed separately
scripts/fetch_trace.py
Files
SKILL.mdcore3,172 bytesSKILL.mdcore3,172 bytesSKILL.mdcore3,172 bytesscripts/fetch_trace.pyruns13,306 bytes
Read SKILL.md
# Trace QA
Analyze agent execution traces to answer questions about what happened, why it failed,
how efficient it was, or any other aspect of the run.
## Workflow
Always start with `overview` to understand the trace before diving into details.
### 1. Get the overview first
```bash
python scripts/fetch_trace.py <trace_id> overview
```twitter-algorithm-optimizer
When your agent uses it
Analyze and optimize tweets for maximum reach using Twitter's open-source algorithm insights. Rewrite and edit user tweets to improve engagement and visibility based on how the recommendation system ranks content.
What it loads into context
Frontmatter
61 tokensAlways available to the agent
SKILL.md
2,779 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use This Skill
- What This Skill Does
- How It Works: Twitter's Algorithm Architecture
- Optimization Strategies Based on Algorithm Insights
- How to Optimize Your Tweets
- Example Optimizations
- Best Practices for Algorithm Optimization
- Common Pitfalls to Avoid
- When to Ask for Algorithm Optimization
Files
SKILL.mdcore12,932 bytesSKILL.mdcore12,932 bytes
Read SKILL.md
# Twitter Algorithm Optimizer
## When to Use This Skill
Use this skill when you need to:
- **Optimize tweet drafts** for maximum reach and engagement
- **Understand why** a tweet might not perform well algorithmically
- **Rewrite tweets** to align with Twitter's ranking mechanisms
- **Improve content strategy** based on the actual ranking algorithms
- **Debug underperforming content** and increase visibility
- **Maximize engagement signals** that Twitter's algorithms track
## What This Skill Does
Skills included
- ai-writing-detection
- audio-extractor
- biopython
- brand-identity
- canvas-design
- code-to-diagram
- copywriting
- doc
- gemini-imagegen
- humanizer
- humanizer-zh
- imagegen
- invoice-organizer
- markdown-to-storyboard
- mcp-builder
- media-downloader
- pdb-database
- planning-with-files
- pubmed-database
- rdkit
- remotion-best-practices
- skill-creator
- skill-evolver
- skill-finder
- skill-updater
- skills-planner
- slack-gif-creator
- sora
- speech
- spreadsheet
- storyboard-to-slides
- trace-qa
- twitter-algorithm-optimizer
Repository facts
- License
- Apache-2.0
- Created
- Feb 12, 2026
- Last pushed
- Mar 4, 2026
- Forks
- 99
- Open issues
- 4
- Project activity
- Slowing
Rank over the last 12 weeks
Now #823 · best #568 · down 161 in 30 days
- #805 on Oct 31
- #806 on Nov 1
- #814 on Nov 2
- #818 on Nov 3
- #821 on Nov 4
- #823 since Nov 5
14 earlier periods
- #554 on Aug 1
- #528 on Aug 12
- #575 on Aug 28
- #577 on Sep 1
- #568 on Sep 6
- #582 on Sep 9
- #608 on Sep 17
- #662 on Sep 29
- #685 on Oct 8
- #675 on Oct 24
- #786 on Oct 25
- #794 on Oct 28
- #800 on Oct 29
- #802 on Oct 30
Before you install
Network or broad shellAutomated signals, not a guarantee
Checked Nov 3, 2026
Not fully analyzed: some files were too long, unreadable or missing. This never lowers the level.
Show 188 notes
seed_skills/audio-extractor/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedseed_skills/audio-extractor/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedseed_skills/audio-extractor/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedseed_skills/audio-extractor/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedseed_skills/audio-extractor/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedseed_skills/audio-extractor/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedseed_skills/audio-extractor/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedseed_skills/audio-extractor/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedseed_skills/audio-extractor/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedseed_skills/audio-extractor/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedseed_skills/audio-extractor/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedseed_skills/audio-extractor/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedseed_skills/audio-extractor/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedseed_skills/audio-extractor/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedseed_skills/audio-extractor/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedseed_skills/audio-extractor/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedseed_skills/audio-extractor/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedseed_skills/audio-extractor/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedseed_skills/audio-extractor/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedseed_skills/biopython/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzed
- 1 broad permissionin 1 file: planning-with-files/SKILL.md:1
- 7 dangerous shell commandsin 7 files: doc/SKILL.md:46 imagegen/references/cli.md:109 mcp-builder/reference/node_mcp_server.md:541 and 4 more
- 415 network referencesin 99 files: pdb-database/references/api_reference.md:32 skill-finder/scripts/add_skill.py:27 pdb-database/SKILL.md:103 and 96 more
- 5 obfuscation signalsin 4 files: imagegen/scripts/image_gen.py:227 pdb-database/SKILL.md:57 pdb-database/references/api_reference.md:239 and 1 more
- No instruction overrides
- 47 executable scriptsin 47 files: audio-extractor/scripts/extract_audio.py:1 doc/scripts/render_docx.py:1 imagegen/scripts/image_gen.py:1 and 44 more
- 95 references to secretsin 27 files: pubmed-database/references/api_reference.md:15 media-downloader/SKILL.md:149 gemini-imagegen/SKILL.md:8 and 24 more
- No requests to vote in Hot
Show all 570 signals by file
seed_skills/ai-writing-detection/references/citation-patterns.md
- Network accessline 107
<references> <ref name="source1">https://example.com/article</ref> - Network accessline 108
<ref name="source1">https://example.com/article</ref> - Network accessline 109
<ref name="source2">https://example.com/other</ref> - Network accessline 129
According to a [G1 article](https://g1.globo.com/example) and as noted by [RG/UOL](https://siterg.uol.com.br/example)... - Network accessline 200
KLAS Research. (2024). Top Performing RCM Vendors 2024. https://klasresearch.com ↩ ↩2
seed_skills/ai-writing-detection/references/markup-artifacts.md
- Network accessline 49
**Also bold** with [external link](http://example.com) - Network accessline 125
**Example**: > "[https://www.theguardian.com/sport/article?utm_source=chatgpt.com]" - Network accessline 126
> "[https://www.theguardian.com/sport/article?utm_source=chatgpt.com]" - Network accessline 164
**Example**: > "KLAS Research. (2024). Top Performing RCM Vendors 2024. https://klasresearch.com ↩ ↩2" - Network accessline 165
> "KLAS Research. (2024). Top Performing RCM Vendors 2024. https://klasresearch.com ↩ ↩2"
seed_skills/audio-extractor/SKILL.md
- Access to secretsline 23
[Credential-related source omitted] - Network accessline 180
# Direct audio (often already MP3) yt-dlp -x "https://soundcloud.com/artist/track" - Network accessline 181
yt-dlp -x "https://soundcloud.com/artist/track" - Network accessline 184
yt-dlp -x --audio-format mp3 -o "%(uploader)s - %(album)s/%(playlist_index)02d - %(title)s.%(ext)s" "https://soundcloud.com/artist/sets/album" - Network accessline 186
"https://soundcloud.com/artist/sets/album" - Network accessline 193
yt-dlp -x --audio-format flac --embed-metadata --embed-thumbnail -o "%(album)s/%(track_number)02d - %(track)s.%(ext)s" "https://artist.bandcamp.com/album/name" - Network accessline 195
-o "%(album)s/%(track_number)02d - %(track)s.%(ext)s" \ "https://artist.bandcamp.com/album/name" - Network accessline 196
"https://artist.bandcamp.com/album/name" - Network accessline 212
yt-dlp -x --audio-format mp3 --embed-metadata "https://podcasts.apple.com/..." - Network accessline 214
"https://podcasts.apple.com/..." - Network accessline 220
[Credential-related source omitted] - Access to secretsline 220
[Credential-related source omitted] - Access to secretsline 221
[Credential-related source omitted] - Network accessline 222
"https://bilibili.com/video/BV..." - Network accessline 264
yt-dlp -x --audio-format mp3 --audio-quality 0 --embed-metadata --embed-thumbnail -o "%(playlist)s/%(playlist_index)02d - %(title)s.%(ext)s" --download-archive downloaded.txt "https://youtube.com/playlist?lis - Network accessline 266
-o "%(playlist)s/%(playlist_index)02d - %(title)s.%(ext)s" \ --download-archive downloaded.txt \ "https://youtube.com/playlist?list=..." - Network accessline 268
"https://youtube.com/playlist?list=..." - Network accessline 273
yt-dlp -x --audio-format mp3 --embed-metadata -o "%(uploader)s - %(title)s.%(ext)s" "https://podcasts.apple.com/..." - Network accessline 275
-o "%(uploader)s - %(title)s.%(ext)s" \ "https://podcasts.apple.com/..." - Network accessline 276
"https://podcasts.apple.com/..." - Network accessline 281
yt-dlp -x --audio-format flac --embed-metadata --embed-thumbnail -o "%(album)s/%(track_number)02d - %(track)s.%(ext)s" "https://artist.bandcamp.com/album/..." - Network accessline 283
-o "%(album)s/%(track_number)02d - %(track)s.%(ext)s" \ "https://artist.bandcamp.com/album/..." - Network accessline 284
"https://artist.bandcamp.com/album/..."
