#428 by GitHub stars
zubair-trabzada/ai-marketing-claude
AI Marketing Suite for Claude Code. 15 marketing skills with parallel subagents — audit any website, generate copy, email sequences, ad campaigns, content calendars, competitive intelligence, and client-ready PDF reports.
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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market/SKILL.md
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Heat
5.1- Star growth, last 7 daysAhead of 87% of tracked repositories
- Star growth, last 24 hoursAhead of 69% of tracked repositories
- Rank movement, last 7 daysAhead of 29% 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
- market
market - market-ads
skills/market-ads - market-audit
skills/market-audit - market-brand
skills/market-brand - market-competitors
skills/market-competitors - market-copy
skills/market-copy - market-emails
skills/market-emails - market-funnel
skills/market-funnel - market-landing
skills/market-landing - market-launch
skills/market-launch - market-proposal
skills/market-proposal - market-report
skills/market-report - market-report-pdf
skills/market-report-pdf - market-seo
skills/market-seo - market-social
skills/market-social
How it works
When your agent uses it
What it loads into context
Frontmatter
0 tokensAlways available to the agent
SKILL.md
1,198 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
- Command Reference
- Routing Logic
- Business Context Detection
- Output Standards
- File Output
- Cross-Skill References
Files
SKILL.mdcore5,327 bytes
Read SKILL.md
# AI Marketing Suite — Main Orchestrator
You are a comprehensive AI marketing analysis and content generation system for Claude Code. You help entrepreneurs, agency builders, and solopreneurs analyze websites, generate marketing content, audit funnels, create client proposals, and build marketing strategies — all from the command line.
## Command Reference
| Command | Description | Output |
|---------|-------------|--------|
| `/market audit <url>` | Full marketing audit (parallel subagents) | MARKETING-AUDIT.md |
| `/market quick <url>` | 60-second marketing snapshot | Terminal output |
| `/market copy <url>` | Generate optimized copy for any page | Terminal + COPY-SUGGESTIONS.md |
| `/market emails <topic/url>` | Generate email sequences | EMAIL-SEQUENCES.md |
| `/market social <topic/url>` | Generate social media content calendar | SOCIAL-CALENDAR.md |
| `/market ads <url>` | Generate ad creative and copy | AD-CAMPAIGNS.md |
| `/market funnel <url>` | Analyze and optimize sales funnel | FUNNEL-ANALYSIS.md |View the complete source on GitHubWhen your agent uses it
What it loads into context
Frontmatter
0 tokensAlways available to the agent
SKILL.md
4,089 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 This Skill Is Invoked
- Phase 1: Campaign Foundation
- Phase 2: Platform-Specific Ad Generation
- Phase 3: Retargeting Sequences
- Phase 4: Budget and Performance
- Phase 5: Ad Variations and Testing
- Output Format: AD-CAMPAIGNS.md
- Terminal Output
- Cross-Skill Integration
Files
SKILL.mdcore15,123 bytes
Read SKILL.md
# Ad Creative & Copy Generation
You are the advertising engine for `/market ads <url>`. You generate complete ad campaigns across platforms with full copy variations, audience targeting strategies, budget recommendations, and creative specifications. Every ad is ready for production or handoff to a media buyer.
## When This Skill Is Invoked
The user runs `/market ads <url>`. Fetch the target site to understand the business, product, audience, and value propositions. Generate complete campaign structures across relevant platforms. Output everything to AD-CAMPAIGNS.md.
---
## Phase 1: Campaign Foundation
### 1.1 Business and Offer Analysis
Before writing any ads, establish:View the complete source on GitHubWhen your agent uses it
What it loads into context
Frontmatter
0 tokensAlways available to the agent
SKILL.md
2,938 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 This Skill Is Invoked
- Phase 1: Discovery (Pre-Analysis)
- Phase 2: Analysis (Parallel Subagent Execution)
- Phase 3: Synthesis (Aggregation and Scoring)
- Output Format: MARKETING-AUDIT.md
- Terminal Output
- Error Handling
- Cross-Skill Integration
Files
SKILL.mdcore12,401 bytes
Read SKILL.md
# Marketing Audit Orchestrator
You are the full marketing audit engine for `/market audit <url>`. You launch 5 parallel subagents, aggregate their results, and produce a unified MARKETING-AUDIT.md report that is client-ready and revenue-focused.
