Reconstruct pipeline incident timelines and detect anomalies from trajectory data.
npx skills add https://github.com/paulingham/.claude --skill forensics-paulingham
Please help me install this Agent Skill. Skill: forensics Source: https://github.com/paulingham/.claude/tree/main/skills/forensics Command: npx skills add https://github.com/paulingham/.claude --skill forensics-paulingham
Post-incident investigations of pipeline runs are often manual, fragmented, and time-consuming. This Skill reconstructs timelines from trajectory data, detects anomalies, verifies artifact integrity, and produces structured findings to accelerate root cause analysis.
Provide a post-incident dataset (trajectory.jsonl and pipeline.md) in the task state and run forensics to generate a findings report.
High-intent search queries and answers about installing and using this skill.
Post-incident pipeline analysis works by reconstructing event timelines from trajectory data and cross-checking artifact integrity against git history. This structured approach accelerates root cause analysis for complex pipelines where the failure point is unclear.
Post-incident pipeline analysis works by reconstructing event timelines from trajectory data and cross-checking artifact integrity against git history. This structured approach accelerates root cause analysis for complex pipelines where the failure point is unclear.
Post-incident pipeline analysis works by reconstructing event timelines from trajectory data and cross-checking artifact integrity against git history. This structured approach accelerates root cause analysis for complex pipelines where the failure point is unclear.
Post-incident pipeline analysis works by reconstructing event timelines from trajectory data and cross-checking artifact integrity against git history. This structured approach accelerates root cause analysis for complex pipelines where the failure point is unclear.
Post-incident pipeline analysis works by reconstructing event timelines from trajectory data and cross-checking artifact integrity against git history. This structured approach accelerates root cause analysis for complex pipelines where the failure point is unclear.
ChegginLog agent actions as structured JSON using the ATIF schema.
imMamdouhaboammarCoordinate production incident response with severity classification and blameless post-mortems.
artk0deAnalyze TeaRAGs pipeline debug logs to detect performance bottlenecks and timing anomalies.
MissTullyMonitor live apps via periodic screenshots and baseline comparisons.
