Creates RPC-style endpoint following layered architecture (Controller → Manager → Repository). Use when creating new API endpoints or CRUD operations.
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Create a structured on-call log by pulling alerts from monitoring and writing a summary to your team's wiki. Requires a monitoring MCP (recommended: Datadog) and a wiki MCP (Confluence or Notion).
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설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Pull alerts from your monitoring platform and create a structured on-call log on your team's wiki.
Two MCP servers are required:
mcp__claude_ai_Atlassian__*) or Notion (mcp__claude_ai_Notion__*).If either is missing, stop with:
Error: Missing required MCP server(s):
<list>. This skill needs both a monitoring MCP and a wiki MCP. Recommended: Datadog MCP + Confluence or Notion MCP.
Ask the user:
If the user has run this before and configuration is available (e.g., in .spartan/config.yaml), reuse those settings and confirm:
"Using previous settings: <frequency>, <env> alerts, wiki at <location>. Correct?"
Based on the log frequency from Step 2:
If the user provides a custom date range, use that instead.
Confirm with the user:
"Logging on-call for <start date> – <end date>. Is this correct?"
Wait for confirmation before continuing.
Search the wiki for an existing page for this period (using the naming convention from Step 7). If found, read it to find the last updated timestamp. Ask the user: "A page for this period already exists. Update it or create new?"
from date instead of the full window start — this avoids re-fetching alerts already logged and reduces token usage.Add a **Last updated:** <timestamp> line at the top of the page on each update.
Use the available monitoring MCP to fetch alert events:
Pagination: If results are truncated, paginate until all events are fetched.
From all fetched events:
Group events by base monitor name. For each group collect:
Sort alerts by Appear Count descending.
Query monitors currently in Alert status. Flag these as needing follow-up by the next on-call.
If no alerts during the window, note "No alerts this period" and continue.
"Any additional notes, incidents, or action items to include in the log?"
Record their input. If "none", continue without notes.
If the user provided a template page in Step 2, fetch it and use its structure as the format guide. Otherwise use the default structure from Step 8.
Organize on-call logs in a consistent hierarchy:
On-call Logs/
On-call <YYYY>/
On-call <MM>/<YYYY>/
[On-call] <Start Date> - <End Date>
Create the page on the wiki platform:
# On-call Log: <Start Date> – <End Date>
## Alert Summary
| Alert | Count | Times | Cause | Resolution |
|-------|-------|-------|-------|------------|
| <monitor name> | <N> | <timestamp 1>, <timestamp 2>, ... | | Still active |
**Total alerts:** <N> across <M> unique monitors
## Currently Active Alerts
<list monitors still in Alert status, or "None — all clear">
## Notes
<additional notes from Step 5, or "None">
## Action Items for Next On-call
- <follow up on active alert X>
- <investigate recurring alert Y — triggered N times>
Formatting:
## On-call Log Created
**Page:** <page title>
**URL:** <wiki page URL>
**Alerts logged:** <N> alerts across <M> unique monitors
**Active alerts:** <count or "None">
**Notes:** <summary or "None">
If there are unresolved alerts:
Action items for next on-call: The following alerts are still active — follow up with the relevant team:
<list>
Create the log page directly on the wiki platform (Confluence or Notion). Present the URL and stats inline in the conversation.
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Creates RPC-style endpoint following layered architecture (Controller → Manager → Repository). Use when creating new API endpoints or CRUD operations.
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Write blog posts, guides, tutorials, and long-form content. Sounds like a real person, not AI. Use when the user wants polished written content.
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Design RPC-style APIs with layered architecture (Controller → Manager → Repository). Use when creating new API endpoints, designing API contracts, or reviewing API patterns.
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Run a structured brainstorm session for startup ideas. Takes a theme or problem and generates ideas with quick gut-checks. Use when the user wants to explore a space or generate new ideas.
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Run real browser QA with Playwright. Use when testing a frontend feature, verifying UI before PR, smoke testing after deploy, or investigating reported visual bugs.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
CI/CD pipeline patterns for GitHub Actions, PR automation, and deployment workflows. Use when setting up CI, fixing broken pipelines, automating PR checks, or configuring deployment.
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