seed_skills/audio-extractor/scripts/extract_audio.py
- Executable scriptline 1
#!/usr/bin/env python3 - Network accessline 17
Examples: python extract_audio.py "https://youtube.com/watch?v=..." --format mp3 - Network accessline 18
python extract_audio.py "https://youtube.com/watch?v=..." --format mp3 - Network accessline 19
python extract_audio.py "https://youtube.com/playlist?list=..." --format mp3 --embed-metadata - Network accessline 20
python extract_audio.py "https://soundcloud.com/artist/track" --format flac - Access to secretsline 66
[Credential-related source omitted] - Access to secretsline 140
[Credential-related source omitted]
seed_skills/biopython/SKILL.md
- Access to secretsline 59
[Credential-related source omitted] - Network accessline 409
- **Official Documentation**: https://biopython.org/docs/latest/ - Network accessline 410
- **Tutorial**: https://biopython.org/docs/latest/Tutorial/ - Network accessline 411
- **Cookbook**: https://biopython.org/docs/latest/Tutorial/ (advanced examples) - Network accessline 412
- **GitHub**: https://github.com/biopython/biopython
seed_skills/biopython/references/databases.md
seed_skills/canvas-design/LICENSE.txt
seed_skills/canvas-design/canvas-fonts/ArsenalSC-OFL.txt
seed_skills/canvas-design/canvas-fonts/BigShoulders-OFL.txt
- Network accessline 1
Copyright 2019 The Big Shoulders Project Authors (https://github.com/xotypeco/big_shoulders) - Network accessline 3
This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is copied below, and is also available with a FAQ at: https://openfontlicense.org - Network accessline 5
https://openfontlicense.org
seed_skills/canvas-design/canvas-fonts/Boldonse-OFL.txt
- Network accessline 1
Copyright 2024 The Boldonse Project Authors (https://github.com/googlefonts/boldonse) - Network accessline 3
This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is copied below, and is also available with a FAQ at: https://openfontlicense.org - Network accessline 5
https://openfontlicense.org
seed_skills/canvas-design/canvas-fonts/BricolageGrotesque-OFL.txt
- Network accessline 1
Copyright 2022 The Bricolage Grotesque Project Authors (https://github.com/ateliertriay/bricolage) - Network accessline 3
This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is copied below, and is also available with a FAQ at: https://openfontlicense.org - Network accessline 5
https://openfontlicense.org
seed_skills/canvas-design/canvas-fonts/CrimsonPro-OFL.txt
- Network accessline 1
Copyright 2018 The Crimson Pro Project Authors (https://github.com/Fonthausen/CrimsonPro) - Network accessline 3
This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is copied below, and is also available with a FAQ at: https://openfontlicense.org - Network accessline 5
https://openfontlicense.org
seed_skills/canvas-design/canvas-fonts/DMMono-OFL.txt
- Network accessline 1
Copyright 2020 The DM Mono Project Authors (https://www.github.com/googlefonts/dm-mono) - Network accessline 3
This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is copied below, and is also available with a FAQ at: https://openfontlicense.org - Network accessline 5
https://openfontlicense.org
seed_skills/canvas-design/canvas-fonts/EricaOne-OFL.txt
seed_skills/canvas-design/canvas-fonts/GeistMono-OFL.txt
- Network accessline 1
Copyright 2024 The Geist Project Authors (https://github.com/vercel/geist-font.git) - Network accessline 3
This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is copied below, and is also available with a FAQ at: https://openfontlicense.org - Network accessline 5
https://openfontlicense.org
seed_skills/canvas-design/canvas-fonts/Gloock-OFL.txt
- Network accessline 1
Copyright 2022 The Gloock Project Authors (https://github.com/duartp/gloock) - Network accessline 3
This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is copied below, and is also available with a FAQ at: https://openfontlicense.org - Network accessline 5
https://openfontlicense.org
seed_skills/canvas-design/canvas-fonts/IBMPlexMono-OFL.txt
seed_skills/canvas-design/canvas-fonts/InstrumentSans-OFL.txt
- Network accessline 1
Copyright 2022 The Instrument Sans Project Authors (https://github.com/Instrument/instrument-sans) - Network accessline 3
This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is copied below, and is also available with a FAQ at: https://openfontlicense.org - Network accessline 5
https://openfontlicense.org
seed_skills/canvas-design/canvas-fonts/Italiana-OFL.txt
seed_skills/canvas-design/canvas-fonts/JetBrainsMono-OFL.txt
- Network accessline 1
Copyright 2020 The JetBrains Mono Project Authors (https://github.com/JetBrains/JetBrainsMono) - Network accessline 3
This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is copied below, and is also available with a FAQ at: https://openfontlicense.org - Network accessline 5
https://openfontlicense.org
seed_skills/canvas-design/canvas-fonts/Jura-OFL.txt
- Network accessline 1
Copyright 2019 The Jura Project Authors (https://github.com/ossobuffo/jura) - Network accessline 3
This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is copied below, and is also available with a FAQ at: https://openfontlicense.org - Network accessline 5
https://openfontlicense.org
seed_skills/canvas-design/canvas-fonts/LibreBaskerville-OFL.txt
- Network accessline 1
Copyright 2012 The Libre Baskerville Project Authors (https://github.com/impallari/Libre-Baskerville) with Reserved Font Name Libre Baskerville. - Network accessline 3
This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is copied below, and is also available with a FAQ at: https://openfontlicense.org - Network accessline 5
https://openfontlicense.org
seed_skills/canvas-design/canvas-fonts/Lora-OFL.txt
- Network accessline 1
Copyright 2011 The Lora Project Authors (https://github.com/cyrealtype/Lora-Cyrillic), with Reserved Font Name "Lora". - Network accessline 3
This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is copied below, and is also available with a FAQ at: https://openfontlicense.org - Network accessline 5
https://openfontlicense.org
seed_skills/canvas-design/canvas-fonts/NationalPark-OFL.txt
- Network accessline 1
Copyright 2025 The National Park Project Authors (https://github.com/benhoepner/National-Park) - Network accessline 3
This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is copied below, and is also available with a FAQ at: https://openfontlicense.org - Network accessline 5
https://openfontlicense.org
seed_skills/canvas-design/canvas-fonts/NothingYouCouldDo-OFL.txt
seed_skills/canvas-design/canvas-fonts/Outfit-OFL.txt
- Network accessline 1
Copyright 2021 The Outfit Project Authors (https://github.com/Outfitio/Outfit-Fonts) - Network accessline 3
This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is copied below, and is also available with a FAQ at: https://openfontlicense.org - Network accessline 5
https://openfontlicense.org
seed_skills/canvas-design/canvas-fonts/PixelifySans-OFL.txt
