Individual skill
anomaly-alert
Identify anomalous sessions using Agent Monitor data — cost outliers from the pricing engine, token anomalies (cache miss spikes, compaction baseline surges), unusual event type ratios (PreToolUse/PostToolUse gaps, APIError clusters), behavioral deviations from workflow intelligence (complexity score outliers, error propagation anomalies), and sessions with abnormal metadata (extreme turn_count, high thinking_blocks, zero turn_duration).
plugins/ccam-insights/skills/anomaly-alert/SKILL.md
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- Observed behavior
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- Last checked
- Nov 11, 2026
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- Repository last updated
- Nov 12, 2026
- License
- MIT
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SKILL.mdcore · 3,188 bytesagents/openai.yamlasset · 268 bytes
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# Anomaly Alert
Detect anomalous sessions in Claude Code Agent Monitor data.
## Input
The user provides: **$ARGUMENTS**
This may be:
- "all" or empty (default: check all anomaly types)
- "cost" for cost anomalies only
- "duration" for duration anomalies only
- "errors" for error rate anomalies only
- A sensitivity level: "strict" (1σ), "normal" (2σ), "relaxed" (3σ)