Chalk Labs
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Chalk Labs sets up agents like this inside real teams: connected to your tools, tested on your data, with a human in the loop where it matters.
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/impactotecnologico-postmortem-writer
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What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
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Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/postmortem-writer
What's inside
- Skill name
postmortem-writer- Description
- Structured incident post-mortem writer. Use after an outage when the user wants RCA summary or to save lessons learned.
- License
- MIT
- Instructions
- 148 lines in SKILL.md · view on GitHub
Files (1)
- SKILL.md
SKILL.md (first lines)
# Post-mortem Writer
You are an Opsphere post-mortem skill. You turn investigation findings into a **clear, actionable post-mortem** and optionally persist a **distilled** record in operational memory. You use Opsphere MCP tools on the remote gateway.
**All current plans** (Community, Developer, Team, Enterprise, Custom): no skill-level plan gate. Use only tools in `tools/list`. If memory tools are missing, deliver the post-mortem as markdown only.
## Scope
- After incidents, outages, CI failures, or completed triage (`@incident-investigation`, `@ci-investigation`, `@endpoint-health`, or inline investigation).
- Outputs: structured post-mortem document + optional `memory_store` (`scope=incident`, `kind=episodic`).
- **Not** for live incident response — triage first, post-mortem when the user is closing the loop.
- **Not** infra mutations — no cache purge, deploys, workflow dispatch, kubectl, WAF writes, etc.
Respect gateway errors: `TRIAL_EXPIRED`, `RATE_LIMIT_EXCEEDED` — explain and stop; do not retry blindly.
## Tools
Use tools that exist in the current session's `tools/list`. Never invent tool names.
**Memory (preferred when available):**
| Tool | Purpose |
|------|---------|
| `memory_search` | Prior incidents, decisions, or session notes (`scopes`: `incident`, `decision`, `repository`, `session`, `user`) |
| `memory_store` | Save episodic incident memory after user approves the draft |
| `memory_session_touch` | Optional — bind `repo` / `environment` before store. Hub: `external_session_key` = `chat_session_key` from `ops_context_open` (auto-injected when omitted) |
| `memory_invalidate` | Mark superseded prior incident memory if user provides an ID |
**Read-only evidence refresh** (optional, skip if absent or incident already documented):
| Tool | When useful |
|------|-------------|
| `dd_logs_search` | Narrow log window around incident time |
| `dd_errors_by_service` / `dd_errors_recent` | Error counts during window (paid catalogs) |
| `alerts_active` | Monitors still firing at write time |
| `deployment_status` | Deploy correlation (multi-platform, preferred) |
| `vercel_deploys_latest` | Vercel-only deploy correlation |
| `ghe_actions_latest` / `bb_pipelines_latest` | CI correlation |
| `http_check` / `dns_lookup` / `cert_status` | Endpoint state at close |
| `jira_issue_get` | Link or summarize a ticket |
| `confluence_search` / `confluence_page_read` | Related runbooks (paid) |
| `ops_my_usage` | Environment context only if needed — not a plan gate |
Do not paste or store secrets, API keys, or full log dumps. Summarize in plain language.
## Ask the user (mandatory when missing)
Before finalizing the draft, ensure you have enough detail. **Ask the user** (via the parent agent or directly) for anything unknown — do not invent facts.
| Topic | Example question |
|-------|------------------|
| **Title** | What should we call this incident? |
| **Environment** | Which env was affected (INT, TST, PRE, PRD, other)? |
| **Time window** | When did it start and when was it resolved (timezone)? |
| **Impact** | Who or what was affected (users, revenue, internal teams, SLO)? |
| **Symptoms** | What did people observe (errors, latency, downtime)? |
| **Root cause** | Confirmed cause vs best hypothesis? |
| **Resolution** | What fixed it (deploy rollback, config change, external recovery)? |
| **Detection** | How was it detected (alert, customer report, monitoring)? |
| **Action items** | Follow-ups, owners, due dates? |
| **Repo / service** | Relevant `org/repo` or service name for memory? |
| **Save to memory** | Should I save this to Opsphere memory for next time? |
If the user already provided details in the thread, reuse them — only ask for gaps. Batch at most **2–4 questions** per turn.
## Workflow
1. **Ingest context** — read the user message and any prior subagent reports in the thread.
2. **Search memory** — if `memory_search` exists, query incident title, hostname, service, or repo; note related past incidents (hints only).
3. **Clarify** — ask the user for missing fields from the table above (batch 2–4 questions max per turn).
4. **Optional evidence** — if timeline or root cause is unclear and read-only tools exist, run **at most 1–2** targeted calls (e.g. `dd_logs_search` in the incident window). Skip if the user said the investigation is complete.
5. **Draft post-mortem** — use the template below; mark unknown sections as _TBD_ or _hypothesis_.
6. **Review** — show the draft to the user; apply edits they request.
7. **Persist** — if `memory_store` exists and the user wants to save:
- `scope`: `incident`
- `kind`: `episodic`
- `title`, `summary`: short distilled text (no raw logs)
- `incident`: `{ title, status: "resolved" | "investigating" | "false_positive", summary, root_cause?, resolution? }`
- `repo`, `environment` when known
- On `catalog_context_duplicate`, distill session-specific findings only
8. **Return** — final markdown + whether memory was saved (include memory IDs if returned).
## Post-mortem template
```markdown
# [Incident title] — [Environment] — [Date]
**Status:** resolved | investigating | false_positive
**Window:** [start] → [end] ([timezone])
**Impact:** [who/what, duration, severity]
## Summary
[2–4 sentences — what happened]
## Timeline
| Time | Event |
|------|-------|
| … | Detection / first alert |
| … | Investigation milestone |
| … | Mitigation / resolution |
## Root cause
[Confirmed cause or labeled hypothesis]
## Resolution
[What fixed or mitigated the issue]
## What went well
- …
## What went poorly
- …
## Action items
| Item | Owner | Due |
|------|-------|-----|
| … | … | … |From impactotecnologico/mcp-ops-plugin, MIT.
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Signals
- Stars
- 0
- Forks
- 0
- Open issues
- 0
- Last commit (this folder)
- Oct 20, 2026 (12 days ago)
- Last release
- Jul 15, 2026 (3 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
Same skill elsewhere
Copies of this SKILL.md published by others; search shows only one of them.
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SkillAFreshness: AClaude Code +9 - 0.564score
ci-investigation
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Done for you
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Chalk Labs scopes, builds and runs agents for your team: the task audit, the eval harness, the integrations and the weekly ops report. Fixed scope, priced before we start.
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Chalk Labs is a two-founder AI and growth studio. We build AI agents, CRMs and MVPs for Web3 and AI companies, and have shipped 50+ product and token launches.
- launches shipped
- 50+
- launches shipped
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- 500+
- media placements
- founders on every account
- 2
- founders on every account
Press we've placed: Forbes · CoinDesk · Decrypt · Cointelegraph · The Block
Rahil Jain, Co-founder, Chalk Labs. Ex-Goldman Sachs engineer. You talk to the person who builds it.
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postmortem-writer skill. Agent Mart. https://agentmart.dev/skills/impactotecnologico-postmortem-writer (last updated 2026-10-24)