sanitize-check

Sanitize Check (Govern)

Purpose

The sanitisation determination is the work: direct identifiers, personal data, commercial figures, licensed material, aggregation risk and confidence floor decide whether an item is held or becomes a release candidate for human review.

When to use

After lesson-cluster and before knowledge-record on every closeout harvest; also whenever a user asks "can we share this externally?" or "is this safe to reuse?".

When NOT to Use

• Raw sources need assembly - use artifact-assemble.
• Assets need reuse scoring or completeness checks - use asset-identify.
• Decisions and retrospective evidence need clustering - use lesson-cluster.
• The user asks for final prose, a handoff or publication - use knowledge-record for a draft only after Govern.

Inputs

lessons_clustered.json containing scored assets, lesson clusters, retrospective inputs and confidentiality terms.

Steps

1. Run scripts/sanitize_check.py --input lessons_clustered.json --out governed.json.
2. Quote sanitisation_report.findings[] verbatim, especially HOLD decisions.
3. Lead with embedded-instruction and aggregation-risk holds; individually safe facts can combine into a client-identification incident.
4. Pass only released_assets[] and rewritten lesson guidance to knowledge-record; held content stays named in the report but out of the reusable record body.
5. If the engine exits non-zero (exit 2 prints sanitize_check: input error: ...; nothing written, including when an upstream output was edited), stop and report the error; never recreate or edit its verdict.

Tools

Run scripts/sanitize_check.py with the shell tool and read governed.json with the file-read tool. Never call email, Teams, SharePoint-write, publishing or knowledge-base actions.

Output

governed.json with sanitisation_report, released_assets, held_assets, governed lesson guidance and a stable knowledge_record object that contains no raw summary seeds. The engine copies every input key forward and adds (one item per array shown):