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: Official docs/repos (highest weight) Technical blogs (Medium, Dev.to) News articles (verified outlets) Community discussions (Reddit, HN) Social media (lowest weight, for sentiment) Research Rounds Round 1 - GitHub API Directly execute scripts/github_api.py without read_file(): python /path/to/skill/scripts/github_api.py summary python /path/to/skill/scripts/github_api.py readme python /path/to/skill/scripts/github_api.py 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: Metadata Block - Date, confidence level, subject Executive Summary - 2-3 sentence overview with key metrics Chronological Timeline - Phased breakdown with dates Key Analysis Sections - Topic-specific deep dives Metrics & Comparisons - Tables, growth charts Strengths & Weaknesses - Balanced assessment Sources - Categorized references Confidence Assessment - Claims by confidence level Methodology - Research approach used Mermaid Diagrams Include diagrams where helpful: Timeline (Gantt): 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): flowchart TD A[User] --> B[Coordinator] B --> C[Planner] C --> D[Research Team] D --> E[Reporter] Comparison (Pie/Bar): 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 Start with official sources - Repo, docs, company blog Verify dates from commits/PRs - More reliable than articles Triangulate claims - 2+ independent sources Note conflicting info - Don't hide contradictions Distinguish fact vs opinion - Label speculation clearly Reference sources - Add source references near claims where applicable Update as you go - Don't wait until end to synthesize Weekly Installs289Repositorybytedance/deer-flowGitHub Stars31.0KFirst SeenFeb 17, 2026Security AuditsGen Agent Trust HubFailSocketPassSnykWarnInstalled onopencode283gemini-cli282github-copilot282codex282kimi-cli280amp280