lead-research
Discovery-scale research harness. A cheap scout maps the topic, the Lead designs topic-specific parallel researcher assignments from the scout's map (drawing on a source-class tactics library — academic, repos, production patterns, web, experts), then verifies claims against sources and writes a decision-oriented report. Use when brainstorming a project or feature, choosing a technology, or asked to "research X", "state of the art", "deep research". For narrow slice-level fact checks inside the build loop, /lead handles those inline.
npx skills add tamdogood/builder-essential-skills --skill lead-research --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Lead Research You are the research Lead. Researchers gather; **you** design the decomposition, verify, and write — judgment never delegates. The source-class tactics library (search mechanics + verified endpoints per source class) is in `tactics.md`; read it when you design researcher assignments. Resolve the `researcher` and `scout` models with `python ../lead/config.py` (or the shipped defaults) exactly as the build loop does — repo `.lead/config`, then `~/.lead/config`, then defaults. ## Scale before anything A tool call is one search OR one page fetch. - **Simple fact-find** → answer directly or 1 researcher, 3–10 tool calls. Don't run a harness on a question one search answers. - **Comparison / focused question** → 2–4 researchers on distinct perspectives, 10–15 tool calls each, no scout — you already know the terrain. - **Brainstorm / SOTA survey / technology choice** → scout first, then a designed fan-out of 4–6 researchers, 15–25 tool calls each. ## Procedure ### 1. Scope → brief If the question is ambiguous, ask at most 2–3 clarifying questions, then compress everything into a **research brief**: the question, the decision it informs, constraints, and what "answered" loo
- Scale before anything
- Procedure
- 1. Scope → brief
- 2. Scout, then design the researchers
- 3. Fan out
- 4. Gap round (max 2 extra rounds, usually 1)
- 5. Verify (your work, against raw sources)
- 6. Synthesize (one pass, one author — you)
- 7. Hand off
codex exec --sandbox read-only -c web_search="live" \
What does the lead-research skill do?
Discovery-scale research harness. A cheap scout maps the topic, the Lead designs topic-specific parallel researcher assignments from the scout's map (drawing on a source-class tactics library — academic, repos, production patterns, web, experts), then verifies claims against sources and writes a decision-oriented report. Use when brainstorming a project or feature, choosing a technology, or asked to "research X", "state of the art", "deep research". For narrow slice-level fact checks inside the build loop, /lead handles those inline.
How do I install it?
Run `npx skills add tamdogood/builder-essential-skills --skill lead-research --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From tamdogood/builder-essential-skills, a repository with 90 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.