## When This Skill Is Invoked
The user runs `/market audit <url>`. This is the flagship command of the entire suite. It produces the most comprehensive deliverable: a scored, prioritized, actionable marketing audit.
---
## Phase 1: Discovery (Pre-Analysis)
Before launching subagents, perform these discovery steps:
### 1.1 Fetch the Target URLView the complete source on GitHubWhen your agent uses it
What it loads into context
Frontmatter
0 tokensAlways available to the agent
SKILL.md
3,884 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
- Skill Purpose
- When to Use
- How to Execute
- Output Format
- Key Principles
Files
SKILL.mdcore16,756 bytesSKILL.mdcore16,756 bytesSKILL.mdcore16,756 bytes
Read SKILL.md
# Brand Voice Analysis and Guidelines Generation
## Skill Purpose
Analyze a brand's voice, tone, and messaging across all available channels and generate a comprehensive brand voice guidelines document. This skill examines how a brand communicates, identifies patterns and inconsistencies, and produces actionable guidelines that any writer or marketer can follow to maintain brand consistency.
## When to Use
- User wants to understand or document a brand's voice
- User needs brand voice guidelines for a team, freelancers, or agency
- User wants to ensure consistency across marketing channels
- User is rebranding or refining their brand identity
- User wants to compare their brand voice to competitors
- Triggered by `/market brand <url>` or `/market brand`
## How to Execute
View the complete source on GitHubWhen your agent uses it
What it loads into context
Frontmatter
0 tokensAlways available to the agent
SKILL.md
4,030 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 This Skill Is Invoked
- Phase 1: Competitor Identification
- Phase 2: Competitor Analysis Framework
- Phase 3: SWOT Analysis
- Phase 4: Strategic Recommendations
- Phase 5: Monitoring and Ongoing Intelligence
- Output Format: COMPETITOR-REPORT.md
- Terminal Output
- Cross-Skill Integration
Scripts executed separately
../../scripts/competitor_scanner.py
Files
../../scripts/competitor_scanner.pyruns9,667 bytesSKILL.mdcore17,333 bytes
Read SKILL.md
# Competitive Intelligence Analysis
You are the competitive intelligence engine for `/market competitors <url>`. You identify competitors, analyze their marketing strategies, and produce a comprehensive comparison report that reveals positioning gaps, steal-worthy tactics, and differentiation opportunities. Output is structured for both strategic decision-making and client presentations.
## When This Skill Is Invoked
The user runs `/market competitors <url>`. Fetch the target site, identify competitors, analyze each one, and produce a COMPETITOR-REPORT.md with actionable intelligence.
---
## Phase 1: Competitor Identification
### 1.1 Competitor Categories
Identify competitors across three tiers:View the complete source on GitHubWhen your agent uses it
What it loads into context
Frontmatter
0 tokensAlways available to the agent
SKILL.md
2,983 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 This Skill Is Invoked
- Phase 1: Copy Discovery
- Phase 2: Copy Analysis
- Phase 3: Copy Generation
- Output Format
- Cross-Skill Integration
Files
SKILL.mdcore12,274 bytes
Read SKILL.md
# Copywriting Analysis & Generation
You are the copywriting engine for `/market copy <url>`. You analyze existing website copy, score it, and generate optimized alternatives with specific before/after examples. Every recommendation is grounded in proven copywriting frameworks and tailored to the detected business type.
## When This Skill Is Invoked
The user runs `/market copy <url>`. Fetch the target page(s), analyze the existing copy, score it, and produce both terminal output and a detailed COPY-SUGGESTIONS.md file.
---
## Phase 1: Copy Discovery
### 1.1 Fetch and Parse
Use `WebFetch` to retrieve the target URL. Extract:View the complete source on GitHubWhen your agent uses it
What it loads into context
Frontmatter
0 tokensAlways available to the agent
SKILL.md
3,904 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 This Skill Is Invoked
- Phase 1: Context Gathering
- Phase 2: Email Frameworks
- Phase 3: Sequence Templates
- Phase 4: Segmentation and Personalization
- Phase 5: Metrics and Benchmarks
- Output Format: EMAIL-SEQUENCES.md
- Terminal Output
- Cross-Skill Integration
Files
SKILL.mdcore15,495 bytes
Read SKILL.md
# Email Sequence Generation
You are the email marketing engine for `/market emails <topic/url>`. You generate complete, ready-to-send email sequences with subject lines, body copy, timing, and segmentation strategies. Every sequence is built on proven email frameworks and calibrated to industry benchmarks.
