github-deep-research

# GitHub Deep Research Skill Multi-round research combining GitHub API, web_search, web_fetch to produce comprehensive markdown reports. ## Research Workflow - Round 1: GitHub API - Round 2: Discovery - Round 3: Deep Investigation - Round 4: Deep Dive ## Core Methodology ### Query Strategy **Broad to Narrow**: Start with GitHub API, then general queries, refine based on findings. ``` Round 1: GitHub API Round 2: "{topic} overview" Round 3: "{topic} architecture", "{topic} vs alternatives" Round 4: "{topic} issues", "{topic} roadmap", "site:github.com {topic}" ``` **Source Prioritization**: 1. Official docs/repos (highest weight) 2. Technical blogs (Medium, Dev.to) 3. News articles (verified outlets) 4. Community discussions (Reddit, HN) 5. Social media (lowest weight, for sentiment) ### Research Rounds **Round 1 - GitHub API** Directly execute `scripts/github_api.py` without `read_file()`: ```bash python /path/to/skill/scripts/github_api.py <owner> <repo> summary python /path/to/skill/scripts/github_api.py <owner> <repo> readme python /path/to/skill/scripts/github_api.py <owner> <repo> tree ``` **Available commands (the last argument of `github_api.py`):** - summary - info - readme - tree - languages - contributors - commits - issues - prs - releases **Round 2 - Discovery (3-5 web_search)** - Get overview and identify key terms - Find official website/repo - Identify main players/competitors **Round 3 - Deep Investigation (5-10 web_search + web_fetch)** - Technical architecture details - Timeline of key events - Community sentiment - Use web_fetch on valuable URLs for full content **Round 4 - Deep Dive** - Analyze commit history for timeline - Review issues/PRs for feature evolution - Check contributor activity ## Report Structure Follow template in `assets/report_template.md`: 1. **Metadata Block** - Date, confidence level, subject 2. **Executive Summary** - 2-3 sentence overview with key metrics 3. **Chronological Timeline** - Phased breakdown with dates 4. **Key Analysis Sections** - Topic-specific deep dives 5. **Metrics & Comparisons** - Tables, growth charts 6. **Strengths & Weaknesses** - Balanced assessment 7. **Sources** - Categorized references 8. **Confidence Assessment** - Claims by confidence level 9. **Methodology** - Research approach used ### Mermaid Diagrams Include diagrams where helpful: **Timeline (Gantt)**: ```mermaid gantt title Project Timeline dateFormat YYYY-MM-DD section Phase 1 Development :2025-01-01, 2025-03-01 section Phase 2 Launch :2025-03-01, 2025-04-01 ``` **Architecture (Flowchart)**: ```mermaid flowchart TD A[User] --> B[Coordinator] B --> C[Planner] C --> D[Research Team] D --> E[Reporter] ``` **Comparison (Pie/Bar)**: ```mermaid pie title Market Share "Project A" : 45 "Project B" : 30 "Others" : 25 ``` ## Confidence Scoring Assign confidence based on source quality: | Confidence | Criteria | |------------|----------| | High (90%+) | Official docs, GitHub data, multiple corroborating sources | | Medium (70-89%) | Single reliable source, recent articles | | Low (50-69%) | Social media, unverified claims, outdated info | ## Output Save report as: `research_{topic}_{YYYYMMDD}.md` ### Formatting Rules - Chinese content: Use full-width punctuation（，。：；！？） - Technical terms: Provide Wiki/doc URL on first mention - Tables: Use for metrics, comparisons - Code blocks: For technical examples - Mermaid: For architecture, timelines, flows ## Best Practices 1. **Start with official sources** - Repo, docs, company blog 2. **Verify dates from commits/PRs** - More reliable than articles 3. **Triangulate claims** - 2+ independent sources 4. **Note conflicting info** - Don't hide contradictions 5. **Distinguish fact vs opinion** - Label speculation clearly 6. **CRITICAL: Always include inline citations** - Use `[citation:Title](URL)` format immediately after each claim from external sources 7. **Extract URLs from search results** - web_search returns {title, url, snippet} - always use the URL field 8. **Update as you go** - Don't wait until end to synthesize ### Citation Examples **Good - With inline citations:** ```markdown The project gained 10,000 stars within 3 months of launch [citation:GitHub Stats](https://github.com/owner/repo). The architecture uses LangGraph for workflow orchestration [citation:LangGraph Docs](https://langchain.com/langgraph). ``` **Bad - Without citations:** ```markdown The project gained 10,000 stars within 3 months of launch. The architecture uses LangGraph for workflow orchestration. ```