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name: git-researcher description: High-performance GitHub research orchestrator. Features search result caching, multi-dimensional analysis, and sub-agent delegation to minimize token usage and prevent context contamination.

Git Researcher

User Guide (How to use)

You can trigger this skill by asking me to research GitHub projects. Here are some examples:

• Basic Search: "Research Python LLM agent projects with more than 100 stars."
• Complex Search: "Search for topic:ai topic:rag stars:50..500 language:python. Analyze the top 2 and give me a Chinese report (--lang zh)."
• Specific Project: "Analyze the repository 'langchain-ai/langchain' from technical, user, and investor perspectives."
• Batch Analysis: "From my last search results, analyze project #3 and #5."

Parameters you can specify:

• Keywords/Topics: topic:ai, llm, agent, etc.
• Metrics: stars:>100, forks:10..50.
• Language: --lang zh (Chinese report), --lang en (English report, default).
• Limit: "Show me the top 10 results."

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Architectural Principles

• Orchestration: The main agent acts as an orchestrator, delegating heavy lifting to sub-agents.
• Persistence: Search results are cached locally in search_results.json to avoid redundant API calls.
• Isolation: Each repository analysis is handled by a fresh sub-agent (e.g., generalist or codebase_investigator) within its specific directory.

Workflow

1. Search & Cache Phase

• Use gh search repos with user criteria.
• Action: Save the raw JSON output to search_results.json in the current directory.
• Example: gh search repos "..." --json ... > search_results.json
• Logic: If the user asks for more projects from a previous query, check search_results.json first before re-searching.

2. Selection & Delegation

• Read search_results.json and present a numbered list to the user.
• For each selected project, delegate the process to a sub-agent.

3. Execution Phase (Sub-Agent Delegation)

For each project, spawn a sub-agent (using the generalist tool) with the following specific mission:

1. Clone: Clone the repository into a unique directory.
2. Investigate: Use codebase_investigator inside that directory to understand the Technical, User, and Investor perspectives.
3. Draft: Create the git-research.md report based on references/report_guide.md.
4. Report Back: Return only a concise summary of the analysis to the Orchestrator.

4. Reporting & Synthesis

• The Orchestrator summarizes the status of all analyzed projects.
• Ensures the workspace remains clean by isolating project-specific artifacts.

Guidelines

• Token Efficiency: Never read the entire codebase into the main context. Always use codebase_investigator via a sub-agent.
• Anti-Redundancy: Verify search_results.json and existing directories before every major action.
• Multi-lingual: If --lang zh is used, ensure the sub-agent generates the report in Chinese.