## When This Skill Is Invoked
The user runs `/market emails <topic/url>`. If a URL is provided, fetch the site to understand the business, product, audience, and voice. If a topic is provided, work from the topic description and ask clarifying questions if needed. Output complete sequences to EMAIL-SEQUENCES.md.
---
## Phase 1: Context Gathering
### 1.1 Business Understanding
Before writing any emails, establish:View the complete source on GitHubWhen your agent uses it
What it loads into context
Frontmatter
0 tokensAlways available to the agent
SKILL.md
4,105 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 This Skill Is Invoked
- Phase 1: Funnel Discovery and Mapping
- Phase 2: Page-by-Page Analysis
- Phase 3: Funnel Metrics and Benchmarks
- Phase 4: Optimization Recommendations
- Phase 5: Nurture Sequence Integration
- Output Format: FUNNEL-ANALYSIS.md
- Terminal Output
- Cross-Skill Integration
Files
SKILL.mdcore16,158 bytes
Read SKILL.md
# Sales Funnel Analysis & Optimization
You are the funnel analysis engine for `/market funnel <url>`. You map the complete conversion path from first visit to purchase, identify drop-off points, quantify friction, and recommend specific optimizations with revenue impact estimates. Every recommendation is prioritized by estimated lift and implementation effort.
## When This Skill Is Invoked
The user runs `/market funnel <url>`. Fetch the target site and trace every step a visitor takes from landing to conversion. Analyze each step for friction, clarity, and effectiveness. Output a complete analysis to FUNNEL-ANALYSIS.md.
---
## Phase 1: Funnel Discovery and Mapping
### 1.1 Identify the Funnel Type
Detect which funnel type the site uses:View the complete source on GitHubWhen your agent uses it
What it loads into context
Frontmatter
0 tokensAlways available to the agent
SKILL.md
3,134 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
- Skill Purpose
- When to Use
- How to Execute
- Output Format
- Key Principles
Files
SKILL.mdcore12,984 bytes
Read SKILL.md
# Landing Page CRO Analysis
## Skill Purpose
Perform a comprehensive Conversion Rate Optimization (CRO) analysis on any landing page. This skill produces a section-by-section teardown with prioritized, actionable fixes that directly impact conversion rates.
## When to Use
- User provides a landing page URL and asks for conversion optimization
- User asks for landing page feedback, review, or audit
- User wants to improve signup, lead capture, or purchase rates
- Triggered by `/market landing <url>` or `/market cro <url>`
## How to Execute
### Step 1: Identify the Page Type
Determine which type of landing page you are analyzing. This affects benchmark expectations and scoring weights.View the complete source on GitHubWhen your agent uses it
What it loads into context
Frontmatter
0 tokensAlways available to the agent
SKILL.md
4,167 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
- Skill Purpose
- When to Use
- How to Execute
- Output Format
- Key Principles
Files
SKILL.mdcore17,576 bytes
Read SKILL.md
# Product/Service Launch Playbook Generator
## Skill Purpose
Generate a complete, week-by-week launch playbook for any product, service, or feature launch. This skill produces a tactical plan with templates, checklists, email sequences, social posts, and metrics tracking -- everything needed to execute a successful launch.
## When to Use
- User is planning to launch a new product, service, feature, or offering
- User asks for a launch plan, go-to-market strategy, or launch checklist
- User wants to coordinate a multi-channel launch campaign
- Triggered by `/market launch` or `/market launch <product description>`
## How to Execute
### Step 1: Gather Launch Context
Before generating the playbook, collect these inputs from the user (ask if not provided):View the complete source on GitHubWhen your agent uses it
What it loads into context
Frontmatter
0 tokensAlways available to the agent
SKILL.md
3,728 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
- Skill Purpose
- When to Use
- How to Execute
- Output Format
- Key Principles
Files
SKILL.mdcore16,303 bytes
Read SKILL.md
# Client Proposal Generator for Marketing Services
## Skill Purpose
Generate a professional, client-ready marketing services proposal. This skill produces a complete proposal document that positions the agency/consultant as the clear choice, frames pricing with anchoring and tiered options, and includes ROI projections to justify the investment.
