Analyze ICR receipts for patterns and insights
Analyze your receipt history to identify patterns, risks, and recommendations. Use it after sessions to review decision distribution, severity levels, and confidence statistics.
/plugin marketplace add az9713/icr/plugin install az9713-icr@az9713/icrPerform deep analysis of receipt history to identify patterns, risks, and recommendations.
/icr:audit - Audit current session/icr:audit session - Same as above/icr:audit 2026-01-01:2026-01-02 - Audit date range/icr:audit all - Audit all receiptsHow actions were routed:
Breakdown of action risk levels:
Based on the patterns found:
ICR Audit Report
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Period: 2026-01-02 (1 session, 47 receipts)
DECISION DISTRIBUTION:
Auto-approved: 32 (68%) ####################..........
AI reviewed: 8 (17%) #####.........................
Human reviewed: 5 (11%) ###...........................
Blocked: 2 (4%) #.............................
SEVERITY DISTRIBUTION:
LOW: 25 (53%) ################..............
MEDIUM: 15 (32%) ##########....................
HIGH: 5 (11%) ###...........................
CRITICAL: 2 (4%) #.............................
CONFIDENCE ANALYSIS:
Average: 0.74
Min: 0.42 (receipt #023, Bash "rm -rf ...")
Max: 0.95 (receipt #001, Write "config.json")
PATTERNS OF INTEREST:
3 bypasses logged (receipts #012, #034, #041)
2 blocks after AI review flagged concerns
Historical pattern match rate: 78%
RECOMMENDATIONS:
- Consider adding user rule for "rm" commands (2 CRITICAL reviews)
- Trust mode was used 0% of time; consider enabling for routine work
- Average user response time: 2.3s (healthy)
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