ai-reliability-copilot
Transform production incidents into structured LLM responses
GraphCanon updated 3w · GitHub synced 3w
Decision brief
ai-reliability-copilot converts production incidents into structured LLM responses with nine sections including severity and root cause analysis.
Good fit when
- When detailed LL-based incident response structuring is required
- For SRE teams focusing on rapid, comprehensive evaluations
Avoid when
- If real-time response customization beyond preset formats is needed
- In environments lacking the required backend databases like pgvector or Supabase
Observed Jul 16, 2026 · Source: enrich:decision_facts
Verify the decision
Adoption
Package downloads where a registry match exists. GitHub stars (102) are secondary evidence.
- npm downloads (30d)
- 8,123·npm downloads API·3w
Maintenance and security
Full trust report- Maintenance
- Steady (34d since push)
- As of 3w
- Provenance
- Not a fork · Personal account
- As of 3w
- Security (OSV)
- No MCP manifest
- As of 1mo
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
npm install ai-reliability-copilotSimilar tools
Same-category neighbours. No typed graph edges are catalogued for this tool yet.
Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
A tool that converts a production incident into a structured nine-section response for analysis and mitigation, featuring severity, root cause, and postmortem sections among others; includes a regression suite with five scenarios and an evaluation pipeline using LLMs.
Capability facts
- CLI
- CLI entrypoint
Source: package.json:bin|scripts · Jul 29, 2026
- MCP server
- Ships MCP server
Source: package.json:@modelcontextprotocol/* · Jul 29, 2026
- Languages
- typescript, javascript
Source: github.language+package.json · Jul 29, 2026
Categories
Tags
README
License
MIT
Built in 30 days as a side project to learn AI engineering and evaluation methodology.
For agents
This page has a .md twin and JSON over the API.