npx skills add ...
npx skills add bytedance/deer-flow --skill github-deep-research
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.
npx skills add bytedance/deer-flow --skill github-deep-research
Multi-round research combining GitHub API, web_search, web_fetch to produce comprehensive markdown reports.
Broad to Narrow: Start with GitHub API, then general queries, refine based on findings.
Source Prioritization:
Round 1 - GitHub API
Directly execute scripts/github_api.py without read_file():
Available commands (the last argument of github_api.py):
Round 2 - Discovery (3-5 web_search)
Round 3 - Deep Investigation (5-10 web_search + web_fetch)
Round 4 - Deep Dive
Follow template in assets/report_template.md:
Include diagrams where helpful:
Timeline (Gantt):
Architecture (Flowchart):
Comparison (Pie/Bar):
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| Low (50-69%) | Social media, unverified claims, outdated info |
Save report as: research_{topic}_{YYYYMMDD}.md
[citation:Title](URL) format immediately after each claim from external sourcesGood - With inline citations:
Bad - Without citations:
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, 2025-04-01flowchart TD
A[User] --> B[Coordinator]
B --> C[Planner]
C --> D[Research Team]
D --> E[Reporter]pie title Market Share
"Project A" : 45
"Project B" : 30
"Others" : 25The 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).The project gained 10,000 stars within 3 months of launch.
The architecture uses LangGraph for workflow orchestration.