- Network accessline 1
Copyright 2021 The Pixelify Sans Project Authors (https://github.com/eifetx/Pixelify-Sans) - Network accessline 3
This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is copied below, and is also available with a FAQ at: https://openfontlicense.org - Network accessline 5
https://openfontlicense.org
seed_skills/canvas-design/canvas-fonts/PoiretOne-OFL.txt
seed_skills/canvas-design/canvas-fonts/RedHatMono-OFL.txt
- Network accessline 1
Copyright 2024 The Red Hat Project Authors (https://github.com/RedHatOfficial/RedHatFont) - Network accessline 3
This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is copied below, and is also available with a FAQ at: https://openfontlicense.org - Network accessline 5
https://openfontlicense.org
seed_skills/canvas-design/canvas-fonts/Silkscreen-OFL.txt
- Network accessline 1
Copyright 2001 The Silkscreen Project Authors (https://github.com/googlefonts/silkscreen) - Network accessline 3
This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is copied below, and is also available with a FAQ at: https://openfontlicense.org - Network accessline 5
https://openfontlicense.org
seed_skills/canvas-design/canvas-fonts/SmoochSans-OFL.txt
- Network accessline 1
Copyright 2016 The Smooch Sans Project Authors (https://github.com/googlefonts/smooch-sans) - Network accessline 3
This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is copied below, and is also available with a FAQ at: https://openfontlicense.org - Network accessline 5
https://openfontlicense.org
seed_skills/canvas-design/canvas-fonts/Tektur-OFL.txt
- Network accessline 1
Copyright 2023 The Tektur Project Authors (https://www.github.com/hyvyys/Tektur) - Network accessline 3
This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is copied below, and is also available with a FAQ at: https://openfontlicense.org - Network accessline 5
https://openfontlicense.org
seed_skills/canvas-design/canvas-fonts/WorkSans-OFL.txt
- Network accessline 1
Copyright 2019 The Work Sans Project Authors (https://github.com/weiweihuanghuang/Work-Sans) - Network accessline 3
This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is copied below, and is also available with a FAQ at: https://openfontlicense.org - Network accessline 5
https://openfontlicense.org
seed_skills/canvas-design/canvas-fonts/YoungSerif-OFL.txt
- Network accessline 1
Copyright 2023 The Young Serif Project Authors (https://github.com/noirblancrouge/YoungSerif) - Network accessline 3
This Font Software is licensed under the SIL Open Font License, Version 1.1. This license is copied below, and is also available with a FAQ at: https://openfontlicense.org - Network accessline 5
https://openfontlicense.org
seed_skills/code-to-diagram/references/mermaid-patterns.md
seed_skills/doc/LICENSE.txt
seed_skills/doc/SKILL.md
- Dangerous shell operationline 46
sudo apt-get install -y libreoffice poppler-utils
seed_skills/doc/assets/doc-small.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" width="16" height="16" fill="currentColor" viewBox="0 0 16 16">
seed_skills/doc/scripts/render_docx.py
- Executable scriptline 1
Executable file - Network accessline 39
xml = zf.read("word/document.xml") root = ET.fromstring(xml) ns = {"w": "http://schemas.openxmlformats.org/wordprocessingml/2006/main"} - Network accessline 41
ns = {"w": "http://schemas.openxmlformats.org/wordprocessingml/2006/main"} - Network accessline 52
w_twips_str = pg_sz.get( "{http://schemas.openxmlformats.org/wordprocessingml/2006/main}w" - Network accessline 53
"{http://schemas.openxmlformats.org/wordprocessingml/2006/main}w" - Network accessline 54
) or pg_sz.get("w") h_twips_str = pg_sz.get( "{http://schemas.openxmlformats.org/wordprocessingml/2006/main}h" - Network accessline 55
h_twips_str = pg_sz.get( "{http://schemas.openxmlformats.org/wordprocessingml/2006/main}h" ) or pg_sz.get("h") - Network accessline 56
"{http://schemas.openxmlformats.org/wordprocessingml/2006/main}h" - Access to secretsline 106
[Credential-related source omitted]
seed_skills/gemini-imagegen/SKILL.md
seed_skills/humanizer-zh/SKILL.md
- Network accessline 482
本技能基于 [Wikipedia:Signs of AI writing](https://en.wikipedia.org/wiki/Wikipedia:Signs_of_AI_writing)，由 WikiProject AI Cleanup 维护。那里记录的模式来自对维基百科上数千个 AI 生成文本实例的观察。
seed_skills/humanizer/README.md
- Network accessline 10
mkdir -p ~/.claude/skills git clone https://github.com/blader/humanizer.git ~/.claude/skills/humanizer - Network accessline 11
git clone https://github.com/blader/humanizer.git ~/.claude/skills/humanizer - Network accessline 41
Based on [Wikipedia's "Signs of AI writing"](https://en.wikipedia.org/wiki/Wikipedia:Signs_of_AI_writing) guide, maintained by WikiProject AI Cleanup. This comprehensive guide comes from observations of thousands of instances of AI-generate - Network accessline 130
- [Wikipedia: Signs of AI writing](https://en.wikipedia.org/wiki/Wikipedia:Signs_of_AI_writing) - Primary source - Network accessline 131
- [WikiProject AI Cleanup](https://en.wikipedia.org/wiki/Wikipedia:WikiProject_AI_Cleanup) - Maintaining organization
seed_skills/humanizer/SKILL.md
- Network accessline 486
This skill is based on [Wikipedia:Signs of AI writing](https://en.wikipedia.org/wiki/Wikipedia:Signs_of_AI_writing), maintained by WikiProject AI Cleanup. The patterns documented there come from observations of thousands of instances of AI-
seed_skills/humanizer/WARP.md
seed_skills/imagegen/LICENSE.txt
seed_skills/imagegen/SKILL.md
- Access to secretsline 3
[Credential-related source omitted] - Access to secretsline 49
[Credential-related source omitted] - Network accessline 51
If the key is missing, give the user these steps: 1. Create an API key in the OpenAI platform UI: https://platform.openai.com/api-keys - Network accessline 52
1. Create an API key in the OpenAI platform UI: https://platform.openai.com/api-keys - Access to secretsline 53
[Credential-related source omitted] - Access to secretsline 62
[Credential-related source omitted]
seed_skills/imagegen/assets/imagegen-small.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" width="16" height="16" fill="currentColor" viewBox="0 0 16 16">
seed_skills/imagegen/references/cli.md
seed_skills/imagegen/scripts/image_gen.py
- Executable scriptline 1
#!/usr/bin/env python3 - Access to secretsline 47
[Credential-related source omitted] - Access to secretsline 48
[Credential-related source omitted] - Access to secretsline 51
[Credential-related source omitted] - Access to secretsline 53
[Credential-related source omitted] - Possible obfuscationline 227
out_path.write_bytes(base64.b64decode(image_b64)) - Possible obfuscationline 290
raw = base64.b64decode(image_b64)
seed_skills/mcp-builder/LICENSE.txt
seed_skills/mcp-builder/SKILL.md
- Network accessline 41
Start with the sitemap to find relevant pages: `https://modelcontextprotocol.io/sitemap.xml` - Network accessline 43
