deep-research

Deep Research

<skill_contract> Decision-relevant question, audience, scope, recency, source and privacy boundaries, budget, and required deliverable. An answer-first synthesis with source and claim ledgers, citations, contradictions, uncertainty, and durable handoff. Decision-critical claims are traceable and adversarially checked, unresolved gaps are explicit, and the stop rule is met. <non_goals>Link collection, uncited material claims, privacy leakage, exhaustive search, or autonomous high-impact experiments.</non_goals>

Research is an evidence loop, not a volume contest. Define the decision, gather the minimum diverse evidence, maintain source and claim ledgers, attack the synthesis, then stop when additional search no longer changes the answer.

Usage Template

Provide: research question, audience/decision, scope, recency, allowed/excluded sources, privacy boundary, budget, output format, and wiki destination if durable. Load references/research-ledgers.md for ledger schemas.

Workflow

Choose one mode: evidence brief, knowledge curation, recency pulse, domain intelligence, scientific-method audit, or heavy research. Convert the question into 3-7 information requirements, decision criteria, interruption points, and a source-access plan.

<unknowns_gate>

If the decision, recency window, private-data authority, or source boundary materially changes the result, return NEEDS_INPUT. Record known, probeable, testable, and inaccessible unknowns. Do not treat inaccessible sources as supporting evidence.

</unknowns_gate>

1. Run a broad discovery pass; rank sources by authority, directness, recency, independence, and relevance.
2. Prefer primary and official evidence for consequential claims; use secondary sources for context and disagreement discovery.
3. Build a source ledger and claim ledger while reading, not after drafting.
4. Triangulate central claims; record dates and whether sources are independent or repeating one origin.
5. Run a gap-fill pass only for decision-critical unknowns.
6. Draft an answer-first synthesis separating evidence, inference, uncertainty, disagreement, and implications.
7. Run an adversarial pass: strongest counterevidence, alternative mechanism, stale data, selection bias, and missing base rate.
8. For science/AI experiments, specify problem, data/simulator, intervention, objective metric, uncertainty, reproducibility, and human judgment boundary.
9. Produce an activity trace and, when requested, a STOW handoff packet for wiki-ingest rather than writing source claims directly into governed concepts.