## When to Use
- User wants to create a proposal for a prospective marketing client
- User has completed a discovery call and needs to formalize the engagement
- User wants a template for their marketing agency's proposals
- Triggered by `/market proposal` or `/market proposal <client name>`
## How to Execute
### Step 1: Gather Proposal Inputs
Collect these details from the user (ask if not provided):View the complete source on GitHubWhen your agent uses it
What it loads into context
Frontmatter
0 tokensAlways available to the agent
SKILL.md
3,741 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
- Skill Purpose
- When to Use
- How to Execute
- Output Format
- Key Principles
Scripts executed separately
../../scripts/analyze_page.py
Files
../../scripts/analyze_page.pyruns17,234 bytesSKILL.mdcore14,209 bytes
Read SKILL.md
# Marketing Report Generator (Markdown Format)
## Skill Purpose
Generate a comprehensive, professionally formatted marketing report in Markdown. This skill compiles data from all previous audit and analysis results into a single, client-ready document with scores, findings, recommendations, and a prioritized action plan with revenue impact estimates.
## When to Use
- User wants a full marketing report for a client or their own business
- User has completed one or more audit skills and wants a compiled report
- User asks for a marketing assessment, scorecard, or analysis document
- Triggered by `/market report` or `/market report <domain>`
## How to Execute
### Step 1: Collect All Available Data
Before generating the report, check for any existing audit data from previous skill runs. Look for these files in the project directory:View the complete source on GitHubWhen your agent uses it
What it loads into context
Frontmatter
0 tokensAlways available to the agent
SKILL.md
3,421 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
- Skill Purpose
- When to Use
- When to Use PDF vs Markdown
- How to Execute
- PDF Report Contents
- Color Scheme
- Score-to-Color Mapping
- Troubleshooting
- Integration with Other Skills
- Output
- Key Principles
Scripts executed separately
../../scripts/analyze_page.py../../scripts/generate_pdf_report.py
Files
../../scripts/analyze_page.pyruns17,234 bytes../../scripts/generate_pdf_report.pyruns20,037 bytesSKILL.mdcore14,050 bytesSKILL.mdcore14,050 bytesSKILL.mdcore14,050 bytesSKILL.mdcore14,050 bytesSKILL.mdcore14,050 bytesSKILL.mdcore14,050 bytesSKILL.mdcore14,050 bytes
Read SKILL.md
# PDF Marketing Report Generator
## Skill Purpose
Generate a professional, visually polished PDF marketing report using the Python script `scripts/generate_pdf_report.py`. This skill collects all available audit and analysis data, structures it into the expected JSON format, invokes the script, and produces a branded PDF with score gauges, bar charts, comparison tables, findings, and a prioritized action plan.
## When to Use
- User wants a PDF version of the marketing report (not just Markdown)
- User is preparing a deliverable for a client presentation
- User asks for a "polished report", "client-ready report", or "PDF report"
- User wants a visual report with charts and scores
- Triggered by `/market report-pdf` or `/market report-pdf <domain>`
## When to Use PDF vs Markdown
| Format | Best For | Pros | Cons |View the complete source on GitHubWhen your agent uses it
What it loads into context
Frontmatter
0 tokensAlways available to the agent
SKILL.md
4,276 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
- Skill Purpose
- When to Use
- How to Execute
- Output Format
- Key Principles
Scripts executed separately
../../scripts/analyze_page.py
Files
../../scripts/analyze_page.pyruns17,234 bytesSKILL.mdcore18,075 bytesSKILL.mdcore18,075 bytes
Read SKILL.md
# SEO Content Audit
## Skill Purpose
Perform a comprehensive SEO audit of a webpage or website, covering on-page SEO, content quality (E-E-A-T), keyword analysis, technical SEO, and content strategy. This skill combines automated analysis via `scripts/analyze_page.py` with expert-level manual review to produce an actionable SEO audit document.
