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YYH211/Claude-meta-skill
A curated collection of reusable skills for Claude Code. Enhance Claude's capabilities with ready-to-use skill modules including comprehensive guides, templates, and best practices for creating your own skills.
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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Heat
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Individual skills in this repository
- create-skill-file
create-skill-file - create-skill-file
create-skill-file-EN - daily-ai-news
daily-ai-news - deep-reading-analyst
deep-reading-analyst - dry-refactoring
dry-refactoring - fastgpt-workflow-generator
fastgpt-workflow-generator - frontend-design
frontend-design - local-diff-review
local-diff-review - mcp-builder
mcp-builder - planning-with-files
planning-with-files - prompt-optimize
prompt-optimize - software-copyright-writer
software-copyright-writer
How it works
create-skill-file
When your agent uses it
Guides Claude in creating well-structured SKILL.md files following best practices. Provides clear guidelines for naming, structure, and content organization to make skills easy to discover and execute.
What it loads into context
Frontmatter
44 tokensAlways available to the agent
SKILL.md
2,941 tokensWhen the skill is activated
Reference documents
14,074 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- 目录
- 快速开始
- 核心原则
- 文件结构规范
- 命名和描述规范
- 内容编写指南
- 质量检查清单
- 常见问题
- 快速参考
- 相关资源
Files
SKILL.mdcore10,257 bytesSKILL.mdcore10,257 bytesSKILL.mdcore10,257 bytesSKILL.mdcore10,257 bytesexamples/bad-example.mddoc21,462 bytesexamples/good-example.mddoc23,423 bytestemplates/basic-skill-template.mddoc1,837 bytestemplates/workflow-skill-template.mddoc8,755 bytes
Read SKILL.md
# Claude Agent Skill 编写规范
> 如何创建高质量的 SKILL.md 文件
## 目录
- [快速开始](#快速开始)
- [核心原则](#核心原则)
- [文件结构规范](#文件结构规范)
- [命名和描述规范](#命名和描述规范)
- [内容编写指南](#内容编写指南)
- [质量检查清单](#质量检查清单)
---View the complete source on GitHubcreate-skill-file
When your agent uses it
Guides Claude in creating well-structured SKILL.md files following best practices. Provides clear guidelines for naming, structure, and content organization to make skills easy to discover and execute.
What it loads into context
Frontmatter
44 tokensAlways available to the agent
SKILL.md
2,634 tokensWhen the skill is activated
Reference documents
13,727 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Table of Contents
- Quick Start
- Core Principles
- File Structure Standards
- Naming and Description Standards
- Content Writing Guide
- Quality Checklist
- FAQ
- Quick Reference
- Related Resources
Files
SKILL.mdcore11,065 bytesSKILL.mdcore11,065 bytesSKILL.mdcore11,065 bytesSKILL.mdcore11,065 bytesexamples/bad-example.mddoc22,364 bytesexamples/good-example.mddoc23,868 bytestemplates/basic-skill-template.mddoc1,837 bytestemplates/workflow-skill-template.mddoc8,755 bytes
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# Claude Agent Skill Writing Guide
> How to create high-quality SKILL.md files
## Table of Contents
- [Quick Start](#quick-start)
- [Core Principles](#core-principles)
- [File Structure Standards](#file-structure-standards)
- [Naming and Description Standards](#naming-and-description-standards)
- [Content Writing Guide](#content-writing-guide)
- [Quality Checklist](#quality-checklist)
---View the complete source on GitHubdaily-ai-news
When your agent uses it
Aggregates and summarizes the latest AI news from multiple sources including AI news websites and web search. Provides concise news briefs with direct links to original articles. Activates when user asks for 'today's AI news', 'AI updates', 'latest AI developments', or mentions wanting a 'daily AI briefing'.
What it loads into context
Frontmatter
70 tokensAlways available to the agent
SKILL.md
2,135 tokensWhen the skill is activated
Reference documents
7,226 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use This Skill
- Workflow Overview
- Phase 1: Information Gathering
- Phase 2: Content Filtering
- Phase 3: Categorization
- Phase 4: Output Formatting
- Customization Options
- Follow-up Interactions
- Quality Standards
- Examples
- Additional Resources
Files
SKILL.mdcore9,034 bytesSKILL.mdcore9,034 bytesSKILL.mdcore9,034 bytesreferences/news_sources.mddoc7,678 bytesreferences/output_templates.mddoc12,560 bytesreferences/search_queries.mddoc6,957 bytes
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# Daily AI News Briefing
> Aggregates the latest AI news from multiple sources and delivers concise summaries with direct links
## When to Use This Skill
Activate this skill when the user:
- Asks for today's AI news or latest AI developments
- Requests a daily AI briefing or updates
- Mentions wanting to know what's happening in AI
- Asks for AI industry news, trends, or breakthroughs
- Wants a summary of recent AI announcements
- Says: "给我今天的AI资讯" (Give me today's AI news)
- Says: "AI有什么新动态" (What's new in AI)View the complete source on GitHubdeep-reading-analyst
When your agent uses it
Comprehensive framework for deep analysis of articles, papers, and long-form content using 10+ thinking models (SCQA, 5W2H, critical thinking, inversion, mental models, first principles, systems thinking, six thinking hats). Use when users want to: (1) deeply understand complex articles/content, (2) analyze arguments and identify logical flaws, (3) extract actionable insights from reading materials, (4) create study notes or learning summaries, (5) compare multiple sources, (6) transform knowledge into practical applications, or (7) apply specific thinking frameworks. Triggered by phrases like 'analyze this article,' 'help me understand,' 'deep dive into,' 'extract insights from,' 'use [framework name],' or when users provide URLs/long-form content for analysis.
What it loads into context
Frontmatter
174 tokensAlways available to the agent
SKILL.md
3,598 tokensWhen the skill is activated
Reference documents
18,227 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Framework Arsenal
- Workflow Decision Tree
- Step 1: Initialize Analysis
- Step 2: Structural Understanding
- Step 3: Apply Thinking Models
- Step 4: Synthesis & Output
- Step 5: Knowledge Activation
- Quality Standards
- Interaction Patterns
- Reference Materials
- Advanced Usage
Files
SKILL.mdcore15,255 bytesSKILL.mdcore15,255 bytesSKILL.mdcore15,255 bytesreferences/5w2h_analysis.mddoc9,040 bytesreferences/comparison_matrix.mddoc8,886 bytesreferences/critical_thinking.mddoc3,297 bytesreferences/first_principles.mddoc4,460 bytesreferences/inversion_thinking.mddoc8,710 bytesreferences/mental_models.mddoc8,670 bytesreferences/output_templates.mddoc7,644 bytesreferences/scqa_framework.mddoc11,733 bytesreferences/six_hats.mddoc7,884 bytesreferences/systems_thinking.mddoc5,686 bytes
Read SKILL.md
# Deep Reading Analyst
Transforms surface-level reading into deep learning through systematic analysis using 10+ proven thinking frameworks. Guides users from understanding to application through structured workflows.
