Feature: Runbooks for Incident Resolution (AI + SRE)

### Summary
Add the ability to define and store runbooks for common incidents so both AI agents and SREs can reference structured resolution steps during incident response.

### Problem
When incidents occur, resolution steps often live in scattered docs, Slack threads, or individual memory.
This leads to:
- Slower resolution times
- Inconsistent handling
- Knowledge silos
- Limited AI-assisted troubleshooting

We need a structured, queryable way to store and retrieve incident runbooks.

### Proposed Solution

Introduce **Runbooks** as a first-class entity:

- Create / edit runbooks
- Tag by service, severity, category
- Structured steps (checklist format)
- Attach logs, queries, dashboards, or links
- Support markdown

Each runbook should include:
- Title
- Description
- Affected services
- Trigger conditions
- Step-by-step resolution instructions
- Escalation notes
- Post-incident checklist

### AI Integration

Runbooks should be:
- Searchable via semantic search
- Automatically suggested during incidents
- Usable by AI agents to execute or recommend steps
- Context-aware based on error signals

Example:
> If error rate spikes on `api-service`, suggest “High 5xx Errors – API Service” runbook.

### Benefits

- Faster MTTR
- Consistent resolution
- Easier onboarding of new SREs
- Enables AI-assisted incident response
- Institutional knowledge capture

### Future Extensions

- Link runbooks to specific alert rules
- Auto-trigger runbooks
- Execution logs tied to incidents
- Feedback loop to improve runbooks over time

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Would love community feedback on:
- How you currently manage runbooks
- What fields are essential
- Whether AI-assisted execution would be useful

Open to refining the scope before implementation.

The issue names no files, tests, or entry points, and leaves the scope open for community feedback. Start by clarifying the Runbook fields, storage and retrieval behavior, and AI integration boundaries; done should be an implementable scope covering creation, editing, structured steps, search, and incident suggestions.

Written by the indexing model from the issue text.