## When to Use
- User provides a URL and asks for SEO analysis, audit, or recommendations
- User wants to improve organic search rankings and traffic
- User asks about on-page SEO, meta tags, content quality, or technical SEO
- User wants a content gap analysis or content strategy recommendations
- Triggered by `/market seo <url>` or `/market seo`
## How to Execute
### Step 1: Run Automated AnalysisView the complete source on GitHubWhen your agent uses it
What it loads into context
Frontmatter
0 tokensAlways available to the agent
SKILL.md
3,760 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 This Skill Is Invoked
- Phase 1: Brand and Audience Discovery
- Phase 2: Content Strategy Framework
- Phase 3: Hook Formulas
- Phase 4: Hashtag Strategy
- Phase 5: Engagement Tactics
- Phase 6: Content Repurposing Strategy
- Phase 7: 30-Day Content Calendar
- Phase 8: Trending Format Detection
- Output Format: SOCIAL-CALENDAR.md
- Terminal Output
- Cross-Skill Integration
Files
SKILL.mdcore14,331 bytes
Read SKILL.md
# Social Media Content Calendar & Generation
You are the social media engine for `/market social <topic/url>`. You generate a complete 30-day content calendar with platform-specific posts, hooks, hashtags, and a content repurposing strategy. Every post is ready to publish or hand to a social media manager.
## When This Skill Is Invoked
The user runs `/market social <topic/url>`. If a URL is provided, fetch the site to understand the brand, audience, and content themes. If a topic is provided, build the strategy around that topic. Output a full calendar to SOCIAL-CALENDAR.md.
---
## Phase 1: Brand and Audience Discovery
### 1.1 Brand Context
Establish before generating any content:View the complete source on GitHubSkills included
Repository facts
- License
- MIT
- Created
- Mar 2, 2026
- Last pushed
- Mar 2, 2026
- Forks
- 730
- Open issues
- 3
- Project activity
- Slowing
Rank over the last 12 weeks
Now #428 · best #333 · down 58 in 30 days
- #416 on Nov 1
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- #428 since Nov 6
74 earlier periods
- #335 on Aug 2
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Before you install
Network or broad shellAutomated signals, not a guarantee
Checked Nov 2, 2026
Not fully analyzed: some files were too long, unreadable or missing. This never lowers the level.
Show 9 notes
skills/market-brand/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/market-brand/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/market-report-pdf/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/market-report-pdf/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/market-report-pdf/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/market-report-pdf/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/market-report-pdf/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/market-report-pdf/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills/market-seo/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzed
- No broad tool permissions
- 1 dangerous shell commandin 1 file: market-report-pdf/SKILL.md:249
- 41 network referencesin 4 files: scripts/analyze_page.py:316 scripts/competitor_scanner.py:186 scripts/generate_pdf_report.py:421 and 1 more
- No hidden or obfuscated text
- No instruction overrides
- 5 executable scriptsin 3 files: scripts/analyze_page.py:1 scripts/competitor_scanner.py:1 scripts/generate_pdf_report.py:1
- No access to secrets
- No requests to vote in Hot
Show all 47 signals by file
scripts/analyze_page.py
- Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Executable scriptline 1
#!/usr/bin/env python3 - Network accessline 316
req = urllib.request.Request(url, headers=headers) - Network accessline 316
req = urllib.request.Request(url, headers=headers) - Network accessline 316
req = urllib.request.Request(url, headers=headers) - Network accessline 317
try: response = urllib.request.urlopen(req, timeout=15, context=ctx) return response.read().decode("utf-8", errors="replace") - Network accessline 317
try: response = urllib.request.urlopen(req, timeout=15, context=ctx) return response.read().decode("utf-8", errors="replace") - Network accessline 317
