Research Skill
Description
Research a topic using web search and specialist agents. Results are synthesized by AI and stored for future reference.
Installation
This entry records only its repository, not the path inside it, so there is no
exact command to give. Open the source below and copy the folder into
~/.claude/skills/, or the file into ~/.claude/agents/.
Repository README
This is the README for bigph00t/claude-research-team, shared by 4 entries
in this directory. It describes the repository, not this entry specifically.
description: "Research a topic using autonomous web search and AI synthesis" argument-hint: " [--depth quick|medium|deep]"
Research Skill
Research a topic using web search and specialist agents. Results are synthesized by AI and stored for future reference.
Arguments
The query to research, optionally followed by depth:
--depth quick- Fast lookup (~10s) for simple facts--depth medium- Standard research (~30s) for how-to questions (default)--depth deep- Comprehensive analysis (~60s) for comparisons
How to Execute
- Parse the query from: $ARGUMENTS
- Extract depth if specified (default: medium)
- Call the research service API:
curl -X POST http://localhost:3200/api/research \
-H "Content-Type: application/json" \
-d '{"query": "", "depth": "", "trigger": "manual"}'
- Poll for results at:
GET http://localhost:3200/api/research/ - Present the findings to the user
Alternative: Direct Execution
For immediate results without polling, use the execute endpoint:
curl -X POST http://localhost:3200/api/research/execute \
-H "Content-Type: application/json" \
-d '{"query": "", "depth": ""}'
This returns results directly (blocks until complete). Timeouts: quick=90s, medium=180s, deep=300s.
Examples
/research What is HTMX- Quick fact lookup/research How to implement rate limiting in FastAPI- Medium depth how-to/research Rust vs Go for CLI tools --depth deep- Deep comparison
Service Status
If the service isn't running, inform the user to start it:
cd /home/bigphoot/Desktop/Projects/claude-research-team && npm run start
Dashboard available at: http://localhost:3200
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