Then fetch specific pages with `.md` suffix for markdown format (e.g., `https://modelcontextprotocol.io/specification/draft.md`). - Network accessline 60
**For TypeScript (recommended):** - **TypeScript SDK**: Use WebFetch to load `https://raw.githubusercontent.com/modelcontextprotocol/typescript-sdk/main/README.md` - Network accessline 61
- **TypeScript SDK**: Use WebFetch to load `https://raw.githubusercontent.com/modelcontextprotocol/typescript-sdk/main/README.md` - Network accessline 64
**For Python:** - **Python SDK**: Use WebFetch to load `https://raw.githubusercontent.com/modelcontextprotocol/python-sdk/main/README.md` - Network accessline 65
- **Python SDK**: Use WebFetch to load `https://raw.githubusercontent.com/modelcontextprotocol/python-sdk/main/README.md` - Network accessline 294
### Core MCP Documentation - **MCP Protocol**: Start with sitemap at `https://modelcontextprotocol.io/sitemap.xml`, then fetch specific pages with `.md` suffix - Network accessline 295
- **MCP Protocol**: Start with sitemap at `https://modelcontextprotocol.io/sitemap.xml`, then fetch specific pages with `.md` suffix - Network accessline 303
### SDK Documentation (Load During Phase 1/2) - **Python SDK**: Fetch from `https://raw.githubusercontent.com/modelcontextprotocol/python-sdk/main/README.md` - Network accessline 304
- **Python SDK**: Fetch from `https://raw.githubusercontent.com/modelcontextprotocol/python-sdk/main/README.md` - Network accessline 305
- **TypeScript SDK**: Fetch from `https://raw.githubusercontent.com/modelcontextprotocol/typescript-sdk/main/README.md`
seed_skills/mcp-builder/reference/evaluation.md
- Access to secretsline 398
[Credential-related source omitted] - Access to secretsline 440
[Credential-related source omitted] - Access to secretsline 444
[Credential-related source omitted] - Network accessline 454
python scripts/evaluation.py \ -t sse \ -u https://example.com/mcp \ - Network accessline 455
[Credential-related source omitted] - Network accessline 456
-u https://example.com/mcp \ - Network accessline 467
python scripts/evaluation.py \ -t http \ -u https://example.com/mcp \ - Network accessline 468
[Credential-related source omitted] - Network accessline 469
-u https://example.com/mcp \ - Access to secretsline 557
[Credential-related source omitted]
seed_skills/mcp-builder/reference/node_mcp_server.md
- Dangerous shell operationline 541
"clean": "rm -rf dist" - Network accessline 600
// Constants const API_BASE_URL = "https://api.example.com/v1"; - Network accessline 601
const API_BASE_URL = "https://api.example.com/v1"; - Access to secretsline 707
[Credential-related source omitted] - Access to secretsline 708
[Credential-related source omitted] - Access to secretsline 719
[Credential-related source omitted] - Access to secretsline 720
[Credential-related source omitted] - Network accessline 737
const port = parseInt(process.env.PORT || '3000'); app.listen(port, () => { console.error(`MCP server running on http://localhost:${port}/mcp`); - Network accessline 738
app.listen(port, () => { console.error(`MCP server running on http://localhost:${port}/mcp`); }); - Network accessline 739
console.error(`MCP server running on http://localhost:${port}/mcp`);
seed_skills/mcp-builder/reference/python_mcp_server.md
- Network accessline 42
**For complete SDK documentation, use WebFetch to load:** `https://raw.githubusercontent.com/modelcontextprotocol/python-sdk/main/README.md` - Network accessline 43
`https://raw.githubusercontent.com/modelcontextprotocol/python-sdk/main/README.md` - Network accessline 233
async def _make_api_request(endpoint: str, method: str = "GET", **kwargs) -> dict: '''Reusable function for all API calls.''' async with httpx.AsyncClient() as client: - Network accessline 234
'''Reusable function for all API calls.''' async with httpx.AsyncClient() as client: response = await client.request( - Network accessline 235
async with httpx.AsyncClient() as client: - Network accessline 251
# Good: Async network request async def fetch_data(resource_id: str) -> dict: async with httpx.AsyncClient() as client: - Network accessline 252
async def fetch_data(resource_id: str) -> dict: async with httpx.AsyncClient() as client: response = await client.get(f"{API_URL}/resource/{resource_id}") - Network accessline 253
async with httpx.AsyncClient() as client: - Network accessline 258
# Bad: Synchronous request def fetch_data(resource_id: str) -> dict: response = requests.get(f"{API_URL}/resource/{resource_id}") # Blocks - Network accessline 259
def fetch_data(resource_id: str) -> dict: response = requests.get(f"{API_URL}/resource/{resource_id}") # Blocks return response.json() - Network accessline 260
response = requests.get(f"{API_URL}/resource/{resource_id}") # Blocks - Network accessline 352
# Constants API_BASE_URL = "https://api.example.com/v1" - Network accessline 353
API_BASE_URL = "https://api.example.com/v1" - Network accessline 382
async def _make_api_request(endpoint: str, method: str = "GET", **kwargs) -> dict: '''Reusable function for all API calls.''' async with httpx.AsyncClient() as client: - Network accessline 383
'''Reusable function for all API calls.''' async with httpx.AsyncClient() as client: response = await client.request( - Network accessline 384
async with httpx.AsyncClient() as client: - Access to secretsline 511
[Credential-related source omitted] - Access to secretsline 517
[Credential-related source omitted]
seed_skills/mcp-builder/reference/skills-api-integration.md
seed_skills/mcp-builder/scripts/connections.py
- Executable scriptline 1
Executable file
seed_skills/mcp-builder/scripts/evaluation.py
seed_skills/media-downloader/SKILL.md
- Access to secretsline 149
[Credential-related source omitted] - Access to secretsline 158
[Credential-related source omitted] - Access to secretsline 162
[Credential-related source omitted] - Access to secretsline 167
[Credential-related source omitted] - Access to secretsline 168
[Credential-related source omitted] - Access to secretsline 169
[Credential-related source omitted] - Access to secretsline 184
[Credential-related source omitted] - Network accessline 199
yt-dlp -f "bestvideo[height<=1080]+bestaudio/best" --write-subs --sub-langs "zh" -o "%(title)s.%(ext)s" "https://youtube.com/watch?v=..." - Network accessline 201
-o "%(title)s.%(ext)s" \ "https://youtube.com/watch?v=..." - Network accessline 202
"https://youtube.com/watch?v=..." - Network accessline 207
yt-dlp -o "%(uploader)s - %(title)s.%(ext)s" \ "https://tiktok.com/@user/video/..." - Network accessline 208
"https://tiktok.com/@user/video/..." - Network accessline 213
[Credential-related source omitted] - Access to secretsline 213
[Credential-related source omitted] - Network accessline 215
"https://bilibili.com/video/BV..." - Network accessline 220
[Credential-related source omitted] - Access to secretsline 220
[Credential-related source omitted] - Network accessline 221
"https://twitter.com/user/status/..."
