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Process

src/core-skills/bmad-deep-recon/references/process.md

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Process

For a report the user names or drops ("there's a research report at <path>, process it"):

  1. File it. Find or create the run folder: if a drafted brief for this topic exists, that folder is the target; otherwise infer type and topic from the report (confirm in one line), bind {doc_workspace} (expand the folder name with uv run scripts/recon_kit.py slug as in Draft), and init the memlog. Move or copy the original into {doc_workspace}/imports/ untouched — full fidelity is preserved there, and nowhere else.
  2. Record provenance in the memlog: what produced it (which tool or firm), when (ask if not evident — production date drives staleness), and what the user wants decided from it.
  3. Extract. A subagent (fresh context, firewall rules) reads the import and pulls every claim bearing on the decision into digest files under {doc_workspace}/digests/ — standard shape {claim, source, publisher, pub_date, accessed, confidence, class}, keeping the original's citations (the cited source is the publisher; the import is the via). Multiple imports each get their own digest; contradictions between them are findings, not noise.
  4. Check against the pack: which of the type's dimensions the material covers, which are open, where its claims fall inside two-source classes but rest on one publisher. Verification per the resolved validation level (references/verification.md) — at normal this is a spot-check of the load-bearing claims only, minutes not hours.
  5. Distill into research.md per references/synthesis.md — the succinct, cited, decision-first summary with full metadata frontmatter (topic, type, decision, source: provenance, dates, status). This is the artifact downstream skills read; nobody ever reprocesses the import. Open dimensions are listed honestly with a one-line route: draft a follow-up prompt, or a targeted Run on the gap.
  6. Finalize per references/finalize.md.