Deep Research

1. Identify the deliverable: direct answer, research memo, literature review, project comparison, due diligence, timeline, implementation recommendation, or full cited report. 2. Choose effort based on risk and ambiguity: - quick: 2-4 meaningful hops, 2+ source classes, for low-risk checks. - standard: 5-8 hops, 3+ source classes, for normal research. - deep: 9-14 hops, 4+ source classes, for broad synthesis. - exhaustive: 15+ hops or user-specified budget, 5+ source classes, for hard, contested, or high-stakes research. 3. Initialize a run:

python {baseDir}/scripts/research_ledger.py init \
  --question "" \
  --out-dir research_runs \
  --effort deep \
  --deliverable "evidence-backed research memo"

4. Load research-protocol.md for the workflow and query-playbook.md for search patterns. 5. After each meaningful retrieval, source opening, repo inspection, citation traversal, or verification step, log a hop. After each source contributes a reusable claim, log evidence. 6. Before finalizing, run:

python {baseDir}/scripts/research_ledger.py lint --run-dir 

7. Use report-template.md. Cite evidence IDs such as [E0001] for high-impact claims.