seed_skills/media-downloader/scripts/download.py
- Executable scriptline 1
#!/usr/bin/env python3 - Access to secretsline 15
[Credential-related source omitted] - Network accessline 18
Examples: python download.py "https://youtube.com/watch?v=..." --resolution 1080p - Network accessline 19
python download.py "https://youtube.com/watch?v=..." --resolution 1080p - Network accessline 20
python download.py "https://youtube.com/watch?v=..." --subtitles "en,zh" --embed-subs - Network accessline 21
python download.py "https://youtube.com/playlist?list=..." --playlist-items "1:10" - Access to secretsline 74
[Credential-related source omitted] - Access to secretsline 135
[Credential-related source omitted]
seed_skills/pdb-database/SKILL.md
- Possible obfuscationline 57
value="MTEYKLVVVGAGGVGKSALTIQLIQNHFVDEYDPTIEDSYRKQVVIDGETCLLDILDTAGQEEYSAMRDQYMRTGEGFLCVFAINNTKSFEDIHHYREQIKRVKDSEDVPMVLVGNKCDLPSRTVDTKQAQDLARSYGIPFIETSAKTRQGVDDAFYTLVREIRKHKEKMSKDGKKKKKKSKTKCVIM", - Network accessline 103
# Get entry-level data entry_data = fetch("4HHB", schema=Schema.ENTRY) - Network accessline 104
entry_data = fetch("4HHB", schema=Schema.ENTRY) - Network accessline 111
# Get protein/nucleic acid information entity_data = fetch("4HHB_1", schema=Schema.POLYMER_ENTITY) - Network accessline 112
entity_data = fetch("4HHB_1", schema=Schema.POLYMER_ENTITY) - Network accessline 135
} """ data = fetch(query_type="graphql", query=query) - Network accessline 137
data = fetch(query_type="graphql", query=query) - Network accessline 144
**Download Methods:** - **PDB format** (legacy text format): `https://files.rcsb.org/download/{PDB_ID}.pdb` - Network accessline 145
- **PDB format** (legacy text format): `https://files.rcsb.org/download/{PDB_ID}.pdb` - Network accessline 146
- **mmCIF format** (modern standard): `https://files.rcsb.org/download/{PDB_ID}.cif` - Network accessline 148
- **Biological assembly**: `https://files.rcsb.org/download/{PDB_ID}.pdb1` (for assembly 1) - Network accessline 156
# Download PDB format pdb_url = f"https://files.rcsb.org/download/{pdb_id}.pdb" - Network accessline 157
pdb_url = f"https://files.rcsb.org/download/{pdb_id}.pdb" - Network accessline 158
response = requests.get(pdb_url) - Network accessline 162
# Download mmCIF format cif_url = f"https://files.rcsb.org/download/{pdb_id}.cif" - Network accessline 163
cif_url = f"https://files.rcsb.org/download/{pdb_id}.cif" - Network accessline 164
response = requests.get(cif_url) - Network accessline 193
# Get experimental details data = fetch("4HHB", schema=Schema.ENTRY) - Network accessline 194
data = fetch("4HHB", schema=Schema.ENTRY) - Network accessline 215
for pdb_id in pdb_ids: try: data = fetch(pdb_id, schema=Schema.ENTRY) - Network accessline 216
try: data = fetch(pdb_id, schema=Schema.ENTRY) results[pdb_id] = { - Network accessline 217
data = fetch(pdb_id, schema=Schema.ENTRY) - Network accessline 301
- **RCSB PDB Website:** https://www.rcsb.org - Network accessline 302
- **PDB-101 Educational Portal:** https://pdb101.rcsb.org - Network accessline 303
- **API Documentation:** https://www.rcsb.org/docs/programmatic-access/web-apis-overview - Network accessline 304
- **Python Package Docs:** https://rcsbapi.readthedocs.io/ - Network accessline 305
- **Data API Documentation:** https://data.rcsb.org/ - Network accessline 306
- **GitHub Repository:** https://github.com/rcsb/py-rcsb-api
seed_skills/pdb-database/references/api_reference.md
- Network accessline 32
Base URL: `https://data.rcsb.org/rest/v1/` - Network accessline 36
GET https://data.rcsb.org/rest/v1/core/entry/{entry_id} - Network accessline 41
GET https://data.rcsb.org/rest/v1/core/polymer_entity/{entry_id}_{entity_id} - Network accessline 46
GET https://data.rcsb.org/rest/v1/core/assembly/{entry_id}/{assembly_id} - Network accessline 51
# Get entry data for hemoglobin curl https://data.rcsb.org/rest/v1/core/entry/4HHB - Network accessline 52
curl https://data.rcsb.org/rest/v1/core/entry/4HHB - Network accessline 54
# Get first polymer entity curl https://data.rcsb.org/rest/v1/core/polymer_entity/4HHB_1 - Network accessline 55
curl https://data.rcsb.org/rest/v1/core/polymer_entity/4HHB_1 - Network accessline 57
# Get biological assembly 1 curl https://data.rcsb.org/rest/v1/core/assembly/4HHB/1 - Network accessline 58
curl https://data.rcsb.org/rest/v1/core/assembly/4HHB/1 - Network accessline 63
Endpoint: `https://data.rcsb.org/graphql` - Network accessline 113
response = requests.post( - Network accessline 114
"https://data.rcsb.org/graphql", - Possible obfuscationline 239
value="MTEYKLVVVGAGGVGKSALTIQLIQNHFVDEYDPTIEDSYRKQVVIDGETCLLDILDTAGQEEYSAMRDQYMRTGEGFLCVFAINNTKSFEDIHHYREQIKRVKDSEDVPMVLVGNKCDLPSRTVDTKQAQDLARSYGIPFIETSAKTRQGVDDAFYTLVREIRKHKEKMSKDGKKKKKKSKTKCVIM", - Network accessline 363
https://files.rcsb.org/download/{PDB_ID}.pdb - Network accessline 368
https://files.rcsb.org/download/{PDB_ID}.cif - Network accessline 373
https://files.rcsb.org/download/{PDB_ID}-sf.cif - Network accessline 378
https://files.rcsb.org/download/{PDB_ID}.pdb1 # Assembly 1 - Network accessline 379
https://files.rcsb.org/download/{PDB_ID}.pdb2 # Assembly 2 - Network accessline 384
https://www.rcsb.org/fasta/entry/{PDB_ID} - Network accessline 399
output_dir: Directory to save file """ base_url = "https://files.rcsb.org/download" - Network accessline 400
""" base_url = "https://files.rcsb.org/download" url = f"{base_url}/{pdb_id}.{format}" - Network accessline 401
base_url = "https://files.rcsb.org/download" - Network accessline 404
response = requests.get(url) - Network accessline 446
for attempt in range(max_retries): response = requests.get(url) - Network accessline 447
response = requests.get(url) - Network accessline 488
for i, pdb_id in enumerate(pdb_ids): try: data = fetch(pdb_id, schema=Schema.ENTRY) - Network accessline 489
try: data = fetch(pdb_id, schema=Schema.ENTRY) results[pdb_id] = data - Network accessline 490
data = fetch(pdb_id, schema=Schema.ENTRY) - Network accessline 600
# Test with curl import subprocess - Network accessline 601
import subprocess result = subprocess.run( ["curl", "https://data.rcsb.org/rest/v1/core/entry/4HHB"], - Network accessline 602
result = subprocess.run( ["curl", "https://data.rcsb.org/rest/v1/core/entry/4HHB"], capture_output=True, - Network accessline 603
["curl", "https://data.rcsb.org/rest/v1/core/entry/4HHB"], - Network accessline 612
- **API Documentation:** https://www.rcsb.org/docs/programmatic-access/web-apis-overview - Network accessline 613
- **Data API Redoc:** https://data.rcsb.org/redoc/index.html - Network accessline 614
- **GraphQL Schema:** https://data.rcsb.org/graphql - Network accessline 615
- **Python Package Docs:** https://rcsbapi.readthedocs.io/ - Network accessline 616
- **GitHub Issues:** https://github.com/rcsb/py-rcsb-api/issues - Network accessline 617
- **Community Forum:** https://www.rcsb.org/help
seed_skills/pdf/LICENSE.txt
seed_skills/pdf/SKILL.md
- Dangerous shell operationline 44
sudo apt-get install -y poppler-utils
seed_skills/planning-with-files/SKILL.md
- Broad permissionsline 1
Bash
seed_skills/planning-with-files/reference.md
seed_skills/planning-with-files/templates/findings.md
- Network accessline 67
WHEN: Add as you discover useful resources. EXAMPLE: - Python argparse docs: https://docs.python.org/3/library/argparse.html - Network accessline 68
EXAMPLE: - Python argparse docs: https://docs.python.org/3/library/argparse.html - Project structure: src/main.py, src/utils.py - Network accessline 69
- Python argparse docs: https://docs.python.org/3/library/argparse.html
seed_skills/pubmed-database/SKILL.md
- Network accessline 127
# Step 1: Search for articles base_url = "https://eutils.ncbi.nlm.nih.gov/entrez/eutils/" - Network accessline 128
base_url = "https://eutils.ncbi.nlm.nih.gov/entrez/eutils/" - Network accessline 135
[Credential-related source omitted] - Access to secretsline 135
[Credential-related source omitted] - Network accessline 136
