Use when creating structured operational runbooks for human operators. Covers runbook organization, documentation patterns, and best practices for clear operational procedures.
View on GitHubTheBushidoCollective/han
jutsu-runbooks
January 24, 2026
Select agents to install to:
npx add-skill https://github.com/TheBushidoCollective/han/blob/main/jutsu/jutsu-runbooks/skills/runbook-structure/SKILL.md -a claude-code --skill runbooks-structureInstallation paths:
.claude/skills/runbooks-structure/# Runbooks - Structure Creating clear, actionable runbooks for operational tasks, maintenance, and troubleshooting. ## What is a Runbook? A runbook is step-by-step documentation for operational tasks: - **Troubleshooting** - Diagnosing and fixing issues - **Incident Response** - Handling production incidents - **Maintenance** - Routine operational tasks - **On-Call** - Reference for on-call engineers ## Basic Runbook Structure ### Minimum Viable Runbook ```markdown # Service Name: Task/Issue ## Overview Brief description of what this runbook covers. ## Prerequisites - Required access/permissions - Tools needed - Knowledge required ## Steps ### 1. First Step Detailed instructions for first action. ### 2. Second Step Detailed instructions for second action. ## Validation How to verify the task was completed successfully. ## Rollback (if applicable) How to undo the changes if needed. ``` ## Comprehensive Runbook Template ```markdown # [Service]: [Task/Issue Title] **Last Updated:** 2025-01-15 **Owner:** Platform Team **Severity:** High/Medium/Low **Estimated Time:** 15 minutes ## Overview Brief description of the problem or task this runbook addresses. ## When to Use This Runbook - Alert fired: `high_cpu_usage` - Customer report: slow response times - Scheduled maintenance window ## Prerequisites - [ ] VPN access to production network - [ ] AWS console access (read/write) - [ ] kubectl configured for production cluster - [ ] Slack access to #incidents channel ## Context ### Architecture Overview Brief explanation of relevant system architecture. ### Common Causes - Database connection pool exhaustion - Memory leaks in worker processes - Third-party API rate limiting ## Diagnosis Steps ### 1. Check System Health ```bash # Check pod status kubectl get pods -n production # Expected output: All pods Running ``` **Decision Point:** If pods are CrashLooping, proceed to step 2. Otherwise, skip to step 3. ### 2. Check Application Logs ```bash #
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