Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add w95/awesome-claude-corporate-skills --skill incident-postmortemgit clone --depth 1 https://github.com/w95/awesome-claude-corporate-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/w95/awesome-claude-corporate-skills/incident-postmortem)<a href="https://agentmods.dev/skills/w95/awesome-claude-corporate-skills/incident-postmortem"><img src="https://agentmods.dev/badge/skills/w95/awesome-claude-corporate-skills/incident-postmortem/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/w95/awesome-claude-corporate-skills/incident-postmortem"><img src="https://agentmods.dev/badge/skills/w95/awesome-claude-corporate-skills/incident-postmortem.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00027 | $0.02396 |
| Opus 5 | $0.00014 | $0.01198 |
| Sonnet 5 | $0.00005 | $0.00479 |
| Haiku 4.5 | $0.00003 | $0.00240 |
Grade A, and why
incident-postmortem scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 288 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Incident Postmortem Builder
Overview
Create blameless incident postmortems that transform operational disruptions into learning opportunities. These documents focus on system failures and process gaps, not individual blame, enabling continuous improvement and preventing recurrence.
Core Principles
- Blameless: Focus on systems, not people. "Why did this happen?" not "Who screwed up?"
- Psychological Safety: Team members must feel safe discussing root causes without fear
- Data-Driven: Base findings on logs, metrics, and facts; not assumptions
- Action-Oriented: Every finding leads to actionable improvements
- Learning Culture: Treat incidents as valuable learning events, not failures
- Transparency: Share findings broadly; communicate changes to prevent similar incidents
Timeline Reconstruction
Create a detailed chronology of events:
Time (UTC) | Who | What | Evidence | Context
-----------|-----|------|----------|----------
2024-02-15 14:32 | Jenkins | Deploy v2.1.3 (buggy) | Logs | Automated Friday deploy
14:35 | Customer | Website errors | CloudFront | 500 errors reported
14:37 | On-call | PagerDuty alert | Alert | Error rate exceeded threshold
14:42 | Eng team | Investigation starts | Slack #incidents | Identified deploy cause
14:55 | Lead | Rollback initiated | Logs | Reverted to v2.1.2
15:02 | On-call | Error rate normal | Metrics | Customers back to normal
15:30 | Team | Root cause meeting | Notes | Identified root cause
Timeline Template:
- T+0 (Alert): When first detected
- T+X (Detection): When incident was recognized
- T+Y (Communication): When stakeholders notified
- T+Z (Mitigation): When incident owner took action
- T+N (Resolution): When system returned to normal
- Duration: Total time from detection to resolution
Root Cause Analysis (5 Whys)
Go beyond the obvious cause to find systemic issues:
Incident: Website down for 28 minutes
Why 1: Why did website go down?
Answer: Deployment v2.1.3 contained a bug causing infinite loop in auth service
Why 2: Why did the bug reach production?
Answer: Code review missed the issue; test suite didn't catch it
Why 3: Why didn't test suite catch the infinite loop?
Answer: Load/stress tests only run occasionally; not part of standard CI pipeline
Why 4: Why aren't load tests mandatory in CI?
Answer: Historically slow; team prioritized speed over reliability
Why 5: Why does team optimize for deploy speed over testing?
Answer: Pressure to ship features fast; no documented standard for testing rigor
ROOT CAUSE: Process gap - no mandatory load testing in CI; pressure to ship
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 288 lines · 27 tokens per session scan A 2aeff0b2bd7a
incident-postmortem is a skill published in the GitHub repository w95/awesome-claude-corporate-skills (198 stars, last pushed 6mo ago), licensed MIT. It adds 27 tokens to every session and 2,396 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
debug
Systematic debugging via logs, health checks, hypothesis-driven investigation. Triggers: debug, error, trace root cause, fix bug, reproduce symptom, investigation.
introspect
Agent self-debugging and recovery. Use when stuck in loops, making repeated errors, or quality degrades. Triggers: introspect, self-debug, stuck, loop, why failing.
git-mastery
Advanced Git: rebase, bisect, reflog, cherry-pick, worktrees, LFS. Triggers: rebase, bisect, cherry-pick, reflog, force push, merge conflict, worktree.
performance-profiling
Performance: golden signals, p50/p95/p99, flame graphs, load testing. Triggers: performance, slow, latency, p99, flame graph, bottleneck, memory leak.
predict
Analyzes diffs for regression risk and blast radius, generates risk-scored impact report. Triggers: PR review, code change risk, breaking change, blast radius, regression check.
qa-session
Interactive QA: user reports bugs conversationally, agent files GitHub issues. Triggers: QA session, report bug, file issue, conversational QA, bug intake.