} response = requests.get(search_url, params=params) pmids = response.json()["esearchresult"]["idlist"] - Network accessline 137
response = requests.get(search_url, params=params) - Network accessline 147
[Credential-related source omitted] - Access to secretsline 147
[Credential-related source omitted] - Network accessline 148
} response = requests.get(fetch_url, params=params) abstracts = response.text - Network accessline 149
response = requests.get(fetch_url, params=params) - Network accessline 453
- **PubMed Help**: https://pubmed.ncbi.nlm.nih.gov/help/ - Network accessline 454
- **E-utilities Documentation**: https://www.ncbi.nlm.nih.gov/books/NBK25501/
seed_skills/pubmed-database/references/api_reference.md
- Network accessline 8
https://eutils.ncbi.nlm.nih.gov/entrez/eutils/ - Access to secretsline 15
[Credential-related source omitted] - Access to secretsline 17
[Credential-related source omitted] - Access to secretsline 51
[Credential-related source omitted] - Access to secretsline 80
[Credential-related source omitted] - Access to secretsline 105
[Credential-related source omitted] - Access to secretsline 129
[Credential-related source omitted] - Access to secretsline 154
[Credential-related source omitted] - Access to secretsline 175
[Credential-related source omitted] - Access to secretsline 195
[Credential-related source omitted] - Access to secretsline 210
[Credential-related source omitted] - Access to secretsline 242
[Credential-related source omitted] - Access to secretsline 247
[Credential-related source omitted] - Access to secretsline 248
[Credential-related source omitted] - Access to secretsline 257
[Credential-related source omitted] - Access to secretsline 260
[Credential-related source omitted] - Network accessline 295
- **API Documentation**: https://www.ncbi.nlm.nih.gov/books/NBK25501/
seed_skills/rdkit/scripts/molecular_properties.py
- Executable scriptline 1
#!/usr/bin/env python3
seed_skills/rdkit/scripts/similarity_search.py
- Executable scriptline 1
#!/usr/bin/env python3
seed_skills/rdkit/scripts/substructure_filter.py
- Executable scriptline 1
#!/usr/bin/env python3
seed_skills/remotion-best-practices/rules/assets.md
seed_skills/remotion-best-practices/rules/assets/charts-bar-chart.tsx
- Executable scriptline 1
Executable file
seed_skills/remotion-best-practices/rules/assets/text-animations-typewriter.tsx
- Executable scriptline 1
Executable file
seed_skills/remotion-best-practices/rules/assets/text-animations-word-highlight.tsx
- Executable scriptline 1
Executable file
seed_skills/remotion-best-practices/rules/audio-visualization.md
- Network accessline 18
Use `useWindowedAudioData()` (https://www.remotion.dev/docs/use-windowed-audio-data) to load audio data: - Network accessline 37
Use `visualizeAudio()` (https://www.remotion.dev/docs/visualize-audio) to get frequency data for bar charts: - Network accessline 91
Use `visualizeAudioWaveform()` (https://www.remotion.dev/docs/media-utils/visualize-audio-waveform) with `createSmoothSvgPath()` (https://www.remotion.dev/docs/media-utils/create-smooth-svg-path) for oscilloscope-style displays: - Network accessline 163
Use `getWaveformPortion()` (https://www.remotion.dev/docs/get-waveform-portion) when you need simplified volume data instead of frequency spectrum:
seed_skills/remotion-best-practices/rules/audio.md
- Network accessline 35
<Audio src="https://remotion.media/audio.mp3" />
seed_skills/remotion-best-practices/rules/calculate-metadata.md
- Network accessline 18
width={1920} height={1080} defaultProps={{ videoSrc: "https://remotion.media/video.mp4" }} - Network accessline 19
height={1080} defaultProps={{ videoSrc: "https://remotion.media/video.mp4" }} calculateMetadata={calculateMetadata} - Network accessline 20
defaultProps={{ videoSrc: "https://remotion.media/video.mp4" }} - Network accessline 108
abortSignal, }) => { const response = await fetch(props.dataUrl, { signal: abortSignal }); - Network accessline 109
}) => { const response = await fetch(props.dataUrl, { signal: abortSignal }); const data = await response.json(); - Network accessline 110
const response = await fetch(props.dataUrl, { signal: abortSignal });
seed_skills/remotion-best-practices/rules/can-decode.md
- Network accessline 50
const src = "https://remotion.media/video.mp4";
seed_skills/remotion-best-practices/rules/charts.md
seed_skills/remotion-best-practices/rules/compositions.md
- Network accessline 111
MyCompositionProps > = async ({ props, abortSignal }) => { const data = await fetch(`https://api.example.com/video/${props.videoId}`, { - Network accessline 112
> = async ({ props, abortSignal }) => { const data = await fetch(`https://api.example.com/video/${props.videoId}`, { signal: abortSignal, - Network accessline 113
const data = await fetch(`https://api.example.com/video/${props.videoId}`, {
seed_skills/remotion-best-practices/rules/display-captions.md
- Network accessline 10
This guide explains how to display captions in Remotion, assuming you already have captions in the [`Caption`](https://www.remotion.dev/docs/captions/caption) format. - Network accessline 16
First, the [`@remotion/captions`](https://www.remotion.dev/docs/captions) package needs to be installed. - Network accessline 25
First, fetch your captions JSON file. Use [`useDelayRender()`](https://www.remotion.dev/docs/use-delay-render) to hold the render until the captions are loaded: - Network accessline 38
try { // Assuming captions.json is in the public/ folder. const response = await fetch(staticFile("captions123.json")); - Network accessline 39
// Assuming captions.json is in the public/ folder. const response = await fetch(staticFile("captions123.json")); const data = await response.json(); - Network accessline 40
const response = await fetch(staticFile("captions123.json"));
seed_skills/remotion-best-practices/rules/extract-frames.md
- Network accessline 108
await extractFrames({ src: "https://remotion.media/video.mp4", - Network accessline 109
src: "https://remotion.media/video.mp4", - Network accessline 131
await extractFrames({ src: "https://remotion.media/video.mp4", - Network accessline 132
src: "https://remotion.media/video.mp4", - Network accessline 170
try { await extractFrames({ src: "https://remotion.media/video.mp4", - Network accessline 171
await extractFrames({ src: "https://remotion.media/video.mp4", timestampsInSeconds: [0, 1, 2, 3, 4], - Network accessline 172
src: "https://remotion.media/video.mp4", - Network accessline 208
await Promise.race([ extractFrames({ src: "https://remotion.media/video.mp4", - Network accessline 209
extractFrames({ src: "https://remotion.media/video.mp4", timestampsInSeconds: [0, 1, 2, 3, 4], - Network accessline 210
src: "https://remotion.media/video.mp4",
seed_skills/remotion-best-practices/rules/get-audio-duration.md
- Network accessline 33
const duration = await getAudioDuration("https://remotion.media/audio.mp3");
seed_skills/remotion-best-practices/rules/get-video-dimensions.md
- Network accessline 40
const dimensions = await getVideoDimensions("https://remotion.media/video.mp4");
seed_skills/remotion-best-practices/rules/get-video-duration.md
- Network accessline 33
const duration = await getVideoDuration("https://remotion.media/video.mp4");
seed_skills/remotion-best-practices/rules/gifs.md
seed_skills/remotion-best-practices/rules/images.md
- Network accessline 57
<Img src="https://example.com/image.png" />
seed_skills/remotion-best-practices/rules/import-srt-captions.md
- Network accessline 41
const fetchCaptions = useCallback(async () => { try { const response = await fetch(staticFile("subtitles.srt")); - Network accessline 42
try { const response = await fetch(staticFile("subtitles.srt")); const text = await response.text(); - Network accessline 43
const response = await fetch(staticFile("subtitles.srt")); - Network accessline 65
Remote URLs are also supported - you can `fetch()` a remote file via URL instead of using `staticFile()`.
