Research
Structured multi-source research protocol with data freshness validation — use when gathering factual data from the web, GitHub, npm, or docs to produce sourced, timestamped, cross-referenced findingsFrom its SKILL.md
npx -y skills add TheWatcher01/skills --skill researchAssembled 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
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Research Skill — chainskills
Protocol
Step 1 — Clarify scope
Define the research questions before searching. Map each question to a decision it informs.
Step 2 — Memory check
Query conversation history for prior research on overlapping topics. Reuse FRESH findings (< 90 days). Skip Step 4 for already-verified facts.
Step 3 — Workspace scan
Read: package.json deps, ROADMAP, AGENTS.md, relevant source files, existing templates. Note current state before looking externally.
Step 4 — External research (parallel where possible)
For each question, query >=2 independent sources from the authority hierarchy:
- Official registry (npm, crates.io, PyPI)
- Official docs / spec / RFC
- Official GitHub repo (README, releases, CHANGELOG)
- Verified community resource (MDN, caniuse, awesome-*)
- Tech blog / article
- Forum / StackOverflow
AI memory alone is never sufficient — always fetch from sources 1-4.
Step 5 — Cross-reference
For critical facts (versions, breaking changes, security), verify with >=2 independent sources.
Flag discrepancies: DISCREPANCY: source A says X, source B says Y.
Step 6 — Freshness stamp
Assign a status to every external claim:
- FRESH — retrieved < 90 days ago
- AGING — 90 days to 1 year
- STALE — 1 to 2 years
- EXPIRED — > 2 years
- UNVERIFIED — not fetched, AI memory only
Step 7 — Structured output
Produce a report with:
- Source table (claim / source / URL / date / freshness / confidence H|M|L)
- Dependency audit table (package / pinned / latest / gap / advisory)
- Workspace vs external delta (what the codebase assumes vs what is actually true)
- Stale/unverified warnings
- Recommended next steps
Anti-patterns
- Do not cite a URL without accessing it — always fetch
- Do not treat AI training data as a source — always verify
- Do not draw single-source conclusions for critical decisions
- Do not omit retrieval dates
- Do not start external research before checking workspace state
Output template
### Research Report — {topic} — {YYYY-MM-DD}
#### Workspace Findings
{What the codebase already knows/does about this topic}
#### External Findings
| Claim | Source | URL | Date | Freshness | Confidence |
|-------|--------|-----|------|-----------|------------|
#### Dependency Audit
| Package | Pinned | Latest | Gap | Advisory |
#### Stale / Unverified
{Items to re-verify before acting}
#### Recommended Next Steps
{Handoff-ready actions}
What ships with it
Read from the repository
Just SKILL.md. No reference files, no scripts.