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You are an expert in automated diagnostics and runbook creation for an AI-driven troubleshooting agents. I will provide you with one or more issue descriptions or test scenarios.
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Your task is to generate a strictly executable runbook for AI Agent to follow. The runbook should be machine-readable but human-understandable, and must include:
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Your task is to generate a strictly executable runbook for AI Agent to follow. The runbook should be machine-readable but human-understandable, and must include the following sections:
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## Goal
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# Runbook Content Structure
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## 1. Goal
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-**Primary Objective:** Clearly define the specific category of issues this runbook addresses (e.g., "diagnose network connectivity problems", "troubleshoot pod startup failures", "investigate performance degradation").
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-**Scope:** Specify the environment, technology stack, or system components covered by this runbook.
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-**Agent Mandate:** Explicitly state that the AI agent must follow the workflow steps sequentially and systematically without deviation to ensure consistent, thorough troubleshooting.
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-**Expected Outcome:** Define what successful completion of this runbook should achieve (root cause identification, issue resolution, or escalation criteria).
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## Workflow for [Issue Category] Diagnosis
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## 2. Workflow for [Issue Category] Diagnosis
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- Provide numbered, sequential steps the AI agent must execute in order.
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- Each step should specify:
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-**Action:** Describe the diagnostic function conceptually (e.g., "retrieve container logs from specified pod", "check service connectivity between components", "examine resource utilization metrics")
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- Describe functions generically so they can be mapped to available tools (e.g., "execute a command to test network connectivity" rather than "ping_host()")
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- Include verification steps to confirm each diagnostic action was successful.
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## Synthesize Findings
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## 3. Synthesize Findings
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-**Data Correlation:** Describe how the AI agent should combine outputs from multiple workflow steps.
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-**Pattern Recognition:** Specify what patterns, error messages, or metrics indicate specific root causes.
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-**Prioritization Logic:** Provide criteria for ranking potential causes by likelihood or severity.
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-**Evidence Requirements:** Define what evidence is needed to confidently identify each potential root cause.
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-**Example Scenarios:** Include sample synthesis statements showing how findings should be summarized.
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## Recommended Remediation Steps
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## 4. Recommended Remediation Steps
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-**Immediate Actions:** List temporary workarounds or urgent fixes for critical issues.
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-**Permanent Solutions:** Provide step-by-step permanent remediation procedures.
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-**Verification Steps:** Define how to confirm each remediation action was successful.
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-**Documentation References:** Include links to official documentation, best practices, or vendor guidance.
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-**Escalation Criteria:** Specify when and how to escalate if remediation steps fail.
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-**Post-Remediation Monitoring:** Describe what to monitor to prevent recurrence.
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# File Organization Guidelines
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## Folder Structure
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*Category folders are used to distinguish and categorize different runbooks based on their focus area or technology domain. Each runbook must be placed into a specific category folder under `holmes/plugins/runbooks/` for better organization and discoverability. Create a new category folder if your runbook doesn't fit into existing categories.*
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## File Naming
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*Use consistent naming conventions for runbook files:*
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- Use descriptive, lowercase names with hyphens: `dns-resolution-troubleshooting.md`
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- Include the issue type or technology: `redis-connection-issues.md`
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- Avoid generic names like `troubleshooting.md` or `debug.md`
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### Catalog Registration
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After creating your runbook, you must add an entry to `catalog.json` in the runbooks directory to make it discoverable by AI agents.
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**Steps to add a new catalog entry:**
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1.**Open**`holmes/plugins/runbooks/catalog.json`
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2.**Add your entry** to the JSON array following this structure:
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