try: response = urllib.request.urlopen(req, timeout=15, context=ctx) return response.read().decode("utf-8", errors="replace") - Network accessline 318
response = urllib.request.urlopen(req, timeout=15, context=ctx) - Network accessline 318
response = urllib.request.urlopen(req, timeout=15, context=ctx) - Network accessline 318
response = urllib.request.urlopen(req, timeout=15, context=ctx) - Network accessline 343
ctx.check_hostname = False ctx.verify_mode = ssl.CERT_NONE req = urllib.request.Request(sitemap_url, headers={"User-Agent": "MarketingBot/1.0"}) - Network accessline 343
ctx.check_hostname = False ctx.verify_mode = ssl.CERT_NONE req = urllib.request.Request(sitemap_url, headers={"User-Agent": "MarketingBot/1.0"}) - Network accessline 343
ctx.check_hostname = False ctx.verify_mode = ssl.CERT_NONE req = urllib.request.Request(sitemap_url, headers={"User-Agent": "MarketingBot/1.0"}) - Network accessline 344
ctx.verify_mode = ssl.CERT_NONE req = urllib.request.Request(sitemap_url, headers={"User-Agent": "MarketingBot/1.0"}) response = urllib.request.urlopen(req, timeout=10, context=ctx) - Network accessline 344
ctx.verify_mode = ssl.CERT_NONE req = urllib.request.Request(sitemap_url, headers={"User-Agent": "MarketingBot/1.0"}) response = urllib.request.urlopen(req, timeout=10, context=ctx) - Network accessline 344
ctx.verify_mode = ssl.CERT_NONE req = urllib.request.Request(sitemap_url, headers={"User-Agent": "MarketingBot/1.0"}) response = urllib.request.urlopen(req, timeout=10, context=ctx) - Network accessline 345
req = urllib.request.Request(sitemap_url, headers={"User-Agent": "MarketingBot/1.0"}) - Network accessline 345
req = urllib.request.Request(sitemap_url, headers={"User-Agent": "MarketingBot/1.0"}) - Network accessline 345
req = urllib.request.Request(sitemap_url, headers={"User-Agent": "MarketingBot/1.0"}) - Network accessline 346
response = urllib.request.urlopen(req, timeout=10, context=ctx) - Network accessline 346
response = urllib.request.urlopen(req, timeout=10, context=ctx) - Network accessline 346
response = urllib.request.urlopen(req, timeout=10, context=ctx) - Network accessline 459
print(json.dumps({ "usage": "python3 analyze_page.py <url>", "example": "python3 analyze_page.py https://calendly.com", - Network accessline 459
print(json.dumps({ "usage": "python3 analyze_page.py <url>", "example": "python3 analyze_page.py https://calendly.com", - Network accessline 459
print(json.dumps({ "usage": "python3 analyze_page.py <url>", "example": "python3 analyze_page.py https://calendly.com", - Network accessline 460
"usage": "python3 analyze_page.py <url>", "example": "python3 analyze_page.py https://calendly.com", "description": "Analyzes a webpage for marketing effectiveness" - Network accessline 460
"usage": "python3 analyze_page.py <url>", "example": "python3 analyze_page.py https://calendly.com", "description": "Analyzes a webpage for marketing effectiveness" - Network accessline 460
"usage": "python3 analyze_page.py <url>", "example": "python3 analyze_page.py https://calendly.com", "description": "Analyzes a webpage for marketing effectiveness" - Network accessline 461
"example": "python3 analyze_page.py https://calendly.com", - Network accessline 461
"example": "python3 analyze_page.py https://calendly.com", - Network accessline 461
"example": "python3 analyze_page.py https://calendly.com",
scripts/competitor_scanner.py
- Executable scriptline 1
#!/usr/bin/env python3 - Network accessline 186
req = urllib.request.Request(url, headers=headers) - Network accessline 187
try: response = urllib.request.urlopen(req, timeout=15, context=ctx) return response.read().decode("utf-8", errors="replace") - Network accessline 188
response = urllib.request.urlopen(req, timeout=15, context=ctx) - Network accessline 225
pricing_urls = [ f"https://{parsed.netloc}/pricing", - Network accessline 226
f"https://{parsed.netloc}/pricing", - Network accessline 227
f"https://{parsed.netloc}/plans", - Network accessline 228
f"https://{parsed.netloc}/price",
scripts/generate_pdf_report.py
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.
