github-deep-research

📁 bytedance/deer-flow 📅 12 days ago
77
总安装量
77
周安装量
#5392
全站排名
安装命令
npx skills add https://github.com/bytedance/deer-flow --skill github-deep-research

Agent 安装分布

opencode 74
gemini-cli 73
github-copilot 73
codex 72
kimi-cli 71
amp 71

Skill 文档

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():

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):

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

  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. Reference sources – Add source references near claims where applicable
  7. Update as you go – Don’t wait until end to synthesize