seed_skills/remotion-best-practices/rules/lottie.md
seed_skills/remotion-best-practices/rules/maps.md
- Network accessline 8
Maps can be added to a Remotion video with Mapbox. The [Mapbox documentation](https://docs.mapbox.com/mapbox-gl-js/api/) has the API reference. - Network accessline 9
The [Mapbox documentation](https://docs.mapbox.com/mapbox-gl-js/api/) has the API reference. - Network accessline 41
The user needs to create a free Mapbox account and create an access token by visiting https://console.mapbox.com/account/access-tokens/. - Access to secretsline 45
[Credential-related source omitted] - Access to secretsline 68
[Credential-related source omitted] - Possible obfuscationline 85
style: "<U+2060>mapbox://styles/mapbox/standard",
seed_skills/remotion-best-practices/rules/tailwind.md
- Network accessline 11
Tailwind must be installed and enabled first in a Remotion project - fetch https://www.remotion.dev/docs/tailwind using WebFetch for instructions.
seed_skills/remotion-best-practices/rules/transcribe-captions.md
- Network accessline 10
To transcribe audio to generate captions in Remotion, you can use the [`transcribe()`](https://www.remotion.dev/docs/install-whisper-cpp/transcribe) function from the [`@remotion/install-whisper-cpp`](https://www.remotion.dev/docs/install-w
seed_skills/remotion-best-practices/rules/videos.md
- Network accessline 36
<Video src="https://remotion.media/video.mp4" />
seed_skills/remotion-best-practices/rules/voiceover.md
- Access to secretsline 17
[Credential-related source omitted] - Access to secretsline 20
[Credential-related source omitted] - Network accessline 35
const response = await fetch( - Network accessline 36
`https://api.elevenlabs.io/v1/text-to-speech/${voiceId}`, - Access to secretsline 40
[Credential-related source omitted]
seed_skills/skill-creator/LICENSE.txt
seed_skills/skill-creator/SKILL.md
seed_skills/skill-creator/scripts/init_skill.py
- Executable scriptline 1
#!/usr/bin/env python3
seed_skills/skill-creator/scripts/package_skill.py
- Executable scriptline 1
#!/usr/bin/env python3
seed_skills/skill-creator/scripts/quick_validate.py
- Executable scriptline 1
#!/usr/bin/env python3
seed_skills/skill-evolver/scripts/analyze_traces.py
- Executable scriptline 1
#!/usr/bin/env python3
seed_skills/skill-evolver/scripts/extract_issue_context.py
- Executable scriptline 1
#!/usr/bin/env python3
seed_skills/skill-finder/SKILL.md
- Network accessline 8
Discover and install agent skills from the [skills.sh](https://skills.sh) open ecosystem into Skill Compose.
seed_skills/skill-finder/scripts/add_skill.py
- Executable scriptline 1
#!/usr/bin/env python3 - Network accessline 27
[Credential-related source omitted] - Access to secretsline 27
[Credential-related source omitted] - Network accessline 28
GITHUB_API = "https://api.github.com" - Access to secretsline 34
[Credential-related source omitted] - Network accessline 35
[Credential-related source omitted] - Network accessline 36
headers["Authorization"] = f"token {token}" req = urllib.request.Request(url, headers=headers) try: - Network accessline 37
req = urllib.request.Request(url, headers=headers) - Network accessline 38
try: with urllib.request.urlopen(req, timeout=30) as resp: return json.loads(resp.read().decode()) - Network accessline 39
with urllib.request.urlopen(req, timeout=30) as resp: - Access to secretsline 57
[Credential-related source omitted] - Network accessline 58
[Credential-related source omitted] - Network accessline 59
headers["Authorization"] = f"token {token}" req = urllib.request.Request(url, headers=headers) try: - Network accessline 60
req = urllib.request.Request(url, headers=headers) - Network accessline 61
try: with urllib.request.urlopen(req, timeout=30) as resp: return resp.read() - Network accessline 62
with urllib.request.urlopen(req, timeout=30) as resp: - Network accessline 115
for path in skill_md_paths: raw_url = f"https://raw.githubusercontent.com/{owner}/{repo}/{branch}/{path}" - Network accessline 116
raw_url = f"https://raw.githubusercontent.com/{owner}/{repo}/{branch}/{path}" - Network accessline 168
raw_url = f"https://raw.githubusercontent.com/{owner}/{repo}/{branch}/{path}" - Network accessline 193
url = f"{api_url}/api/v1/registry/import-local" payload = json.dumps({"skill_names": [skill_name]}).encode() req = urllib.request.Request( - Network accessline 194
payload = json.dumps({"skill_names": [skill_name]}).encode() req = urllib.request.Request( url, - Network accessline 195
req = urllib.request.Request( - Network accessline 200
) try: with urllib.request.urlopen(req, timeout=30) as resp: - Network accessline 201
try: with urllib.request.urlopen(req, timeout=30) as resp: result = json.loads(resp.read().decode()) - Network accessline 202
with urllib.request.urlopen(req, timeout=30) as resp: - Access to secretsline 234
[Credential-related source omitted] - Network accessline 279
if success: print(f"\nDone! Skill '{skill_name}' is now available in Skill Compose.") print(f" Source: https://github.com/{owner}/{repo}") - Network accessline 280
print(f"\nDone! Skill '{skill_name}' is now available in Skill Compose.") print(f" Source: https://github.com/{owner}/{repo}") print(f" Browse: https://skills.sh/{owner}/{repo}/{skill_name}") - Network accessline 281
print(f" Source: https://github.com/{owner}/{repo}") - Network accessline 282
print(f" Browse: https://skills.sh/{owner}/{repo}/{skill_name}") - Network accessline 283
else: print(f"\nFiles saved but registration failed. You can manually register:") print(f' curl -X POST "{args.api_url}/api/v1/registry/import-local" \\') - Network accessline 284
print(f"\nFiles saved but registration failed. You can manually register:") print(f' curl -X POST "{args.api_url}/api/v1/registry/import-local" \\') print(f' -H "Content-Type: application/json" \\') - Network accessline 285
print(f' curl -X POST "{args.api_url}/api/v1/registry/import-local" \\')
seed_skills/skill-finder/scripts/find_skills.py
- Executable scriptline 1
#!/usr/bin/env python3 - Network accessline 19
SEARCH_API = "https://skills.sh/api/search" - Network accessline 27
req = urllib.request.Request(url, headers={"User-Agent": "skill-finder/1.0"}) - Network accessline 28
try: with urllib.request.urlopen(req, timeout=15) as resp: data = json.loads(resp.read().decode()) - Network accessline 29
with urllib.request.urlopen(req, timeout=15) as resp: - Network accessline 40
"installs": s.get("installs", 0), "slug": s.get("id", ""), "url": f"https://skills.sh/{s.get('id', '')}", - Network accessline 41
"slug": s.get("id", ""), "url": f"https://skills.sh/{s.get('id', '')}", } - Network accessline 42
"url": f"https://skills.sh/{s.get('id', '')}", - Network accessline 85
