deep-research

/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 ~/code/makerskills/skills/deep-research/references/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

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

Also append a one-line entry to references/research-archive/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.