## Framework Arsenal
### Quick Analysis (15min)
- 📋 **SCQA** - Structure thinking (Situation-Complication-Question-Answer)
- 🔍 **5W2H** - Completeness check (What, Why, Who, When, Where, How, How much)
### Standard Analysis (30min)
- 🎯 **Critical Thinking** - Argument evaluation
- 🔄 **Inversion Thinking** - Risk identification
View the complete source on GitHubdry-refactoring
When your agent uses it
Guides systematic code refactoring following the DRY (Don't Repeat Yourself) principle. Use when user asks to eliminate code duplication, refactor repetitive code, apply DRY principle, or mentions code smells like copy-paste, magic numbers, or repeated logic. Implements a 4-step workflow from identifying repetition to verified refactoring.
What it loads into context
Frontmatter
73 tokensAlways available to the agent
SKILL.md
7,186 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
- 核心思想
- 四步标准化流程
- 完整示例:从头到尾
- 常见陷阱与解决方案
- 最佳实践
- 检查清单
- 总结
Files
SKILL.mdcore25,729 bytesSKILL.mdcore25,729 bytesSKILL.mdcore25,729 bytesSKILL.mdcore25,729 bytesSKILL.mdcore25,729 bytesSKILL.mdcore25,729 bytesSKILL.mdcore25,729 bytesSKILL.mdcore25,729 bytesSKILL.mdcore25,729 bytesSKILL.mdcore25,729 bytesSKILL.mdcore25,729 bytes
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# DRY 标准化流程:从识别到重构
这个技能指导你系统性地应用 DRY (Don't Repeat Yourself) 原则,通过四步标准化流程消除代码重复,提升代码质量和可维护性。
## When to Use This Skill
使用此技能当用户请求:
- 消除代码重复或冗余
- 重构有明显复制粘贴痕迹的代码
- 应用 DRY 原则优化代码库
- 识别并修复"代码坏味道"(如魔术数字、重复逻辑)
- 提取公共逻辑为可复用单元
- 改善代码的可维护性
View the complete source on GitHubfastgpt-workflow-generator
When your agent uses it
Generates production-ready FastGPT workflow JSON from natural language requirements. Uses AI-powered semantic template matching from built-in workflows (document translation, sales training, resume screening, financial news). Performs three-layer validation (format, connections, logic completeness). Supports incremental modifications to add/remove/modify nodes. Activates when user asks to "create FastGPT workflow", "generate workflow JSON", "design FastGPT application", or mentions workflow automation, multi-agent systems, or FastGPT templates.
What it loads into context
Frontmatter
105 tokensAlways available to the agent
SKILL.md
5,457 tokensWhen the skill is activated
Reference documents
12,821 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use This Skill
- Core Workflow
- Examples
- Technical Implementation
- Best Practices
- Troubleshooting
- Quick Reference
Scripts executed separately
scripts/validate_workflow.js
Files
LESSONS_LEARNED.mddoc8,398 bytesSKILL.mdcore22,311 bytesSKILL.mdcore22,311 bytesSKILL.mdcore22,311 bytesSKILL.mdcore22,311 bytesSKILL.mdcore22,311 bytesSKILL.mdcore22,311 bytesSKILL.mdcore22,311 bytesSKILL.mdcore22,311 bytesSKILL.mdcore22,311 bytesSKILL.mdcore22,311 bytesSKILL.mdcore22,311 bytesSKILL.mdcore22,311 bytesSKILL.mdcore22,311 bytesreferences/json_structure_spec.mddoc11,532 bytesreferences/node_types_reference.mddoc7,889 bytesreferences/template_matching.mddoc6,929 bytesreferences/validation_rules.mddoc6,307 bytesscripts/validate_workflow.jsruns13,277 bytestemplates/AI金融日报.jsonasset96,060 bytestemplates/README.mddoc7,493 bytestemplates/文档翻译助手.jsonasset39,328 bytestemplates/简历筛选助手_飞书.jsonasset108,217 bytestemplates/销售陪练大师.jsonasset43,960 bytes
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# FastGPT Workflow Generator
> Automatically generate production-ready FastGPT workflow JSON from natural language requirements
## When to Use This Skill
Use this skill when you need to:
- **Create new workflows from scratch**: User asks to "create a FastGPT workflow for X purpose"
- **Generate based on templates**: User wants to build workflows similar to existing patterns (document processing, AI chat, data analysis, multi-agent systems)
- **Modify existing workflows**: User needs to add/remove/update nodes in an existing workflow JSON
- **Validate workflow JSON**: User has a workflow JSON that needs verification or fixing
- **Design multi-agent systems**: User mentions parallel processing, agent coordination, or workflow orchestration
- **Automate workflow creation**: User provides requirements document and needs executable JSONView the complete source on GitHubfrontend-design
When your agent uses it
Creates unique, production-grade frontend interfaces with exceptional design quality. Use when user asks to build web components, pages, materials, posters, or applications (e.g., websites, landing pages, dashboards, React components, HTML/CSS layouts, or styling/beautifying any web UI). Generates creative, polished code and UI designs that avoid mediocre AI aesthetics.
What it loads into context
Frontmatter
78 tokensAlways available to the agent
SKILL.md
4,562 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
- 核心原则
- 前端美学指南
- 避免通用 AI 美学
- 实现复杂性与美学匹配
- 工作流程
- 示例场景
- 代码质量标准
- 技术栈参考
- 检查清单
- 最后提醒
Files
SKILL.mdcore14,509 bytes
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# Frontend Design Skill
此技能指导创建独特的生产级前端界面,避免平庸的"AI 粗糙"美学。实现真正可用的代码,并高度关注美学细节和创意选择。
## When to Use This Skill
使用此技能当用户请求:
- 构建 Web 组件、页面或完整应用程序
- 创建着陆页、仪表盘或营销页面
- 设计 React、Vue 或原生 HTML/CSS 界面
- 美化或重新设计现有的 Web UI
- 创建海报、素材或视觉设计元素(用于 Web)
- 需要高设计品质和独特美学的任何前端项目
View the complete source on GitHublocal-diff-review
When your agent uses it
基于本地 git diff 的代码审查技能。用于在提交 PR 前先做自检评审,严格复用 pr-review 的三维度标准(代码质量标准、FastGPT 风格规范、常见问题清单),支持审查未暂存改动、已暂存改动、某次提交、或当前分支相对基线分支的全部改动。
What it loads into context
Frontmatter
94 tokensAlways available to the agent
SKILL.md
929 tokensWhen the skill is activated
Reference documents
9,677 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- 核心原则
- 审查标准来源(必须遵循)
- 使用场景
- 信息收集流程
- 审查步骤
- 输出格式(建议)
- 评审时的行为约束
- 常用触发语句(示例)
Files
SKILL.mdcore3,191 bytesSKILL.mdcore3,191 bytesSKILL.mdcore3,191 bytescode-quality-standards.mddoc15,420 bytescommon-issues-checklist.mddoc17,794 bytes
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# Local Diff Review(提交前本地评审)
## 核心原则
1. 审查标准必须与 `pr-review` 保持一致,不允许自定义弱化标准。
2. 先审查再改代码:默认先输出问题清单,只有用户明确要求才改代码。
3. 结论必须可执行:每个问题都要给出文件路径、行号、风险说明、修复建议。
## 审查标准来源(必须遵循)
- 代码质量标准:[`./code-quality-standards.md`](code-quality-standards.md)
- 常见问题清单:[`./common-issues-checklist.md`](common-issues-checklist.md)
> 说明:本 skill 的“评审准则”以 `pr-review` 当前版本为准,以上链接即唯一标准来源。View the complete source on GitHubmcp-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
1,938 tokensWhen the skill is activated
Reference documents
18,723 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.mdcore9,092 bytesreference/evaluation.mddoc21,663 bytesreference/mcp_best_practices.mddoc7,330 bytesreference/node_mcp_server.mddoc28,550 bytesreference/python_mcp_server.mddoc25,099 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:
View the complete source on GitHubplanning-with-files
When your agent uses it
Transforms workflow to use Manus-style persistent markdown files for planning, progress tracking, and knowledge storage. Use when starting complex tasks, multi-step projects, research tasks, or when the user mentions planning, organizing work, tracking progress, or wants structured output.
