github-deep-research
Conduct multi-round deep research on any GitHub Repo.
Skill by jiaqiang000
Chalk Labs
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Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
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About
Use cases: documents, research
Reviews
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What's inside
- Skill name
github-deep-research- Description
- Conduct multi-round deep research on any GitHub Repo. Use when users request comprehensive analysis, timeline reconstruction, competitive analysis, or in-depth investigation of GitHub. Produces structured markdown reports with executive summaries, chronological timelines, metrics analysis, and Mermaid diagrams. Triggers on Github repository URL or open source projects.
- License
- MIT
- Instructions
- 163 lines in SKILL.md · view on GitHub
Before installing
- Ships executable scripts
Files (3)
- SKILL.md
- report_template.md · assets/
- github_api.py · scripts/
SKILL.md (first lines)
# 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:From jiaqiang000/AI-Teacher-Copilot, MIT.
Signals
- Stars
- 0
- Forks
- 0
- Open issues
- 0
- Last commit (this folder)
- Aug 3, 2026 (2 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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github-deep-research skill. Agent Mart. https://agentmart.dev/skills/jiaqiang000-github-deep-research (last updated 2026-10-24)