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 agentmods add skills/hoavdc/codexkit/codexkit-incident-postmortemnpx skills add hoavdc/CodexKit --skill codexkit-incident-postmortemgit clone --depth 1 https://github.com/hoavdc/CodexKitWhat 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 | $0.00058 | $0.01362 |
| Opus 5 | $0.00029 | $0.00681 |
| Sonnet 5 | $0.00012 | $0.00272 |
| Haiku 4.5 | $0.00006 | $0.00136 |
Grade A, and why
codexkit-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 2d 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 — 159 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Incident Postmortem
When to Use
- After any production incident that affected users
- After near-misses that revealed systemic weaknesses
- When establishing a blameless postmortem culture
- When leadership requests incident RCA (Root Cause Analysis)
Procedure
Step 1 — Incident Summary
Write a 2–3 sentence summary:
- What happened, when, and how long
- Impact in business terms (users affected, revenue lost, SLA breach)
- Current status (resolved, monitoring, partially mitigated)
Severity classification:
| Severity | Criteria |
|---|---|
| SEV-1 | Complete outage or data loss affecting all users |
| SEV-2 | Major feature unavailable or significant degradation |
| SEV-3 | Minor feature impact, workaround available |
| SEV-4 | Cosmetic or non-user-facing issue |
Step 2 — Timeline
Build a minute-by-minute timeline:
| Time (UTC) | Event | Source |
|---|---|---|
| 14:02 | Deploy v2.3.1 to production | CI/CD |
| 14:05 | Error rate spikes to 15% | Datadog |
| 14:08 | PagerDuty alerts on-call engineer | PagerDuty |
| 14:12 | On-call begins investigation | Slack thread |
| 14:25 | Root cause identified: DB migration timeout | Logs |
| 14:30 | Rollback initiated | CI/CD |
| 14:35 | Service fully recovered | Monitoring |
Time to Detect (TTD): 3 min | Time to Resolve (TTR): 33 min
Step 3 — Root Cause Analysis (5 Whys)
- Why did the service fail? → Database queries timed out
- Why did queries time out? → Migration locked a critical table for 8 minutes
- Why was the table locked? → ALTER TABLE ran without
CONCURRENTLYflag - Why wasn't it concurrent? → Migration script didn't follow the safe-migration checklist
- Why wasn't the checklist followed? → No automated check in CI pipeline
Root cause: Missing CI check for safe migration patterns.
Step 4 — Impact Assessment
| Metric | Value |
|---|---|
| Duration | 33 minutes |
| Users affected | ~12,000 (8% of DAU) |
| Requests failed | ~45,000 (500 errors) |
| Revenue impact | ~$2,400 estimated |
| SLA impact | 99.92% (target: 99.95%) — SLA breached |
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 2d ago First seen · 159 lines · 58 tokens per session scan A 27d5968df7cf
codexkit-incident-postmortem is a skill published in the GitHub repository hoavdc/CodexKit (21 stars, last pushed 3mo ago), licensed MIT. It adds 58 tokens to every session and 1,362 once invoked, about $0.0003 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 2026-08-30.
Other skills, from other repositories
reducing-aigc-detection
Systematically reduce AIGC detection rates in academic papers (Chinese/English). Analyzes detection reports, identifies high-impact sections, applies multi-layer rewriting strategies preserving formatting/footnotes, and verifies results. Supports 维普/知网/Turnitin platforms.
architecting-security
安全架构与治理：威胁建模 (STRIDE/PASTA/LINDDUN)、零信任身份架构、IAM/SSO/MFA/PAM、合规框架 (SOC2/PCI/HIPAA/GDPR)、DLP、隐私工程、安全控制设计。Use when designing security architecture, threat modeling new systems, implementing zero-trust identity, designing IAM/SSO/PAM, building compliance evidence chains, or planning privacy-by-design.
defending-applications
Application security defense knowledge for builders. Covers Web/API/GraphQL hardening (XSS/SQLi/SSRF/IDOR/BOLA/Mass Assignment/deserialization/upload/path traversal), authentication/authorization (OAuth 2.0/OIDC/JWT/Session/Cookie/SAML/SSO), and LLM application security (prompt injection, jailbreak, RAG poisoning…
detecting-and-responding
蓝队与紫队工程：检测规则编写、SIEM/EDR 调优、事件响应、数字取证、威胁狩猎、ATT&CK 映射、紫队演练闭环。Use when writing Sigma/YARA detection rules, tuning SIEM noise, responding to security incidents, conducting forensic analysis, hunting threats, or running purple team exercises.
securing-cloud-and-supply-chain
云原生与软件供应链安全防御。容器/K8s 加固、Service Mesh、CI/CD 安全、SLSA/SBOM/Sigstore、云 IAM、Secrets 管理、IaC 安全。Use when hardening Kubernetes clusters, auditing CI/CD pipelines, implementing supply chain security, managing cloud IAM, or reviewing IaC code.
analyzing-changes
Analyzes code changes, detects documentation drift, and evaluates change impact scope. Use when reviewing diffs, checking doc sync, or running pre-commit analysis. Automatically triggered after design-level changes or refactoring.