What it loads into context
Frontmatter
59 tokensAlways available to the agent
SKILL.md
925 tokensWhen the skill is activated
Reference documents
1,905 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Quick Start
- The 3-File Pattern
- Core Workflow
- task_plan.md Template
- notes.md Template
- Critical Rules
- When to Use This Pattern
- Anti-Patterns to Avoid
- Advanced Patterns
Files
SKILL.mdcore3,876 bytesSKILL.mdcore3,876 bytesSKILL.mdcore3,876 bytesSKILL.mdcore3,876 bytesexamples.mddoc4,426 bytesreference.mddoc3,478 bytes
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# Planning with Files
Work like Manus: Use persistent markdown files as your "working memory on disk."
## Quick Start
Before ANY complex task:
1. **Create `task_plan.md`** in the working directory
2. **Define phases** with checkboxes
3. **Update after each phase** - mark [x] and change status
4. **Read before deciding** - refresh goals in attention window
## The 3-File PatternView the complete source on GitHubprompt-optimize
When your agent uses it
Expert prompt engineering skill that transforms Claude into "Alpha-Prompt" - a master prompt engineer who collaboratively crafts high-quality prompts through flexible dialogue. Activates when user asks to "optimize prompt", "improve system instruction", "enhance AI instruction", or mentions prompt engineering tasks.
What it loads into context
Frontmatter
65 tokensAlways available to the agent
SKILL.md
2,393 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
- Core Identity Transformation
- Operating Principles
- Interaction Workflow
- Knowledge Base Reference
- Quality Standards
- Important Reminders
- Example Scenarios
- Final Mandate
Files
SKILL.mdcore8,481 bytes
Read SKILL.md
# 提示词优化专家 (Alpha-Prompt)
## When to Use This Skill
触发场景:
- 用户明确要求"优化提示词"、"改进 prompt"、"提升指令质量"
- 用户提供了现有的提示词并希望改进
- 用户描述了一个 AI 应用场景,需要设计提示词
- 用户提到"prompt engineering"、"系统指令"、"AI 角色设定"
- 用户询问如何让 AI 表现得更好、更专业
## Core Identity Transformation
当此技能激活时,你将转变为**元提示词工程师 Alpha-Prompt**:View the complete source on GitHubsoftware-copyright-writer
When your agent uses it
根据真实代码仓库、官网页面、运行界面、模块范围和目标软著数量,分析软件著作权(软著)申报方向,拆分可申报主题,检查 Logo、版权、备案、截图和源码等材料约束,生成 3w-4w 字正文、局部代码片段、源码原文、网页截图证据和 .docx 文档。Use when Claude needs to prepare or split legitimate software copyright registration materials from code repositories, product pages, running UI screenshots, module scopes, or source evidence.
What it loads into context
Frontmatter
128 tokensAlways available to the agent
SKILL.md
5,358 tokensWhen the skill is activated
Reference documents
7,723 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- Compliance Boundary
- Output Mode
- Workflow
- Scripts
- References
- Output Rules
- Failure Rules
Scripts executed separately
scripts/_fetch_web_evidence.mjsscripts/assemble_source_code.pyscripts/export_ruanzhu_docx.pyscripts/fetch_web_evidence.pyscripts/package.json
Files
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Read SKILL.md
# Software Copyright Writer
## Overview
使用这个 skill 处理“根据代码仓库和官网材料写软著”的完整流程,而不是只写一篇泛泛的介绍文档。它面向任意软件产品或平台项目,不绑定某个特定产品、技术框架或行业。
先判断仓库里到底能拆出几个像样的软著主题,再补材料、写正文、整理源码原文、抓网页证据、导出 `.docx`。如果仓库体量根本撑不起用户要的数量,直接指出来,不要硬凑题目。
仓库和 GitHub 只作为内部分析输入。最终软著正文必须使用“软件/系统/平台/产品”的正式说明口径,介绍产品功能、业务流程、运行界面和技术实现,不要写成代码仓库分析报告。
## Compliance Boundary
这个 skill 只用于整理真实软件项目的申报材料,不用于伪造软件、伪造截图、伪造权属、虚构功能或包装不存在的源码。
View the complete source on GitHubSkills included
- create-skill-file
- create-skill-file
- daily-ai-news
- deep-reading-analyst
- dry-refactoring
- fastgpt-workflow-generator
- frontend-design
- local-diff-review
- mcp-builder
- planning-with-files
- prompt-optimize
- software-copyright-writer
Repository facts
- License
- MIT
- Created
- Oct 31, 2025
- Last pushed
- May 15, 2026
- Forks
- 28
- Open issues
- 1
- Project activity
- Slowing
Before you install
Network or broad shellAutomated signals, not a guarantee
Checked Nov 6, 2026
Not fully analyzed: some files were too long, unreadable or missing. This never lowers the level.
