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Research

Skill rauleburro/skills/skills/research

Conduct focused technical research on a problem before implementation. Use when the user asks to investigate, research, deep-dive, or understand a technical issue (bugs, platform quirks, integration problems). Produces a concise consolidated report plus optional detail docs.From its SKILL.md

Install
npx -y skills add rauleburro/skills --skill research

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

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SKILL.md

2.1 KB, 453 tokens by cl100k_base, as published. Nobody here has run it

Research Skill

Investigate a technical problem efficiently and persist what you learn so the team never re-investigates the same topic twice.

1. Scope the topic

Extract from the user's message (ask only if genuinely unclear):

  • Topic slug: kebab-case folder name, e.g. bluetooth-audio-routing
  • Stack: platform/language/framework
  • Symptom: observed vs expected behavior
  • Known: hypotheses already tried

2. Prepare the workspace

Run scripts/init-research.sh {topic-slug} to create the docs folder.

3. Launch 3 default agents in parallel

Each agent gets a one-line angle plus the shared context. Read reference/agent-prompts.md when you need the exact prompt wording.

  1. Codebase analysis (Explore agent) — find relevant code, gaps, file:line references.
  2. Root-cause theory (web agent) — why it happens at the OS/framework/protocol level.
  3. Solutions & validation (web agent) — native APIs, libraries, community-confirmed fixes.

Spawn the optional 4th/5th agent only if the user explicitly asks for library comparison or cross-platform API deep-dive.

4. Synthesize

Create exactly these two files:

  • docs/{topic}/NOTAS.md — raw findings, snippets, URLs, quick observations.
  • docs/{topic}/RESEARCH_CONSOLIDADO.md — structured master doc.

Use reference/consolidated-template.md only when you need the full template. Optional detail files (03_android_api.md, 04_librerias.md, etc.) are created only when findings justify them.

5. Finalize

Run scripts/finalize-research.sh {topic-slug} to validate the master doc exists and append an iteration row. Then report to the user:

  1. Root cause (with file:line if applicable)
  2. Top 3 non-obvious findings
  3. Files created
  4. Suggested next step

Keep the chat report concise; the detail lives in the docs.

What ships with it: 4 files

4.0 KB alongside SKILL.md, 2 of them executable

scripts/

Keep looking

Skills are one crate of 326,645. 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.