community-automations/research-team

DevOps & Code

PublicClaude subagent

Research Crew

One model researching a broad question gets shallow fast; it cannot read widely and fact-check itself at the same time. This crew splits the job across specialists.

sonnet1 weekCrewAITavilyFirecrawlOpenAI
ClaudeClaude
ROI for
README.md

Why this subagent

One model researching a broad question gets shallow fast; it cannot read widely and fact-check itself at the same time. This crew splits the job across specialists.

A lead agent breaks the question into sub-topics, scrapers gather sources in parallel, and synthesis and verifier agents merge and check the findings. You get a cited research brief where every claim traces back to a source, not a confident guess.

How it runs

    • Read

      Used at step 01 to kick off the pipeline.

    • Write

      Used at step 01 to kick off the pipeline.

    • WebFetch

      Used at step 01 to kick off the pipeline.

    • WebSearch

      Used at step 01 to kick off the pipeline.

Sample output

json
// Sample output
// (generated when the pipeline finishes)

As the lead agent, decompose the research question into sub-topics, dispatch parallel scrapers, then have synthesis and verification agents produce a single brief where every claim carries a source link.

Unlock the rest

The full agent definition, install snippet, and starter task are gated for community members.

Members get the full `.md` agent file, the npm / pnpm install one-liners, a starter prompt that we've tuned against real runs, and the open-source repo when this automation ships there. One email, magic link, done.