Show 51 notes
create-skill-file/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedcreate-skill-file/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedcreate-skill-file/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedcreate-skill-file-EN/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedcreate-skill-file-EN/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedcreate-skill-file-EN/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzeddaily-ai-news/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzeddaily-ai-news/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzeddeep-reading-analyst/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzeddeep-reading-analyst/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzeddry-refactoring/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzeddry-refactoring/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzeddry-refactoring/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzeddry-refactoring/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzeddry-refactoring/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzeddry-refactoring/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzeddry-refactoring/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzeddry-refactoring/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzeddry-refactoring/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzeddry-refactoring/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzed
- No broad tool permissions
- 1 dangerous shell commandin 1 file: mcp-builder/reference/node_mcp_server.md:541
- 233 network referencesin 23 files: daily-ai-news/references/news_sources.md:9 fastgpt-workflow-generator/templates/AI金融日报.json:363 fastgpt-workflow-generator/templates/简历筛选助手_飞书.json:2325 and 20 more
- 4 obfuscation signalsin 1 file: fastgpt-workflow-generator/templates/简历筛选助手_飞书.json:903
- No instruction overrides
- 8 executable scriptsin 8 files: fastgpt-workflow-generator/scripts/validate_workflow.js:1 mcp-builder/scripts/connections.py:1 mcp-builder/scripts/evaluation.py:1 and 5 more
- 38 references to secretsin 14 files: local-diff-review/common-issues-checklist.md:745 local-diff-review/code-quality-standards.md:140 mcp-builder/reference/evaluation.md:398 and 11 more
- No requests to vote in Hot
Show all 284 signals by file
create-skill-file-EN/SKILL.md
- Access to secretsline 87
[Credential-related source omitted] - Network accessline 466
- [Claude Agent Skills Official Documentation](https://docs.claude.com/en/docs/agents-and-tools/agent-skills) - Network accessline 467
- [Best Practices Checklist](https://docs.claude.com/en/docs/agents-and-tools/agent-skills/best-practices)
create-skill-file-EN/examples/bad-example.md
- Access to secretsline 182
[Credential-related source omitted] - Access to secretsline 226
[Credential-related source omitted] - Network accessline 678
# Check green environment health curl https://myapp-prod-green.aws.com/health - Network accessline 679
curl https://myapp-prod-green.aws.com/health - Network accessline 686
# Run smoke tests against green environment BASE_URL=https://myapp-prod-green.aws.com npm run test:smoke - Network accessline 687
BASE_URL=https://myapp-prod-green.aws.com npm run test:smoke - Network accessline 708
# Verify production URL serves new version curl https://myapp.com/version - Network accessline 709
curl https://myapp.com/version - Network accessline 752
# 2. Verify old version is serving curl https://myapp.com/version - Network accessline 753
curl https://myapp.com/version
create-skill-file-EN/examples/good-example.md
- Network accessline 278
- [Alembic Documentation](https://alembic.sqlalchemy.org/) - Network accessline 279
- [SQLAlchemy Documentation](https://docs.sqlalchemy.org/) - Network accessline 363
- Copy Swagger UI static files to `docs/api/` - Configure to load generated spec - Test in browser: `http://localhost:8000/docs` - Network accessline 365
- Test in browser: `http://localhost:8000/docs` - Network accessline 446
View documentation at: http://localhost:8000/docs - Network accessline 536
Access at: - Swagger UI: `http://localhost:8000/docs` - Network accessline 537
- Swagger UI: `http://localhost:8000/docs` - Network accessline 538
- ReDoc: `http://localhost:8000/redoc` - Network accessline 539
- OpenAPI JSON: `http://localhost:8000/openapi.json` - Network accessline 579
- [OpenAPI Specification](https://spec.openapis.org/oas/latest.html) - Network accessline 580
- [FastAPI Documentation](https://fastapi.tiangolo.com/) - Network accessline 581
- [Swagger Documentation](https://swagger.io/docs/) - Network accessline 879
- [OWASP Top 10](https://owasp.org/www-project-top-ten/) - Network accessline 880
- [Python Best Practices](https://docs.python-guide.org/) - Network accessline 881
- [Clean Code Principles](https://www.amazon.com/Clean-Code-Handbook-Software-Craftsmanship/dp/0132350882)
create-skill-file/SKILL.md
- Access to secretsline 87
[Credential-related source omitted] - Network accessline 466
- [Claude Agent Skills 官方文档](https://docs.claude.com/en/docs/agents-and-tools/agent-skills) - Network accessline 467
- [Best Practices Checklist](https://docs.claude.com/en/docs/agents-and-tools/agent-skills/best-practices)
create-skill-file/examples/bad-example.md
- Access to secretsline 182
[Credential-related source omitted] - Access to secretsline 226
[Credential-related source omitted] - Network accessline 678
# Check green environment health curl https://myapp-prod-green.aws.com/health - Network accessline 679
curl https://myapp-prod-green.aws.com/health - Network accessline 686
# Run smoke tests against green environment BASE_URL=https://myapp-prod-green.aws.com npm run test:smoke - Network accessline 687
BASE_URL=https://myapp-prod-green.aws.com npm run test:smoke - Network accessline 708
# Verify production URL serves new version curl https://myapp.com/version - Network accessline 709
curl https://myapp.com/version - Network accessline 752
# 2. Verify old version is serving curl https://myapp.com/version - Network accessline 753
curl https://myapp.com/version
create-skill-file/examples/good-example.md
- Network accessline 278
- [Alembic Documentation](https://alembic.sqlalchemy.org/) - Network accessline 279
- [SQLAlchemy Documentation](https://docs.sqlalchemy.org/) - Network accessline 363
- Copy Swagger UI static files to `docs/api/` - Configure to load generated spec - Test in browser: `http://localhost:8000/docs` - Network accessline 365
- Test in browser: `http://localhost:8000/docs` - Network accessline 446
View documentation at: http://localhost:8000/docs - Network accessline 536
Access at: - Swagger UI: `http://localhost:8000/docs` - Network accessline 537
- Swagger UI: `http://localhost:8000/docs` - Network accessline 538
- ReDoc: `http://localhost:8000/redoc` - Network accessline 539
- OpenAPI JSON: `http://localhost:8000/openapi.json` - Network accessline 579
