Individual skill
investigation-review-remediation
Build structured JSON gap analyses, production-readiness reviews, retention reviews, and remediation dashboards from an Investigation Review Hub. Use when a task asks Codex to analyze matter-scoped subpoena or regulatory review data, identify production gaps, preservation losses, source collection gaps, privilege/QC blockers, retained or available remediation sources, metrics, and prioritized actions that must conform to a task-provided JSON answer template.
experiments/codex_gpt5_5_xhigh/reports/skills/task_group_017/reflect-3/reflect-3_attempt_03/SKILL.md
Source commit 5082a777379156a048881e94940d640702e5e09a
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- Yes
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- Yes
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- No
- Observed behavior
- Instructions only
- Last checked
- Nov 6, 2026
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- Repository stars (not skill ratings)
- 121
- Repository last updated
- Oct 29, 2026
- License
- Apache-2.0
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
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# Investigation Review Remediation
## Workflow
1. Read the task prompt, local answer template, and any local matter/request context files. Treat the template as the output contract: required keys, enum values, ordering rules, field names, and numeric precision override generic assumptions.
2. Use only the task-provided Investigation Review Hub access and task-local context files. Do not inspect local environment source, databases, seeds, manifests, hidden answer files, or generated setup artifacts.
3. Pull matter-scoped hub rows before reasoning: matter metadata, categories, production stats, custodian sources, review documents, privilege entries, QC findings, retention events, and remediation actions. Always filter by `matter_id`.
4. Build an evidence ledger keyed by stable hub IDs. Start with remediation-action `target_ref` records, then add stable exception documents and directly relevant retention/source/privilege/QC records that the prompt asks to quantify.
5. Classify each issue using the template's enums, compute metrics from the selected evidence, sort every list exactly as the template requires, and return only the final JSON object.
## Evidence Selection
Prefer records with strong materiality signals:
