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AI Operations Center for Multi-Agent Systems with DevOps incident response workflows, chaos engineering, and root cause analysis copilot
This FastAPI HTTP server exposes 12 tools with basic descriptions but significant quality gaps. Tool names are reasonably clear (health_check, trigger_run, get_run, list_runs, stream_run, get_scenarios, enable_chaos_mode, disable_chaos_mode, get_current_chaos_state, list_chaos_modes, ask_copilot, compare_runs), but descriptions are inconsistent in depth. Most critically: input schemas are visible but lack comprehensive parameter descriptions (e.g., 'scenario' in trigger_run has minimal guidance on valid values; 'mode' in enable_chaos_mode lists modes but no intensity range detail). Output schemas are not documented anywhere in the provided code. Error handling is not evident from the source. No tool annotations (readOnlyHint, destructiveHint, idempotentHint) are present. The ask_copilot tool description is verbose but vague about what 'verified telemetry' means to the LLM. Overall, this reads as a working backend with functional tools but insufficient LLM-optimization for agent use.
Root Cause Copilot endpoint. Collects local workflow context, calls Evidence Engine via MCP to SigNoz, validates evidence, and streams LLM response grounded in verified telemetry.
Compare two workflow runs side-by-side.
Disable a specific chaos mode or all chaos.
Enable a chaos mode with given intensity.
Get current chaos injection state.
Get the status and result of a workflow run.
Return the list of demo incident scenarios.
Output schemas not documented. No tool returns a documented schema showing what fields the LLM should expect. This forces agents to guess at response structure and breaks downstream tool chaining.
Parameter descriptions lack actionable constraints. 'scenario' in trigger_run says 'The incident scenario to investigate. If None, pick random default' but does not enumerate valid scenarios or explain format. 'intensity' in enable_chaos_mode lacks range (0.0 - 1.0) in the description text itself.
No error handling guidance. Source code does not show error responses, recovery hints, or categorization (retryable vs. fatal). Agents cannot determine what to do if a tool call fails.
Inferred effective spec: <=2025-11-25.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | D | 50 | <=2025-11-25 | v2 |
Health check endpoint — also serves as system status for the frontend.
List all available chaos modes.
List all workflow runs.
SSE endpoint: stream real-time status updates for a run.
Trigger a new incident response workflow run.
No tool annotations. Tools lack readOnlyHint, destructiveHint, or idempotentHint. Agents cannot infer which tools are safe to retry or which modify state without reading descriptions.
Pagination not evident. list_runs and list_chaos_modes lack limit/offset/page parameters and do not document result count or next_cursor. Large result sets will blow context windows.