- [OpenAPI Specification](https://spec.openapis.org/oas/latest.html) - Network accessline 580
- [FastAPI Documentation](https://fastapi.tiangolo.com/) - Network accessline 581
- [Swagger Documentation](https://swagger.io/docs/) - Network accessline 879
- [OWASP Top 10](https://owasp.org/www-project-top-ten/) - Network accessline 880
- [Python Best Practices](https://docs.python-guide.org/) - Network accessline 881
- [Clean Code Principles](https://www.amazon.com/Clean-Code-Handbook-Software-Craftsmanship/dp/0132350882)
daily-ai-news/SKILL.md
- Network accessline 47
**Recommended Primary Sources** (choose 3-5 per session): - VentureBeat AI: https://venturebeat.com/category/ai/ - Network accessline 48
- VentureBeat AI: https://venturebeat.com/category/ai/ - Network accessline 49
- TechCrunch AI: https://techcrunch.com/category/artificial-intelligence/ - Network accessline 50
- The Verge AI: https://www.theverge.com/ai-artificial-intelligence - Network accessline 51
- MIT Technology Review AI: https://www.technologyreview.com/topic/artificial-intelligence/ - Network accessline 52
- AI News: https://artificialintelligence-news.com/ - Network accessline 53
- AI Hub Today: https://ai.hubtoday.app/
daily-ai-news/references/news_sources.md
- Network accessline 9
### 1. VentureBeat AI - **URL**: https://venturebeat.com/category/ai/ - Network accessline 10
- **URL**: https://venturebeat.com/category/ai/ - Network accessline 16
### 2. TechCrunch AI - **URL**: https://techcrunch.com/category/artificial-intelligence/ - Network accessline 17
- **URL**: https://techcrunch.com/category/artificial-intelligence/ - Network accessline 23
### 3. The Verge AI - **URL**: https://www.theverge.com/ai-artificial-intelligence - Network accessline 24
- **URL**: https://www.theverge.com/ai-artificial-intelligence - Network accessline 30
### 4. MIT Technology Review AI - **URL**: https://www.technologyreview.com/topic/artificial-intelligence/ - Network accessline 31
- **URL**: https://www.technologyreview.com/topic/artificial-intelligence/ - Network accessline 37
### 5. AI News - **URL**: https://artificialintelligence-news.com/ - Network accessline 38
- **URL**: https://artificialintelligence-news.com/ - Network accessline 44
### 6. AI Hub Today - **URL**: https://ai.hubtoday.app/ - Network accessline 45
- **URL**: https://ai.hubtoday.app/ - Network accessline 57
### 1. OpenAI Blog - **URL**: https://openai.com/blog - Network accessline 58
- **URL**: https://openai.com/blog - Network accessline 64
### 2. Google AI Blog - **URL**: https://blog.google/technology/ai/ - Network accessline 65
- **URL**: https://blog.google/technology/ai/ - Network accessline 71
### 3. DeepMind Blog - **URL**: https://deepmind.google/discover/blog/ - Network accessline 72
- **URL**: https://deepmind.google/discover/blog/ - Network accessline 78
### 4. Anthropic News - **URL**: https://www.anthropic.com/news - Network accessline 79
- **URL**: https://www.anthropic.com/news - Network accessline 85
### 5. Microsoft AI Blog - **URL**: https://blogs.microsoft.com/ai/ - Network accessline 86
- **URL**: https://blogs.microsoft.com/ai/ - Network accessline 92
### 6. Meta AI Blog - **URL**: https://ai.meta.com/blog/ - Network accessline 93
- **URL**: https://ai.meta.com/blog/ - Network accessline 105
### 1. arXiv.org - **URL**: https://arxiv.org/list/cs.AI/recent - Network accessline 106
- **URL**: https://arxiv.org/list/cs.AI/recent - Network accessline 116
### 2. Hugging Face - **URL**: https://huggingface.co/blog - Network accessline 117
- **URL**: https://huggingface.co/blog - Network accessline 123
### 3. Papers with Code - **URL**: https://paperswithcode.com/ - Network accessline 124
- **URL**: https://paperswithcode.com/ - Network accessline 130
### 4. Google DeepMind Publications - **URL**: https://deepmind.google/research/publications/ - Network accessline 131
- **URL**: https://deepmind.google/research/publications/ - Network accessline 143
### 1. AI Ethics Newsletter - **URL**: https://aiethicsnewsletter.com/ - Network accessline 144
- **URL**: https://aiethicsnewsletter.com/ - Network accessline 150
### 2. Synced Review - **URL**: https://syncedreview.com/ - Network accessline 151
- **URL**: https://syncedreview.com/ - Network accessline 157
### 3. KDnuggets - **URL**: https://www.kdnuggets.com/ - Network accessline 158
- **URL**: https://www.kdnuggets.com/ - Network accessline 164
### 4. VentureBeat AI Beat - **URL**: https://venturebeat.com/category/ai/ - Network accessline 165
- **URL**: https://venturebeat.com/category/ai/ - Network accessline 171
### 5. Towards Data Science - **URL**: https://towardsdatascience.com/ - Network accessline 172
- **URL**: https://towardsdatascience.com/ - Network accessline 207
**For quick updates**: - Focus on AI News (aggregator) and AI Hub Today (https://ai.hubtoday.app/) - Network accessline 208
- Focus on AI News (aggregator) and AI Hub Today (https://ai.hubtoday.app/)
dry-refactoring/SKILL.md
fastgpt-workflow-generator/references/json_structure_spec.md
- Access to secretsline 309
[Credential-related source omitted]
fastgpt-workflow-generator/references/node_types_reference.md
- Network accessline 174
{ "key": "system_httpReqUrl", "value": "https://api.weather.com/v1?city={$VARIABLE_NODE_ID.city$}" - Network accessline 175
"key": "system_httpReqUrl", "value": "https://api.weather.com/v1?city={$VARIABLE_NODE_ID.city$}" }, - Network accessline 176
"value": "https://api.weather.com/v1?city={$VARIABLE_NODE_ID.city$}"
fastgpt-workflow-generator/scripts/validate_workflow.js
- Executable scriptline 1
#!/usr/bin/env node
fastgpt-workflow-generator/templates/AI金融日报.json
- Network accessline 363
"list": [], "defaultValue": "", "value": "https://www.pedaily.cn/vcpeevent/", - Network accessline 364
"defaultValue": "", "value": "https://www.pedaily.cn/vcpeevent/", "canEdit": false, - Network accessline 365
"value": "https://www.pedaily.cn/vcpeevent/", - Network accessline 429
"list": [], "defaultValue": "", "value": "https://tech.sina.com.cn/chuangshiji/", - Network accessline 430
"defaultValue": "", "value": "https://tech.sina.com.cn/chuangshiji/", "canEdit": false, - Network accessline 431
"value": "https://tech.sina.com.cn/chuangshiji/", - Network accessline 541
"label": "", "description": "common:core.module.input.description.Http Request Url", "placeholder": "https://api.ai.com/getInventory", - Network accessline 542
"description": "common:core.module.input.description.Http Request Url", "placeholder": "https://api.ai.com/getInventory", "required": false, - Network accessline 543
"placeholder": "https://api.ai.com/getInventory", - Network accessline 544
"required": false, "value": "https://api.bochaai.com/v1/web-search", "valueDesc": "", - Network accessline 545
"value": "https://api.bochaai.com/v1/web-search", - Network accessline 795
"list": [], "defaultValue": "", "value": "https://www.36kr.com/information/contact/", - Network accessline 796
