---
name: github-deep-research
description: Conduct multi-round deep research on any GitHub repository. Use when users request comprehensive analysis, timeline reconstruction, competitive analysis, or in-depth investigation of a GitHub project. Produces structured markdown reports with executive summaries, chronological timelines, metrics analysis, and Mermaid diagrams. Triggers on GitHub repository URLs or open source project names.
---

# 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**

Execute the bundled `scripts/github_api.py` using the `bash` tool:
```bash
python scripts/github_api.py <owner> <repo> summary
python scripts/github_api.py <owner> <repo> readme
python scripts/github_api.py <owner> <repo> tree
```

The script path is relative to this skill's base directory (shown in the skill output).

**Available commands (the last argument of `github_api.py`):**
- summary — comprehensive overview (stars, forks, languages, latest release)
- info — basic repository metadata
- readme — repository README content
- tree — directory structure (depth 3)
- languages — language breakdown by bytes
- contributors — top contributors
- commits — recent commit history
- issues — open/closed issues
- prs — pull requests
- releases — release history

**Environment:** Set `GITHUB_TOKEN` for higher API rate limits (optional but recommended).

**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. **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 a multi-agent workflow [citation:Official Docs](https://docs.example.com).
```

**Bad - Without citations:**
```markdown
The project gained 10,000 stars within 3 months of launch.
The architecture uses a multi-agent workflow.
```
