adr-writer
Use when capturing an architecture decision so it survives turnover — produces an ADR-NNNN.md from context, options considered,…
Use after an incident is resolved — drafts a blameless postmortem from timeline notes, alerts, and chat threads.
$ npx -y skills add oxbshw/LLM-Agents-Ecosystem-Handbook --skill incident-postmortem --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/incident-postmortemContext preview
The summary Claude sees to decide when to auto-load this skill.
Use after an incident is resolved — drafts a blameless postmortem from timeline notes, alerts, and chat threads.
name: incident-postmortem description: Use after an incident is resolved — drafts a blameless postmortem from timeline notes, alerts, and chat threads. version: 0.1.0 status: experimental risk: low tags: [ops, writes-files]
| Name | Type | Required | Notes | |---|---|---|---| | `timeline` | text or paths | yes | Source notes, alert links, chat extracts | | `severity` | `S0`–`S3` | yes | Severity at peak | | `incident_id` | string | yes | e.g. `INC-2026-04-12-001` |
`postmortem.md` with: Summary, Impact, Timeline, Direct cause, Contributing factors, What went well, What didn't, Action items.
1. Reconstruct the timeline (UTC), one row per notable event 2. State **impact** in user-facing terms (requests failed, dollars lost, customers affected) 3. Identify the **direct cause** in one sentence — what specifically broke 4. List **contributing factors** (the conditions that made the incident possible / hard to mitigate) 5. Separate **what went well** (genuine wins, not platitudes) and **what didn't** 6. Owners + dates on every action item; hard fail if missing 7. Tone: blameless. Describe systems failing, not people.
A practical operating manual for building, evaluating, securing, and shipping modern LLM agent systems. Modern agents are not "a prompt + a tool."
Use when capturing an architecture decision so it survives turnover — produces an ADR-NNNN.md from context, options considered,…
Use when reviewing a proposed REST or GraphQL API change before merge — checks contract clarity, backwards compatibility, errors,…
Use when first encountering a new dataset — produces a structured profile (schema, missingness, distributions, outliers, gotchas)…
Use when opening a PR — produces a clean PR description (what / why / how to verify / risks) from a branch diff against base.
Use when planning the next sprint — turns ticket intake + team capacity into a planned sprint with explicit non-goals.
Use after a session to promote useful episodic notes from logs/episodic/ into distilled, dated entries in MEMORY.md and…