"defaultValue": "", "value": "https://www.36kr.com/information/contact/", "canEdit": false, - Network accessline 797
"value": "https://www.36kr.com/information/contact/", - Network accessline 982
"description": "common:core.app.tip.systemPromptTip", "placeholder": "common:core.app.tip.chatNodeSystemPromptTip", "value": "# 角色\n你是新闻数据处理专家,你擅长全面提取和分析大量新闻条目,你能够确保所有的新闻均被完整处理并输出,绝不遗漏任何符合筛选标准的内容,即使是20条以上的内容也能全部处理并输出。新闻内 - Network accessline 983
"placeholder": "common:core.app.tip.chatNodeSystemPromptTip", "value": "# 角色\n你是新闻数据处理专家,你擅长全面提取和分析大量新闻条目,你能够确保所有的新闻均被完整处理并输出,绝不遗漏任何符合筛选标准的内容,即使是20条以上的内容也能全部处理并输出。新闻内容的时间范围严格控制在:{{$utE8TlbcSIICH2i8.qLUQfhG0ILRX$}}\n##背景\n你负责接收并处理大 - Network accessline 984
"value": "# 角色\n你是新闻数据处理专家,你擅长全面提取和分析大量新闻条目,你能够确保所有的新闻均被完整处理并输出,绝不遗漏任何符合筛选标准的内容,即使是20条以上的内容也能全部处理并输出。新闻内容的时间范围严格控制在:{{$utE8TlbcSIICH2i8.qLUQfhG0ILRX$}}\n##背景\n你负责接收并处理大量新闻数据,需要确保即使面对20条以上的新闻内容,也能全部进行处理并完整输出,不会因为数量多而省略或简化任何符合条件的新闻条目。\n## 技能\ - Network accessline 1737
"label": "", "description": "common:core.module.input.description.Http Request Url", "placeholder": "https://api.ai.com/getInventory", - Network accessline 1738
"description": "common:core.module.input.description.Http Request Url", "placeholder": "https://api.ai.com/getInventory", "required": false, - Network accessline 1739
"placeholder": "https://api.ai.com/getInventory", - Network accessline 1740
"required": false, "value": "https://api.bochaai.com/v1/web-search", "valueDesc": "", - Network accessline 1741
"value": "https://api.bochaai.com/v1/web-search", - Network accessline 2037
"label": "", "description": "common:core.module.input.description.Http Request Url", "placeholder": "https://api.ai.com/getInventory", - Network accessline 2038
"description": "common:core.module.input.description.Http Request Url", "placeholder": "https://api.ai.com/getInventory", "required": false, - Network accessline 2039
"placeholder": "https://api.ai.com/getInventory", - Network accessline 2040
"required": false, "value": "https://api.bochaai.com/v1/web-search", "valueDesc": "", - Network accessline 2041
"value": "https://api.bochaai.com/v1/web-search", - Network accessline 2337
"label": "", "description": "common:core.module.input.description.Http Request Url", "placeholder": "https://api.ai.com/getInventory", - Network accessline 2338
"description": "common:core.module.input.description.Http Request Url", "placeholder": "https://api.ai.com/getInventory", "required": false, - Network accessline 2339
"placeholder": "https://api.ai.com/getInventory", - Network accessline 2340
"required": false, "value": "https://api.bochaai.com/v1/web-search", "valueDesc": "", - Network accessline 2341
"value": "https://api.bochaai.com/v1/web-search", - Network accessline 2618
"label": "", "valueType": "string", "value": "function main({ input }) {\n // 使用正则表达式找到\"(https://www.36kr.com/information/other/)\"之后到\"查看更多\"之前的内容\n const regex = /\\(https:\\/\\/www\\.36kr\\.com\\/information\\/othe - Network accessline 2619
"valueType": "string", "value": "function main({ input }) {\n // 使用正则表达式找到\"(https://www.36kr.com/information/other/)\"之后到\"查看更多\"之前的内容\n const regex = /\\(https:\\/\\/www\\.36kr\\.com\\/information\\/other\\/\\)\\s*(.*?)(?=查看更多 - Network accessline 2620
"value": "function main({ input }) {\n // 使用正则表达式找到\"(https://www.36kr.com/information/other/)\"之后到\"查看更多\"之前的内容\n const regex = /\\(https:\\/\\/www\\.36kr\\.com\\/information\\/other\\/\\)\\s*(.*?)(?=查看更多)/s;\n const match = input.match
fastgpt-workflow-generator/templates/文档翻译助手.json
- Network accessline 425
"description": "common:core.app.tip.systemPromptTip", "placeholder": "common:core.app.tip.chatNodeSystemPromptTip", "value": "Role \n文档内容翻译专家\n如果有图片链接存在,图片链接以Markdown格式返回,并且补全链接,使用根地址https://cloud.fastgpt.io补全链接缺失的根地址\n - Network accessline 426
"placeholder": "common:core.app.tip.chatNodeSystemPromptTip", "value": "Role \n文档内容翻译专家\n如果有图片链接存在,图片链接以Markdown格式返回,并且补全链接,使用根地址https://cloud.fastgpt.io补全链接缺失的根地址\n\nBackground \n具备丰富的多语言翻译经验,精通文档内容的精准转换,能够根据指定目标语言高效完成翻译任务。熟悉各类 - Network accessline 427
"value": "Role \n文档内容翻译专家\n如果有图片链接存在,图片链接以Markdown格式返回,并且补全链接,使用根地址https://cloud.fastgpt.io补全链接缺失的根地址\n\nBackground \n具备丰富的多语言翻译经验,精通文档内容的精准转换,能够根据指定目标语言高效完成翻译任务。熟悉各类文档结构和语境,确保译文准确、流畅且符合目标语言习惯。\n\nAttention \n- 仅输出翻译后的译文,不包含任何解释或原文内容\n-
fastgpt-workflow-generator/templates/简历筛选助手_飞书.json
- Possible obfuscationline 903
"value": "# 角色\n您具备精准匹配简历与岗位需求的能力,尤其擅长对候选人的教育背景进行专业评估与量化评分\n## 评分标准\n### 1.<U+200B>学历层次(8分)<U+200B>\n博士/硕士(8分)\n本科(6分)\n专科及以下(4分)\n要求:学历需与岗位相关,如技术岗优先理工科。\n### <U+200B>2.GPA/成绩表现(7分)<U+200B>\n前10%或GPA≥3.5(7分)\n前30%或GPA≥3.0(5分)\n其他(3分)\n要求:需标注班级/专业排名或具体分数,若未注明扣2分。\n### - Possible obfuscationline 1168
"value": "# 角色\n您具备精准匹配简历与岗位需求的能力,尤其擅长对候选人的工作经历进行专业评估与量化评分\n## 评分标准\n###<U+200B> 1.校园经历(10分)<U+200B>\n<U+200B>学生干部/社团活动:校级干部(5分)、院级(3分)、班级(1分)\n<U+200B>竞赛/项目成果:国家级奖项(5分)、省级(3分)、校级(1分)\n要求:需明确角色(如组织者、核心成员)及成果量化(如“策划活动覆盖500人”)。\n<U+200B>### 2.实习/工作经历(12分)<U+200B>\n<U+200B>岗位相关性:与目标职位高度相关(8分 - Possible obfuscationline 1433
"value": "# 角色\n您具备精准匹配简历与岗位需求的能力,尤其擅长对候选人的技能与证书进行专业评估与量化评分\n## 评分标准\n### 1.<U+200B>专业技能(10分)<U+200B>\n<U+200B>岗位核心技能:如编程语言、设计软件等,每项熟练(3分)、基础(1分),上限6分\n<U+200B>证书等级:国家认证高级证书(如PMP、CFA,4分)、基础证书(如英语四级,2分)\n### 2.<U+200B>通用技能(6分)<U+200B>\n<U+200B>语言能力:英语六级(3分)、雅思6.5+/托福90+(+2分)\n<U+200B>计算机能力:Office - Possible obfuscationline 1698
"value": "# 角色\n您具备精准匹配简历与岗位需求的能力,尤其擅长对候选人的个人综合能力进行专业评估与量化评分\n## 评分标准\n<U+200B>### 1.逻辑与表达(满分10分)<U+200B>\n<U+200B>简历结构:板块清晰、重点突出(5分),混乱扣3分\n<U+200B>语言表述:无错别字/语法错误(3分),每处错误扣0.5分\n<U+200B>量化描述:80%以上内容含数据支撑(+2分)\n<U+200B>### 2.综合素质(满分15分)<U+200B>\n<U+200B>团队协作:描述团队项目中的角色贡献(5分)\n<U+200B>问题解决:案例体现分析能力(如“独立 - Network accessline 2325
"label": "", "description": "common:core.module.input.description.Http Request Url", "placeholder": "https://api.ai.com/getInventory", - Network accessline 2326
"description": "common:core.module.input.description.Http Request Url", "placeholder": "https://api.ai.com/getInventory", "required": false, - Network accessline 2327
"placeholder": "https://api.ai.com/getInventory", - Network accessline 2328
"required": false, "value": "https://open.feishu.cn/open-apis/auth/v3/app_access_token/internal", "valueDesc": "", - Network accessline 2329
[Credential-related source omitted] - Access to secretsline 2329
[Credential-related source omitted] - Access to secretsline 2475
[Credential-related source omitted] - Access to secretsline 2476
[Credential-related source omitted] - Network accessline 2567
"label": "", "description": "common:core.module.input.description.Http Request Url", "placeholder": "https://api.ai.com/getInventory", - Network accessline 2568
"description": "common:core.module.input.description.Http Request Url", "placeholder": "https://api.ai.com/getInventory", "required": false, - Network accessline 2569
"placeholder": "https://api.ai.com/getInventory", - Network accessline 2570
"required": false, "value": "https://open.feishu.cn/open-apis/bitable/v1/apps/{{$mj4ZG8C1WKcTaU7N.jiSE3GH5I5LbdzXg$}}/tables/{{$mj4ZG8C1WKcTaU7N.lO14ic8JMABDGum8$}}/records", "valueDesc": "", - Network accessline 2571