Declared and executed: 1 fact
- Contacts calendly.com, which SKILL.md, the README and the plugin manifest do not mentionscripts/analyze_page.py:461High confidence
Signal confidence: 47 facts
- Executable script in code of a file that runsscripts/analyze_page.py:1High confidence
- Executable script in code of a file that runsscripts/analyze_page.py:1High confidence
- Executable script in code of a file that runsscripts/analyze_page.py:1High confidence
- Network access in code of a file that runsscripts/analyze_page.py:316High confidence
- Network access in code of a file that runsscripts/analyze_page.py:316High confidence
- Network access in code of a file that runsscripts/analyze_page.py:316High confidence
- Network access in code of a file that runsscripts/analyze_page.py:317High confidence
- Network access in code of a file that runsscripts/analyze_page.py:317High confidence
- Network access in code of a file that runsscripts/analyze_page.py:317High confidence
- Network access in code of a file that runsscripts/analyze_page.py:318High confidence
- Network access in code of a file that runsscripts/analyze_page.py:318High confidence
- Network access in code of a file that runsscripts/analyze_page.py:318High confidence
- Network access in code of a file that runsscripts/analyze_page.py:343High confidence
- Network access in code of a file that runsscripts/analyze_page.py:343High confidence
- Network access in code of a file that runsscripts/analyze_page.py:343High confidence
- Network access in code of a file that runsscripts/analyze_page.py:344High confidence
- Network access in code of a file that runsscripts/analyze_page.py:344High confidence
- Network access in code of a file that runsscripts/analyze_page.py:344High confidence
- Network access in code of a file that runsscripts/analyze_page.py:345High confidence
- Network access in code of a file that runsscripts/analyze_page.py:345High confidence
- Network access in code of a file that runsscripts/analyze_page.py:345High confidence
- Network access in code of a file that runsscripts/analyze_page.py:346High confidence
- Network access in code of a file that runsscripts/analyze_page.py:346High confidence
- Network access in code of a file that runsscripts/analyze_page.py:346High confidence
- Network access in code of a file that runsscripts/analyze_page.py:459High confidence
- Network access in code of a file that runsscripts/analyze_page.py:459High confidence
- Network access in code of a file that runsscripts/analyze_page.py:459High confidence
- Network access in code of a file that runsscripts/analyze_page.py:460High confidence
- Network access in code of a file that runsscripts/analyze_page.py:460High confidence
- Network access in code of a file that runsscripts/analyze_page.py:460High confidence
- Network access in code of a file that runsscripts/analyze_page.py:461High confidence
- Network access in code of a file that runsscripts/analyze_page.py:461High confidence
- Network access in code of a file that runsscripts/analyze_page.py:461High confidence
- Executable script in code of a file that runsscripts/competitor_scanner.py:1High confidence
- Network access in code of a file that runsscripts/competitor_scanner.py:186High confidence
- Network access in code of a file that runsscripts/competitor_scanner.py:187High confidence
- Network access in code of a file that runsscripts/competitor_scanner.py:188High confidence
- Network access in code of a file that runsscripts/competitor_scanner.py:225High confidence
- Network access in code of a file that runsscripts/competitor_scanner.py:226High confidence
- Network access in code of a file that runsscripts/competitor_scanner.py:227High confidence
- Network access in code of a file that runsscripts/competitor_scanner.py:228High confidence
- Executable script in code of a file that runsscripts/generate_pdf_report.py:1High confidence
- Network access in code of a file that runsscripts/generate_pdf_report.py:421High confidence
- Network access in code of a file that runsscripts/generate_pdf_report.py:422High confidence
- Network access in code of the SKILL.mdmarket-report-pdf/SKILL.md:47High confidence
- Network access in code of the SKILL.mdmarket-report-pdf/SKILL.md:48High confidence
- Dangerous shell operation in code of the SKILL.mdmarket-report-pdf/SKILL.md:249High confidence
Works with
| Agent | Status | Evidence | Install to |
|---|---|---|---|
| Claude Code | Unknown | No evidence | |
| Codex | Unknown | No evidence | |
| Cursor | Unknown | No evidence | |
| Gemini CLI | Unknown | No evidence | |
| GitHub Copilot | Unknown | No evidence | |
| OpenCode | Unknown | No evidence |
- 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.
Add this badge to your README
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[](https://hotskills.dev/skill/zubair-trabzada-ai-marketing-claude/)