pattern-detection

pattern-detection is an Observability & incident response skill for AI agents, published by akillness in the jeo-skills repository on GitHub. Skillspace rates pattern-detection D (59/100) and it passed the safety scan; the rating is based on static analysis only.

Route repeated pattern, rule, and anomaly work into one detection packet before suggesting tools or fixes. Use when the user needs reusable scans, suspicious repeated shapes, grouped outlier candidates, or first-pass anomaly triage across code, logs/events, telemetry, and metric tables. Choose one packet: text-prefilter, structural-code-rule, log-event-pattern, or metric-anomaly. Triggers on: repeated bug, suspicious spike, odd cohort, noisy event, code smell family, rule pack, anti-pattern, outlier, anomaly, fraud signal, or recurring issue. Route root-cause incident work to log-analysis, KPI/business explanation to data-analysis, repo tracing to codebase-search, remediation to specialist skills, and alert/incident operations to monitoring-observability.

Grade

D

Quality

59 / 100

Safety

Passed

GitHub stars

37

Unproven: rated by static analysis only, not yet compared head-to-head.

Our two independent classifiers differ on this skill's category, so treat the placement as provisional.

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