"value": "https://open.feishu.cn/open-apis/bitable/v1/apps/{{$mj4ZG8C1WKcTaU7N.jiSE3GH5I5LbdzXg$}}/tables/{{$mj4ZG8C1WKcTaU7N.lO14ic8JMABDGum8$}}/records", - Network accessline 3434
"label": "app_id", "type": "internal", "description": "飞书开发平台的应用ID(可以改为自己的)\n飞书开放平台:https://open.feishu.cn", - Network accessline 3435
"type": "internal", "description": "飞书开发平台的应用ID(可以改为自己的)\n飞书开放平台:https://open.feishu.cn", "required": false, - Network accessline 3436
"description": "飞书开发平台的应用ID(可以改为自己的)\n飞书开放平台:https://open.feishu.cn", - Network accessline 3451
"label": "app_secret", "type": "internal", "description": "飞书开放平台的应用密钥(可以改为自己的)\n飞书开放平台:https://open.feishu.cn", - Network accessline 3452
"type": "internal", "description": "飞书开放平台的应用密钥(可以改为自己的)\n飞书开放平台:https://open.feishu.cn", "required": false, - Network accessline 3453
"description": "飞书开放平台的应用密钥(可以改为自己的)\n飞书开放平台:https://open.feishu.cn", - Network accessline 3485
"label": "table_url", "type": "internal", "description": "(此处无需填写!!!)\n飞书多维表格的链接,若不填入则会自动创建一个新的飞书多维表格\n严格按照如下参考格式:https://xxxxxxxxxx.feishu.cn/base/xxxxxxxxxxxxx?table=xxxxxxxxxx&view=xxxxxxxxxxx", - Network accessline 3486
"type": "internal", "description": "(此处无需填写!!!)\n飞书多维表格的链接,若不填入则会自动创建一个新的飞书多维表格\n严格按照如下参考格式:https://xxxxxxxxxx.feishu.cn/base/xxxxxxxxxxxxx?table=xxxxxxxxxx&view=xxxxxxxxxxx", "required": false, - Network accessline 3487
"description": "(此处无需填写!!!)\n飞书多维表格的链接,若不填入则会自动创建一个新的飞书多维表格\n严格按照如下参考格式:https://xxxxxxxxxx.feishu.cn/base/xxxxxxxxxxxxx?table=xxxxxxxxxx&view=xxxxxxxxxxx", - Network accessline 3488
"required": false, "valueType": "string", "defaultValue": "https://yarbzsh1dg9.feishu.cn/base/ERLpb39CaaxJsGsxgNncfYkhnFf?table=tbl8pEJpyxSl0sJB&view=vewN4yQCKY", - Network accessline 3489
"valueType": "string", "defaultValue": "https://yarbzsh1dg9.feishu.cn/base/ERLpb39CaaxJsGsxgNncfYkhnFf?table=tbl8pEJpyxSl0sJB&view=vewN4yQCKY", "enums": [ - Network accessline 3490
"defaultValue": "https://yarbzsh1dg9.feishu.cn/base/ERLpb39CaaxJsGsxgNncfYkhnFf?table=tbl8pEJpyxSl0sJB&view=vewN4yQCKY",
frontend-design/SKILL.md
- Network accessline 276
position: absolute; inset: 0; background-image: url("data:image/svg+xml,%3Csvg viewBox='0 0 200 200' xmlns='http://www.w3.org/2000/svg'%3E%3Cfilter id='noise'%3E%3CfeTurbulence type='fractalNoise' baseFrequency='0.9' numOctaves='4' /%3E - Network accessline 277
inset: 0; background-image: url("data:image/svg+xml,%3Csvg viewBox='0 0 200 200' xmlns='http://www.w3.org/2000/svg'%3E%3Cfilter id='noise'%3E%3CfeTurbulence type='fractalNoise' baseFrequency='0.9' numOctaves='4' /%3E%3C/filter%3E%3Crect w - Network accessline 278
background-image: url("data:image/svg+xml,%3Csvg viewBox='0 0 200 200' xmlns='http://www.w3.org/2000/svg'%3E%3Cfilter id='noise'%3E%3CfeTurbulence type='fractalNoise' baseFrequency='0.9' numOctaves='4' /%3E%3C/filter%3E%3Crect width='100%25
local-diff-review/code-quality-standards.md
local-diff-review/common-issues-checklist.md
- Network accessline 133
// ❌ 问题代码 async function fetchUserData(userId: string) { const response = await fetch(`/api/users/${userId}`); - Network accessline 134
async function fetchUserData(userId: string) { const response = await fetch(`/api/users/${userId}`); const data = await response.json(); - Network accessline 135
const response = await fetch(`/api/users/${userId}`); - Network accessline 141
async function fetchUserData(userId: string): Promise<UserData> { try { const response = await fetch(`/api/users/${userId}`); - Network accessline 143
const response = await fetch(`/api/users/${userId}`); - Access to secretsline 745
[Credential-related source omitted] - Access to secretsline 749
[Credential-related source omitted] - Access to secretsline 752
[Credential-related source omitted] - Access to secretsline 753
[Credential-related source omitted] - Access to secretsline 772
[Credential-related source omitted] - Access to secretsline 779
[Credential-related source omitted] - Access to secretsline 781
[Credential-related source omitted]
mcp-builder/LICENSE.txt
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 202
### Core MCP Documentation (Load First) - **MCP Protocol**: Start with sitemap at `https://modelcontextprotocol.io/sitemap.xml`, then fetch specific pages with `.md` suffix - Network accessline 203
- **MCP Protocol**: Start with sitemap at `https://modelcontextprotocol.io/sitemap.xml`, then fetch specific pages with `.md` suffix - Network accessline 211
### SDK Documentation (Load During Phase 1/2) - **Python SDK**: Fetch from `https://raw.githubusercontent.com/modelcontextprotocol/python-sdk/main/README.md` - Network accessline 212
- **Python SDK**: Fetch from `https://raw.githubusercontent.com/modelcontextprotocol/python-sdk/main/README.md` - Network accessline 213
- **TypeScript SDK**: Fetch from `https://raw.githubusercontent.com/modelcontextprotocol/typescript-sdk/main/README.md`
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]
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`);
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]
mcp-builder/scripts/connections.py
- Executable scriptline 1
Executable file
mcp-builder/scripts/evaluation.py
planning-with-files/reference.md
software-copyright-writer/SKILL.md
- Network accessline 272
python3 scripts/fetch_web_evidence.py \ --url https://github.com/openai/openai-cookbook \ - Network accessline 273
--url https://github.com/openai/openai-cookbook \ - Network accessline 274
--url https://openai.com \ - Network accessline 281
python3 scripts/fetch_web_evidence.py \ --url https://example.com/dashboard \ - Network accessline 282
--url https://example.com/dashboard \ - Network accessline 293
python3 scripts/fetch_web_evidence.py \ --url https://example.com/dashboard \ - Network accessline 294
--url https://example.com/dashboard \ - Network accessline 304
python3 scripts/fetch_web_evidence.py \ --url https://example.com/dashboard \ - Network accessline 305
--url https://example.com/dashboard \ - Access to secretsline 317
[Credential-related source omitted] - Network accessline 331
首页 | https://example.com/dashboard | main - Network accessline 332
订单页面 | https://example.com/orders | #app - Network accessline 340
{ "name": "产品资料上传界面", "url": "https://example.com/workbench", - Network accessline 341
"name": "产品资料上传界面", "url": "https://example.com/workbench", "click_texts": ["资料中心", "产品资料库", "新建/导入", "文本资料"] - Network accessline 342
"url": "https://example.com/workbench",
software-copyright-writer/scripts/_fetch_web_evidence.mjs
- Executable scriptline 1
Executable file
software-copyright-writer/scripts/assemble_source_code.py
- Executable scriptline 1
#!/usr/bin/env python3
software-copyright-writer/scripts/export_ruanzhu_docx.py
software-copyright-writer/scripts/fetch_web_evidence.py
software-copyright-writer/scripts/package.json
- Executable scriptline 1
Executable file
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.
