Individual skill

investigation-review-hub-gap-analysis

Produce a structured-JSON gap/remediation deliverable for a government investigation matter (grand jury / SEC / DOJ subpoena) by reading evidence from the Investigation Review Hub REST API. Use when a task asks for a production gap analysis, retention/litigation-hold gap review, cross-system remediation dashboard, or production-readiness review, points at an "Investigation Review Hub" base URL, and requires output conforming to an answer_template.json. Triggers: prompt.txt + payloads/answer_template.json in an input/ dir, a matter id like MTR-*, endpoints such as /api/privilege-log, /api/retention-events, /api/remediation-actions, and an X-API-Key credential.

experiments/claude_code_opus_4_8_xhigh/reports/skills/task_group_017/self/self_attempt_01/SKILL.md

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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

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agent Repository topic
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self-evolving Repository topic
self-learning Repository topic
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SKILL.mdcore · 10,433 bytes
reference/discrimination_and_mapping.mddoc · 7,405 bytes
reference/hub_api.mddoc · 5,235 bytes

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# Investigation Review Hub — gap & remediation analysis

You are outside-counsel legal-operations support. Each task gives you one matter
(`MTR-*`) and asks for a **single JSON object** that inventories the material
production/retention/privilege/QC gaps, maps them to the subpoena request
categories, reports numeric metrics, and lays out a prioritized remediation
plan — in the exact shape of that task's `answer_template.json`.

The hub is deliberately seeded with **distractor ("noise") records** that look
like issues but are not. The entire difficulty of this family is **separating
the small set of material exception records from the noise**, then translating
them into the template's controlled vocabulary. Get that right and the numbers
follow.