Research Skill

Three modes. Select by request signal:

Signal	Mode
Formal research, investigation, sourced report, gather evidence	Research Pipeline
Fact check, verify claims, check facts, is this accurate, verify quote	Fact-Check
Why did you, explain routing, show trace, decision log, why that agent	Explanation Traces

Default: Research Pipeline.

Final report. When the final report synthesizes two or more dispatched agents' findings, run one self-review pass on the draft before delivery: skills/shared-patterns/report-self-review.md (separate dispatch, model: opus). It applies to Mode A and Mode B.

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Mode A: Research Pipeline

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Mode B: Fact-Check

Verify every factual claim in a draft before publish. Burden of proof sits on the claim, not the checker. Works standalone or as a pre-publish gate. Non-blocking: the report warns; the caller decides whether to publish.

Phase 1: EXTRACT

List every checkable claim: statistics, prices, dates, quotes, attributions, titles, event facts, rankings, causal assertions. Opinions and speculation stay out.

For each claim, record: ID, verbatim text, type (stat/quote/attribution/event/title/price/causal), location. Extract quotes verbatim for exact-words comparison.

Gate: Every checkable assertion has a claim ID. Sweep the document twice.

Phase 2: VERIFY

Work claim by claim.

1. Check provided sources first. Search caller-supplied documents before external sources. Record exact passages.
2. Read laterally. Judge a source by what other sources say about it, not by its own presentation.
3. Climb the source tier. Follow citations upward: primary (study, filing, transcript) > direct secondary (interviews, primary reading) > derived (aggregators, rewrites). A broken citation chain caps the claim at Unverifiable.
4. Triangulate contested claims. Two independent sources (separate origins, not wire rewrites). One source suffices for routine facts from a primary document.
5. Verify quotes on three axes. All must hold: exact words match, attributed speaker confirmed, original context supports the meaning used.
6. Check staleness. Time-sensitive claims expire. Prices/rates: 1 day-1 week. Counts: 1-3 months. Titles/roles: 3-6 months. Event status: until event date. Surveys: 6-12 months. Science: 1-3 years. Laws: 6-12 months. Records/superlatives: re-check every use. Stable history: none.

Gate: Every claim has an evidence record.

Phase 3: ADJUDICATE

Assign each claim one label:

Label	Assign when
Verified	Evidence supports; current within staleness window; sufficient source tier
Disputed	Evidence contradicts; newer source supersedes; quote fails any axis
Unverifiable	Sources engage the claim but settle nothing
Missing-source	No available source addresses it

Rules: contradiction beats support. Partial verification gets the weakest label. Stale figure superseded by newer = Disputed; merely old with no newer figure = Unverifiable.

Gate: Every claim carries one label and a one-line justification.

Phase 4: REPORT

# Fact-Check Report: [document]
## Summary
Claims: N | Verified: n | Disputed: n | Unverifiable: n | Missing-source: n
Unchecked: n (reason)
## Per-Claim Findings
### C1 -- [label]
Claim: [text] | Evidence: [source + passage] | Reasoning: [why this label]
## Warnings
[Every Disputed/Missing-source claim with correction]
## Publish Recommendation
[Hold / fix-then-publish / clear]

Every time-sensitive Verified claim carries its as-of date.

Gate: Report covers every claim ID. Warnings lists every Disputed and Missing-source finding.

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Mode C: Explanation Traces

Read the per-dispatch route event log and present routing decisions as a human-readable timeline. Answer "why did I get routed here?" from recorded events only -- never from reconstruction or rationalization.

Log path: ${CLAUDE_LEARNING_DIR:-$HOME/.claude/learning}/route-events.jsonl (append-only JSONL).

Phase 1: LOCATE

LOG="${CLAUDE_LEARNING_DIR:-$HOME/.claude/learning}/route-events.jsonl"
wc -l "$LOG"

If absent or empty, report the path and the producing hook (hooks/routing-decision-recorder.py). Do not reconstruct from memory.

Phase 2: PARSE

Parse each JSON line. Two event types: DECISION (one per /do-routed dispatch) and OUTCOME (one per finalized dispatch). See references/trace-schema.md for full field semantics.

Filter to the user's query:

User signal	Filter
Names an agent or skill	DECISION/OUTCOME events matching that name
"Why routed here" / latest	Most recent DECISION, current session first
Outcome question	OUTCOME events, joined to decisions
No specific target	Chronological timeline, most recent session

Join OUTCOME to DECISION on same session AND key == "{agent}:{skill}". File adjacency is unreliable.

Phase 3: PRESENT

Sort by ts. For each decision, show: time, agent+skill, complexity, request snippet, health at decision (three states: numeric, no-weight-row, legacy), alternates, outcome.

Lead with the answer to the user's specific question, then offer surrounding context. Flag gaps honestly: pre-instrumentation entries, unmatched outcomes.

request_snippet is private session data: show to the session's user, keep out of PR bodies, issues, exports.

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Deep References

Signal	Reference	Content
Event field schema, health states, join rules	references/trace-schema.md	DECISION/OUTCOME field semantics
Diagnosing thin trace data, consumer mistakes	references/preferred-patterns.md	Failure mode catalog for log reading
Parse/read errors, missing log, unmatched outcomes	references/error-handling.md	Error-fix mappings for trace reading