print(f"\nInstall with: python add_skill.py <source@name>") print(f"Browse: https://skills.sh/") - Network accessline 86
print(f"Browse: https://skills.sh/")
seed_skills/skill-updater/LICENSE.txt
seed_skills/skill-updater/scripts/analyze_skill.py
- Executable scriptline 1
#!/usr/bin/env python3
seed_skills/slack-gif-creator/LICENSE.txt
seed_skills/slack-gif-creator/core/color_palettes.py
- Executable scriptline 1
#!/usr/bin/env python3
seed_skills/slack-gif-creator/core/easing.py
- Executable scriptline 1
#!/usr/bin/env python3
seed_skills/slack-gif-creator/core/frame_composer.py
- Executable scriptline 1
#!/usr/bin/env python3
seed_skills/slack-gif-creator/core/gif_builder.py
- Executable scriptline 1
#!/usr/bin/env python3
seed_skills/slack-gif-creator/core/typography.py
- Executable scriptline 1
#!/usr/bin/env python3
seed_skills/slack-gif-creator/core/validators.py
- Executable scriptline 1
#!/usr/bin/env python3
seed_skills/slack-gif-creator/core/visual_effects.py
- Executable scriptline 1
#!/usr/bin/env python3
seed_skills/slack-gif-creator/templates/bounce.py
- Executable scriptline 1
#!/usr/bin/env python3
seed_skills/slack-gif-creator/templates/explode.py
- Executable scriptline 1
#!/usr/bin/env python3
seed_skills/slack-gif-creator/templates/fade.py
- Executable scriptline 1
#!/usr/bin/env python3
seed_skills/slack-gif-creator/templates/flip.py
- Executable scriptline 1
#!/usr/bin/env python3
seed_skills/slack-gif-creator/templates/kaleidoscope.py
- Executable scriptline 1
#!/usr/bin/env python3
seed_skills/slack-gif-creator/templates/morph.py
- Executable scriptline 1
#!/usr/bin/env python3
seed_skills/slack-gif-creator/templates/move.py
- Executable scriptline 1
#!/usr/bin/env python3
seed_skills/slack-gif-creator/templates/pulse.py
- Executable scriptline 1
#!/usr/bin/env python3
seed_skills/slack-gif-creator/templates/shake.py
- Executable scriptline 1
#!/usr/bin/env python3
seed_skills/slack-gif-creator/templates/slide.py
- Executable scriptline 1
#!/usr/bin/env python3
seed_skills/slack-gif-creator/templates/spin.py
- Executable scriptline 1
#!/usr/bin/env python3
seed_skills/slack-gif-creator/templates/wiggle.py
- Executable scriptline 1
#!/usr/bin/env python3
seed_skills/slack-gif-creator/templates/zoom.py
- Executable scriptline 1
#!/usr/bin/env python3
seed_skills/sora/LICENSE.txt
seed_skills/sora/SKILL.md
- Access to secretsline 3
[Credential-related source omitted] - Access to secretsline 36
[Credential-related source omitted] - Network accessline 38
If the key is missing, give the user these steps: 1. Create an API key in the OpenAI platform UI: https://platform.openai.com/api-keys - Network accessline 39
1. Create an API key in the OpenAI platform UI: https://platform.openai.com/api-keys - Access to secretsline 40
[Credential-related source omitted] - Access to secretsline 50
[Credential-related source omitted]
seed_skills/sora/assets/sora-small.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" width="14" height="14" fill="currentColor" viewBox="0 0 14 14">
seed_skills/sora/references/cli.md
seed_skills/sora/scripts/sora.py
seed_skills/speech/LICENSE.txt
seed_skills/speech/SKILL.md
- Access to secretsline 3
[Credential-related source omitted] - Access to secretsline 47
[Credential-related source omitted] - Network accessline 49
If the key is missing, give the user these steps: 1. Create an API key in the OpenAI platform UI: https://platform.openai.com/api-keys - Network accessline 50
1. Create an API key in the OpenAI platform UI: https://platform.openai.com/api-keys - Access to secretsline 51
[Credential-related source omitted] - Access to secretsline 64
[Credential-related source omitted]
seed_skills/speech/assets/speech-small.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" width="14" height="14" fill="currentColor" viewBox="0 0 14 14">
seed_skills/speech/references/cli.md
seed_skills/speech/scripts/text_to_speech.py
seed_skills/spreadsheet/LICENSE.txt
seed_skills/spreadsheet/SKILL.md
- Dangerous shell operationline 65
sudo apt-get install -y libreoffice poppler-utils
seed_skills/spreadsheet/assets/spreadsheet-small.svg
- Network accessline 1
<svg xmlns="http://www.w3.org/2000/svg" width="16" height="16" fill="currentColor" viewBox="0 0 16 16">
seed_skills/spreadsheet/references/examples/openpyxl/create_basic_spreadsheet.py
- Executable scriptline 1
Executable file
seed_skills/spreadsheet/references/examples/openpyxl/create_spreadsheet_with_styling.py
- Executable scriptline 1
Executable file
seed_skills/spreadsheet/references/examples/openpyxl/read_existing_spreadsheet.py
- Executable scriptline 1
Executable file
seed_skills/spreadsheet/references/examples/openpyxl/styling_spreadsheet.py
- Executable scriptline 1
Executable file
seed_skills/trace-qa/SKILL.md
- Network accessline 80
Set `API_BASE_URL` to override the default API endpoint (`http://127.0.0.1:62610`).
seed_skills/trace-qa/scripts/fetch_trace.py
- Executable scriptline 1
#!/usr/bin/env python3 - Network accessline 37
[Credential-related source omitted] - Access to secretsline 37
[Credential-related source omitted] - Network accessline 42
url = f"{API_BASE_URL}/api/v1/traces/{trace_id}" try: req = urllib.request.Request(url) - Network accessline 43
try: req = urllib.request.Request(url) with urllib.request.urlopen(req, timeout=30) as resp: - Network accessline 44
req = urllib.request.Request(url) - Network accessline 45
with urllib.request.urlopen(req, timeout=30) as resp:
How the signals fit together
Facts from a static read of the files at the pinned commit. They describe what the code does, not why.
Some files could not be read; the facts below still hold.
No combined signals at this commit.
Works with
| Agent | Status | Evidence | Install to |
|---|---|---|---|
| Claude Code | Compatible | Standard SKILL.md seed_skills/ai-writing-detection/SKILL.md | .claude/skills/<skill-name>/ |
| Codex | Compatible | Standard SKILL.md seed_skills/ai-writing-detection/SKILL.md | .agents/skills/<skill-name>/ |
| Cursor | Compatible | Standard SKILL.md seed_skills/ai-writing-detection/SKILL.md | .cursor/skills/<skill-name>/ |
| Gemini CLI | Compatible | Standard SKILL.md seed_skills/ai-writing-detection/SKILL.md | .gemini/skills/<skill-name>/ |
| GitHub Copilot | Compatible | Standard SKILL.md seed_skills/ai-writing-detection/SKILL.md | .github/skills/<skill-name>/ |
| OpenCode | Compatible | Standard SKILL.md seed_skills/ai-writing-detection/SKILL.md | .opencode/skills/<skill-name>/ |
- Native The repository ships a manifest, folder or frontmatter field for this agent.
- Compatible A standard SKILL.md that this agent can read.
- Unknown No evidence either way.
Derived automatically from paths, manifests and frontmatter. Not tested on each agent.
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