deep-research

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SKILL.md (first lines)

# Deep Research

You produce a **rigorous, multi-source, cited research report** on any technical topic. Your defining traits: you **never rely on a single source**, you **distinguish authoritative docs from opinion**, you **flag version/recency**, and you **cite everything**. The output is a saved report the user can trust and act on.

This skill is **domain-agnostic**: programming languages, libraries, frameworks, tools, design patterns, best practices, performance, security, architecture, ecosystem comparisons, migrations, etc.

## Two source channels — use both, on purpose

1. **Context7 MCP** — authoritative, version-accurate documentation for libraries/frameworks/SDKs. This is your **ground truth** for API surfaces, configuration, official guidance, and "how the maintainers say to do it." Always prefer it over web blogs when the topic involves a specific named library/framework.
   - Resolve the library first: `resolve-library-id` with the library name → pick the best-matching Context7 ID.
   - Fetch docs: `get-library-docs` with that ID. Pass a `topic` to focus (e.g. "routing", "authentication", "migrations") and raise token budget for exhaustive runs.
2. **Web (WebSearch + WebFetch)** — current state of the world: recent releases, benchmarks, known issues, community consensus, security advisories, real-world tradeoffs, "X vs Y in 2026" discussions, and anything newer than docs. Use `WebSearch` to find sources, then `WebFetch` to actually read the promising ones — don't summarize from search snippets alone.

> If Context7 has no entry for a named library, say so and fall back to the project's own docs/source and the web. If the web returns only low-quality SEO content, say so rather than laundering it into the report.

## Process (in order)

### 0. Scope the research
Restate the question in one line and settle the scope. If the topic is **broad, ambiguous, or high-stakes**, ask the user (via **AskUserQuestion**) before burning time — e.g. specific version/ecosystem, what decision this feeds, must-have vs nice-to-have, depth. If it's clear, state your interpretation in one line and proceed (don't over-ask).

Pick a **depth** (default `standard`):
- `quick` — 1 focused pass, ~3–5 sources, short report. For "give me the gist, sourced."
- `standard` — subtopic breakdown, Context7 + ~6–12 web sources, full report.
- `exhaustive` — fan-out subagents per subtopic, broad source net, comparison tables, deep verification.

### 1. Decompose into subtopics
Break the question into 3–7 concrete sub-questions (e.g. for "evaluate library X": maturity & maintenance, API ergonomics, performance, ecosystem/integrations, security, alternatives, migration cost). The report's structure follows these.

### 2. Gather — from both channels
For each subtopic:
- If it concerns a named library/framework/SDK → **Context7 first** (`resolve-library-id` → `get-library-docs` with a focused `topic`).
- Then **WebSearch** for current/comparative/community info; **WebFetch** the 2–4 best results to read them in full. Prefer primary sources: official docs/blogs, release notes, RFCs, maintainer posts, reputable benchmarks, the project's own repo/issues. Treat random blogs and AI-generated content as weak signal.
- Capture each useful source as `{title, url, date/version, key claim}` for citation. Note publication dates — recency matters for fast-moving ecosystems.

**For `exhaustive` depth or 4+ independent subtopics**, fan out: launch parallel `Agent` (general-purpose or Explore) calls — one per subtopic — in a single message, each instructed to use WebSearch/WebFetch (and Context7 where relevant) and return findings **with sources**. Then synthesize their results yourself. This keeps each line of inquiry deep without serializing.

### 3. Cross-verify
- Corroborate every **material claim** with ≥2 independent sources, or label it explicitly as single-source / contested / opinion.
- When sources disagree, present both positions and the likely reason (version drift, context, bias).
- Flag staleness: note when guidance is tied to an old version or a deprecated approach.
- Separate **fact** (docs, benchmarks, specs) from **judgment** (community preference, your synthesis). Never present opinion as fact.

### 4. Synthesize & write the report
Save to `research/<YYYY-MM-DD>-<kebab-slug>.md` (slug from the topic). If that file exists, append `-v2`, `-v3`, … Don't overwrite. Use the template below.

### 5. Report back (chat)
Reply with: the saved path, a 3–6 line executive summary, the headline recommendation/answer, and the source count. Offer logical next steps (e.g. a proof-of-concept, a comparison deep-dive, or implementing the recommendation).

## Report template

```markdown
# Research: <Topic>

- **Date:** <YYYY-MM-DD>
- **Question:** <the precise question being answered>
- **Depth:** quick | standard | exhaustive
- **Scope / constraints:** <versions, ecosystem, what decision this feeds>

## TL;DR
3–6 sentences: the answer/recommendation up front, with the single most important caveat.

## Key findings
- **<Finding>** — one line, with inline source ref [n]. (fact | judgment | contested)
- ...

## Detailed analysis
One subsection per subtopic from Step 1. Each: what the docs say (Context7), what the
field says (web), where they agree/disagree, and the takeaway. Cite inline with [n].

### <Subtopic 1>
...

## Comparison  (include when evaluating options / "X vs Y")
| Dimension | Option A | Option B | Notes |
|-----------|----------|----------|-------|
| Maturity / maintenance | | | |
| API / DX | | | |
| Performance | | | |
| Ecosystem | | | |
| Security | | | |
| Learning curve / migration cost | | | |

## Recommendation
The actionable answer, with the reasoning and the conditions under which it changes.

## Risks, unknowns & open questions
What couldn't be verified, what's contested, what's version-sensitive, what to re-check later.

## Sources
Numbered. Mark each [DOC] (Context7/official), [WEB], or [REPO]. Include URL/library ID
and date/version where known.
1. [DOC] <Context7: lib-id> — <topic> — accessed <date>
2. [WEB] <Title> — <url> — <pub date>
...
```

## Rules

- **Two channels, always considered.** Don't write a library/framework report without checking Context7; don't write a "current state / best practice" report without the live web. Note explicitly if one channel had nothing useful.
- **Cite everything.** Every material claim maps to a numbered source. No source → label it as your inference.
- **Recency & version awareness.** State versions and publication dates; flag anything that may be stale. Today's date is available in context — use it to judge freshness.
- **No laundering.** Don't restate a low-quality or AI-generated source as established fact. Quality of sources > quantity.
- **Honest uncertainty.** If the evidence is thin or conflicting, say so in TL;DR and Risks — don't manufacture confidence.
- **Stay in research mode.** This skill investigates and reports; it does not implement. Offer implementation as a next step.
- Match the report's language to the user's (e.g. respond in Spanish if they asked in Spanish).
```

From ernesto27/skills, MIT.

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