Agent skill

deep-research

Quellcode ansehen: coreyhaines31/makerskills

#201Globales Ranking · von 201 SkillsMedium

Installation

npx skills add coreyhaines31/makerskills --skill deep-research

267

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/deep-research — Multi-source research with archive

Plans, executes, and synthesizes research from multiple sources. Archives the output so the corpus compounds.

Step 1 — Frame the question

Restate the research question in one tight sentence. If ambiguous, ask the user:

  • What's the decision this research will inform?
  • What's the minimum useful answer? (Saves over-researching.)
  • Any sources to prioritize or avoid?

Output: **Research question:** <one sentence>

Step 2 — Plan the sources

Pick from this menu based on the question type. Note which sources you'll hit and why.

Source When to use Tool
Web search (Google) Authoritative articles, docs, official statements WebSearch
/last30days What people are actually saying right now — Reddit, X, YouTube, HN, web recency Skill({skill: "last30days", args: "<topic>"})
Specific URLs When the user hands over starting URLs WebFetch
Browsable pages (auth-walled, JS-heavy) Pricing pages, product tours, profiles agent-browser via the compound-engineering:agent-browser skill
Memory Prior research / decisions / context the user already captured grep ~/.claude/memory/
Notion If the topic touches a known Notion workspace Direct Notion API (key in $NOTION_API_KEY, see reference_notion_api.md)
Research archive Prior /deep-research runs that touched this topic grep ${MAKERSKILLS_CONFIG:-$HOME/.config/makerskills}/deep-research/archive/

Run discovery passes in parallel where possible. Sequential only when one source needs another's output (e.g., agent-browser a URL discovered by WebSearch).

Step 3 — Execute discovery

Run each chosen source. For each result, capture:

  • The source (URL or system)
  • 1–3 sentence summary of what was said
  • Date / recency
  • Confidence in the source (high/medium/low)

Don't synthesize yet — just collect.

Step 4 — Synthesize

  1. Group findings by theme or sub-question
  2. Contradiction check — flag anywhere sources disagree. Don't average them; surface the disagreement.
  3. Confidence: high (multiple independent sources agree), medium (one strong source or several weak), low (single anecdote or speculation)
  4. Gaps: what would change the answer? What's NOT in the corpus?

Step 5 — Output the brief

Use this template:

# Research: <question>

**Date:** <YYYY-MM-DD>
**Decision this informs:** <one line>
**Confidence overall:** high / medium / low

## TL;DR
<2–4 sentences with the answer>

## Key findings

### 1. <Finding>
<2–4 sentences>. Sources: [1], [3], [5]

### 2. <Finding>
...

## Contradictions / uncertainty
- <where sources disagree, with each side cited>

## Gaps
- <what's missing from the corpus>
- <what to research next to close the gap>

## Recommended next steps
1. <action>
2. <action>

## Sources
[1] <Title> — <URL or system> (<date>) — <confidence>
[2] ...

Step 6 — Archive

Archives live in ${MAKERSKILLS_CONFIG:-$HOME/.config/makerskills}/deep-research/archive/ (create the directory if missing). Never write archives inside the skill's own folder — skill installs and upgrades re-sync from source and wipe anything saved there. Migration: if this skill's folder contains an old references/research-archive/ with user entries, move those files into the archive directory first.

Write the brief to <archive dir>/<YYYY-MM-DD>-<slug>.md so it's grep-able forever. Slug = kebab-case of the topic.

Also append a one-line entry to <archive dir>/INDEX.md (create if missing):

- 2026-06-15 — [<topic>](./<filename>.md) — <one-line TL;DR>

Step 7 — Surface

After archiving:

  • Show the full brief in chat
  • Tell the user the archive path
  • Offer: "Push to Notion or save to a project's docs?"

Composes with

  • business-brainstorm — calls this skill during the market validation step
  • /domain — when research includes "is the .com available"
  • /last30days — one of the data sources

Notes on quality

  • Always cite. Every claim in the brief needs a source pointer.
  • Recency matters — note dates on each source. For fast-moving topics (AI, startups), de-weight sources >12 months old.
  • Don't trust a single source for high-stakes claims. Re-search until you have at least 2 independent corroborations or surface the uncertainty.
  • No padding. If the answer is one paragraph, return one paragraph. The template is a maximum, not a minimum.

Installationen

Installationen267
Globales Ranking#201 von 201

Sicherheitsprüfung

athMedium
socketSafe
Warnungen: 0Bewertung: 90
snykMedium
WEB DATA FOR AGENTS

Give agents clean web context

Search and extract the public web as Markdown or structured JSON through one API or hosted MCP server.

Explore Webstractor

So verwenden Sie diesen Skill

1

Install deep-research by running npx skills add coreyhaines31/makerskills --skill deep-research in your project directory. Führen Sie den obigen Installationsbefehl in Ihrem Projektverzeichnis aus. Die Skill-Datei wird von GitHub heruntergeladen und in Ihrem Projekt platziert.

2

Keine Konfiguration erforderlich. Ihr KI-Agent (Claude Code, Cursor, Windsurf usw.) erkennt installierte Skills automatisch und nutzt sie als Kontext bei der Code-Generierung.

3

Der Skill verbessert das Verständnis Ihres Agenten für deep-research, und hilft ihm, etablierte Muster zu befolgen, häufige Fehler zu vermeiden und produktionsreifen Code zu erzeugen.

Was Sie erhalten

Skills sind Klartext-Anweisungsdateien — kein ausführbarer Code. Sie kodieren Expertenwissen über Frameworks, Sprachen oder Tools, das Ihr KI-Agent liest, um seine Ausgabe zu verbessern. Das bedeutet null Laufzeit-Overhead, keine Abhängigkeitskonflikte und volle Transparenz: Sie können jede Anweisung vor der Installation lesen und prüfen.

Kompatibilität

Dieser Skill funktioniert mit jedem KI-Coding-Agenten, der das skills.sh-Format unterstützt, einschließlich Claude Code (Anthropic), Cursor, Windsurf, Cline, Aider und anderen Tools, die projektbezogene Kontextdateien lesen. Skills sind auf Transportebene framework-agnostisch — der Inhalt bestimmt, für welche Sprache oder welches Framework er gilt.

Data sourced from the skills.sh registry and GitHub. Install counts and security audits are updated regularly.