القائمة
Autonomous multi-source research agent with MCP server. Planner/executor architecture, 5 MCP tools. Requires 3 API keys (Tavily + Anthropic + embeddings). Research-flavor.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
4-skill academic pipeline: deep research (13-agent), academic paper (LaTeX), peer review (7-agent), pipeline orchestrator (10-stage). CC BY-NC 4.0 — non-commercial use only.
Analyzes existing workflows and processes to find inefficiencies, bottlenecks, and optimization opportunities. Goes beyond automation to improve the process itself. Use when user says "optimize my process", "find bottlenecks", "why is this slow", "improve this workflow", "process audit", or "efficiency review".
Takes a process description and generates a complete Standard Operating Procedure document with numbered steps, decision points, checklists, and troubleshooting guidance. Use when user says "write an SOP", "create SOP", "standard operating procedure", "document this process", "write a procedure for", or asks to formalize any business process.
Interactive weekly review assistant that helps business owners reflect on their week, measure progress against stated goals, and plan the next week with clarity. Use when user says "weekly review", "review my week", "what did I accomplish", "plan next week", "week in review", "how did my week go", or asks to reflect on recent work.
Maps business processes from natural language descriptions into structured workflows, identifies automation opportunities using the GREEN/YELLOW/RED framework, and generates visual workflow diagrams. Use when user says "map my workflow", "describe my process", "where should I automate", "workflow audit", or describes any business process.
GraphRAG-powered code review with blast-radius analysis via Tree-sitter AST. MCP server. Recommended for 500+ file codebases.
| name | gpt-researcher |
| description | Autonomous multi-source research agent with MCP server. Planner/executor architecture, 5 MCP tools. Requires 3 API keys (Tavily + Anthropic + embeddings). Research-flavor. |
| auto-activate | false |
Autonomous multi-source research agent with a planner/executor architecture. Gathers information from multiple sources in parallel.
Upstream: https://github.com/assafelovic/gpt-researcher MCP Server: https://github.com/assafelovic/gptr-mcp
Add to your project's .mcp.json:
{
"gpt-researcher": {
"type": "stdio",
"command": "uvx",
"args": ["gptr-mcp"],
"env": {
"TAVILY_API_KEY": "<your-key>",
"ANTHROPIC_API_KEY": "<your-key>",
"FAST_LLM": "anthropic:<your-fast-model>",
"SMART_LLM": "anthropic:<your-smart-model>"
}
}
}
Replace <your-fast-model> and <your-smart-model> with your preferred Claude model IDs before use.
| Tool | Purpose |
|---|---|
deep_research | Full multi-source research on a topic |
quick_search | Fast single-source lookup |
write_report | Generate structured report from research |
get_research_sources | List sources used in research |
get_research_context | Retrieve accumulated research context |
/researcher — quick single-pass web researchgptr-mcp), early-stage