Signal confidence: 217 facts
- Access to secrets in code of the SKILL.mdcreate-skill-file-EN/SKILL.md:87High confidence
- Network access in prose of the SKILL.mdcreate-skill-file-EN/SKILL.md:466Low confidence
- Network access in prose of the SKILL.mdcreate-skill-file-EN/SKILL.md:467Low confidence
- Access to secrets in code of documentation: a variable, placeholder or call, not a stored valuecreate-skill-file-EN/examples/bad-example.md:182Low confidence
- Access to secrets in code of documentation: a variable, placeholder or call, not a stored valuecreate-skill-file-EN/examples/bad-example.md:226Low confidence
- Network access in code of documentationcreate-skill-file-EN/examples/bad-example.md:678Low confidence
- Network access in code of documentationcreate-skill-file-EN/examples/bad-example.md:679Low confidence
- Network access in code of documentationcreate-skill-file-EN/examples/bad-example.md:686Low confidence
- Network access in code of documentationcreate-skill-file-EN/examples/bad-example.md:687Low confidence
- Network access in code of documentationcreate-skill-file-EN/examples/bad-example.md:708Low confidence
- Network access in code of documentationcreate-skill-file-EN/examples/bad-example.md:709Low confidence
- Network access in code of documentationcreate-skill-file-EN/examples/bad-example.md:752Low confidence
- Network access in code of documentationcreate-skill-file-EN/examples/bad-example.md:753Low confidence
- Network access in prose of documentationcreate-skill-file-EN/examples/good-example.md:278Low confidence
- Network access in prose of documentationcreate-skill-file-EN/examples/good-example.md:279Low confidence
- Network access in prose of documentationcreate-skill-file-EN/examples/good-example.md:363Low confidence
- Network access in prose of documentationcreate-skill-file-EN/examples/good-example.md:365Low confidence
- Network access in code of documentationcreate-skill-file-EN/examples/good-example.md:446Low confidence
- Network access in prose of documentationcreate-skill-file-EN/examples/good-example.md:536Low confidence
- Network access in prose of documentationcreate-skill-file-EN/examples/good-example.md:537Low confidence
- Network access in prose of documentationcreate-skill-file-EN/examples/good-example.md:538Low confidence
- Network access in prose of documentationcreate-skill-file-EN/examples/good-example.md:539Low confidence
- Network access in prose of documentationcreate-skill-file-EN/examples/good-example.md:579Low confidence
- Network access in prose of documentationcreate-skill-file-EN/examples/good-example.md:580Low confidence
- Network access in prose of documentationcreate-skill-file-EN/examples/good-example.md:581Low confidence
- Network access in prose of documentationcreate-skill-file-EN/examples/good-example.md:879Low confidence
- Network access in prose of documentationcreate-skill-file-EN/examples/good-example.md:880Low confidence
- Network access in prose of documentationcreate-skill-file-EN/examples/good-example.md:881Low confidence
- Access to secrets in code of the SKILL.mdcreate-skill-file/SKILL.md:87High confidence
- Network access in prose of the SKILL.mdcreate-skill-file/SKILL.md:466Low confidence
- Network access in prose of the SKILL.mdcreate-skill-file/SKILL.md:467Low confidence
- Access to secrets in code of documentation: a variable, placeholder or call, not a stored valuecreate-skill-file/examples/bad-example.md:182Low confidence
- Access to secrets in code of documentation: a variable, placeholder or call, not a stored valuecreate-skill-file/examples/bad-example.md:226Low confidence
- Network access in code of documentationcreate-skill-file/examples/bad-example.md:678Low confidence
- Network access in code of documentationcreate-skill-file/examples/bad-example.md:679Low confidence
- Network access in code of documentationcreate-skill-file/examples/bad-example.md:686Low confidence
- Network access in code of documentationcreate-skill-file/examples/bad-example.md:687Low confidence
- Network access in code of documentationcreate-skill-file/examples/bad-example.md:708Low confidence
- Network access in code of documentationcreate-skill-file/examples/bad-example.md:709Low confidence
- Network access in code of documentationcreate-skill-file/examples/bad-example.md:752Low confidence
- Network access in code of documentationcreate-skill-file/examples/bad-example.md:753Low confidence
- Network access in prose of documentationcreate-skill-file/examples/good-example.md:278Low confidence
- Network access in prose of documentationcreate-skill-file/examples/good-example.md:279Low confidence
- Network access in prose of documentationcreate-skill-file/examples/good-example.md:363Low confidence
- Network access in prose of documentationcreate-skill-file/examples/good-example.md:365Low confidence
- Network access in code of documentationcreate-skill-file/examples/good-example.md:446Low confidence
- Network access in prose of documentationcreate-skill-file/examples/good-example.md:536Low confidence
- Network access in prose of documentationcreate-skill-file/examples/good-example.md:537Low confidence
- Network access in prose of documentationcreate-skill-file/examples/good-example.md:538Low confidence
- Network access in prose of documentationcreate-skill-file/examples/good-example.md:539Low confidence
and 167 more
Works with
| Agent | Status | Evidence | Install to |
|---|---|---|---|
| Claude Code | Compatible | Standard SKILL.md create-skill-file/SKILL.md | .claude/skills/<skill-name>/ |
| Codex | Compatible | Standard SKILL.md create-skill-file/SKILL.md | .agents/skills/<skill-name>/ |
| Cursor | Compatible | Standard SKILL.md create-skill-file/SKILL.md | .cursor/skills/<skill-name>/ |
| Gemini CLI | Compatible | Standard SKILL.md create-skill-file/SKILL.md | .gemini/skills/<skill-name>/ |
| GitHub Copilot | Compatible | Standard SKILL.md create-skill-file/SKILL.md | .github/skills/<skill-name>/ |
| OpenCode | Compatible | Standard SKILL.md create-skill-file/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.