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Research brief

Skill Evan-Daruwalla/claude-skill-suite/research-brief

Deep research on a technical or market topic producing a structured, sourced brief saved to the project's docs. Use when the user says "research X", "deep dive into X", "do research into X and propose candidates", or asks for analysis of an architecture, paper, strategy, or market event. Not for quick factual questions.From its SKILL.md

Install
npx -y skills add Evan-Daruwalla/claude-skill-suite --skill research-brief

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

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SKILL.md

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Research Brief

Structured deep research with sources, skepticism, and a saved artifact — instead of a one-off chat answer that evaporates. Runs a 10-stage research process adapted for desk research: an LLM can search, read, and analyze; it cannot run surveys or interviews — stages needing new field data are scoped honestly as limitations, never simulated.

Trigger

/research-brief <topic>, or the user says "research X", "deep dive into X", "analyze what happened [in the market / to this stock]", "propose top N candidates for X".

Inputs

  • Topic, plus any constraints (time budget, number of candidates, decision it feeds into).
  • Where to save: default docs/research/<date>_<slug>.md in the current project; if no docs/ exists, ask.

The 10 stages

1. Identify the problem. One sentence: what question is this brief answering, and what practical problem makes it worth answering? If the topic is a proposal the user wrote, analyze it from multiple genuinely different angles (optimistic, pessimistic, different approach directions) — no yes-man convergence.

2. Survey existing work. Before forming any view, check what already exists: prior project docs/briefs, published papers and peer-reviewed literature, authoritative primary docs. The gap between what's already answered and what isn't IS the research problem — restate stage 1 if the survey shifts it.

3. State hypotheses. Write the expected answer as a falsifiable working hypothesis, plus at least one rival (or null) hypothesis. Do this BEFORE deep collection — it is the anti-confirmation-bias gate: you now know in advance what evidence would count against you.

4. Design the research. Plan before collecting: which source types (primary — papers, filings, official docs, datasets — vs. secondary commentary), what analysis (comparison table, quantitative check, timeline), and what evidence would confirm or refute each stage-3 hypothesis.

5. Name the audience. Who reads this brief, and what decision do they make with it? Depth, jargon level, and ranking criteria all follow from this.

6–7. Choose methods, then collect. Web-search wide then deep per the stage-4 design, favoring primary sources over blog rehashes; get actual numbers (prices, dates, magnitudes), not narratives. If the question genuinely requires NEW primary data — a survey, interviews, an experiment — say so: scope it as a limitation naming the method a human would use. Never fabricate respondents, quotes, or results.

8. Analyze. Separate analysis from collection. Any load-bearing claim needs 2+ independent sources or an explicit "single-source, unverified" tag. Test each hypothesis against the evidence; say which survived and which died.

9. Findings. State findings distinct from interpretation. If the ask was "propose top N", rank candidates with a one-line tradeoff each.

10. Report. Write and save the brief:

  • Header — title, absolute date, the question, who it's for (stage 5).
  • TL;DR (3–5 sentences, verdict first — which hypothesis won).
  • Method (2–3 lines: the stage-4 design, source types used, limitations including any primary-data gap from stages 6–7).
  • Findings (organized by theme, each with inline source links).
  • Candidates/options ranked (if asked) with a one-line tradeoff each.
  • What would change this conclusion (untested stage-3 falsifiers, open questions).
  • Sources (full list, dated).

Save to the docs path with today's absolute date, and add one line to the project record if the project keeps one.

Long runs: if research will take >15 minutes, spawn background research agents in parallel by sub-topic (split along stage-4 lines — by hypothesis or theme), then compile when all report in.

Output

  • The saved brief file, plus the TL;DR and ranked candidates inline in chat.

Rules

  • DO NOT MAKE ANYTHING UP. Missing data is reported as missing; unrunnable methods (surveys, interviews, experiments) are reported as limitations, not simulated.
  • Prefer primary sources; date every source (staleness matters).
  • Hypotheses come before deep collection — never retrofit them to findings.
  • Keep the chat response short — the file is the deliverable.

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

Keep looking

Skills are one crate of 326,782. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.