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Audit AI features for governance guardrails, fallback logic, validation, and human review.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "io.github.nugehs/aiglare" MCP server from askskill: Run: claude mcp add 'io-github-nugehs-aiglare' -- npx -y @nugehs/aiglare
Please audit our customer support AI workflow. Focus on confidence thresholds, low-confidence fallback rules, validation for sensitive answers, and whether human review checkpoints are in place. List risks and recommendations.
An audit report with governance gaps, risk explanations, and improvement recommendations.
Review the governance guardrails in our marketing content generation system. Verify output validation, exception fallback, human approval, and logging mechanisms, then identify missing controls.
A control checklist and issue summary for the content generation workflow.
Assess whether our internal knowledge Q&A bot has sufficient governance controls, including answer confidence display, fallback when it cannot answer, result validation, and human escalation flow.
A compliance assessment summary describing current status, risks, and recommended safeguards.
Add deterministic security checks, host audits, and diagnostics to AI workflows.
Audit AI agent code for pre-deploy security risks missed by generic SAST.
Enforce compliant AI-to-data access with masking, policy controls, and audit trails.
Set AI agent budgets, enforce spend limits, and audit every decision.
Safely let your AI run code, query databases, use LMs, and commit to GitHub.
Audit AI readiness with crawl checks, llms.txt, and structured data tools.