Crawl AI policy outputs and triage drift against approved commitments.
npx skills add https://github.com/gtgspot/clegal --skill policy-monitor-gtgspot
Please help me install this Agent Skill. Skill: policy-monitor Source: https://github.com/gtgspot/clegal/tree/main/ai-governance-legal/skills/policy-monitor Command: npx skills add https://github.com/gtgspot/clegal --skill policy-monitor-gtgspot
This skill helps legal and compliance teams detect when AI policies, practices, and use cases drift away from approved commitments, enabling timely updates and governance.
Run policy-monitor to perform a weekly sweep of outputs and report any policy gaps.
High-intent search queries and answers about installing and using this skill.
AI policy drift is detected by crawling output artifacts and triaging results against approved use cases to keep AI governance aligned with current commitments. This process flags gaps in use-case coverage, vendor data terms, and disclosure requirements automatically.
AI policy drift occurs when deployed AI practices and use cases diverge from approved legal commitments. You should monitor for compliance gaps during weekly sweeps, direct policy queries, or when assessing new vendor reviews and internal documentation updates.
To check if a proposed AI use case is covered, run a direct query against your approved use case registry. The system provides registry guidance and flags coverage gaps, generating suggested language for any missing policy commitments.
Yes, monitoring AI governance compliance requires a configured CLAUDE policy file, an outputs folder with artifacts, and a registry of approved use cases. These elements are diffed against each other to identify policy gaps and vendor review issues.
Yes, you can automate weekly compliance sweeps to crawl the AI policy outputs folder and compare artifacts against current policy commitments. This automated triage flags gaps in vendor data terms and disclosure requirements.
The best way to flag gaps in AI use-case coverage and disclosure requirements is to diff output artifacts against a registry of approved use cases. This drift detection mechanism generates suggested language to resolve policy gaps.
uk-agentsDetects UK AI policy drift and drafts REQUIRED or ADVISABLE updates for review.
ZekaiSuniDetect AI policy drift by comparing saved AIAs, triage outcomes, and vendor reviews.
foundry-worksIdentify implementation deviations from specifications using LSP and MCP fidelity analysis.
Bossmann007Compare AI practices against policy commitments and use case registry.
