Distill failures into principles and preflight checks from logs or diffs.
npx skills add https://github.com/isymchych/accel-os --skill postmortem-isymchych
Please help me install this Agent Skill. Skill: postmortem Source: https://github.com/isymchych/accel-os/tree/main/ai/codex/skills/postmortem Command: npx skills add https://github.com/isymchych/accel-os --skill postmortem-isymchych
Distill a failure into a reusable principle and a preflight check to prevent recurrence and guide future work.
Input the event, failure, and intent, then generate a generalized finding, a prescriptive rule, and a concrete preflight check.
High-intent search queries and answers about installing and using this skill.
To write a preventive incident postmortem, you distill a failure into a reusable principle and a preflight check. This process converts incident details from logs or diffs into a mistaken assumption, correct principle, generalized finding, general rule, and preflight check to guide future work.
Turning command history into lessons learned involves extracting details from logs, diffs, or command history to form a generalized finding and a prescriptive rule. This creates a structured learning document and generates a concrete preflight check to prevent similar wasted effort.
Yes, you can generate guardrails for an existing failure analysis by applying this process to postmortems. It produces a generic lesson and a one-sentence preflight check that serves as error-prevention documentation for similar tasks.
Postmortem analysis works for both code changes and wasted engineering effort. By analyzing the event, failure, and intent, it generates a generalized finding and a prescriptive rule that applies to regressions, code changes, and wasted effort alike.
You create error-prevention guidelines from a root-cause analysis by distilling the failure into a correct principle and a preflight check. This output can be directly leveraged to create AGENTS.md and error-prevention guidelines for teams.
mediar-aiGenerate structured GitHub issues for Terminator failures with logs and reproduction steps.
dongzhuoyaoEnforce explicit errors and preflight validation in ML training pipelines.
openeuler-mirrorCorrelate logs, trace spans, and dependency graphs to output structured JSON root cause reports.
JhabbigDraft blameless incident postmortems with root cause analysis and action items.
