| name | mcp-debugging-workflow |
| description | Use image-scoring MCP tools to debug scoring failures, check database health, and investigate system issues. Trigger when the user asks to debug scoring, investigate failure, or check database health. |
MCP Debugging Workflow
When to Use
Apply this skill when the user asks to:
- Debug scoring
- Investigate failure
- Check database health
- Find failed images
- Diagnose pipeline issues
Workflow Steps
1. Get Error Overview
On is-be-mcp: search("scoring failures") → dispatch("diagnostics.get_error_summary", {}).
2. Check Database Health
dispatch("diagnostics.check_database_health", {})
3. Get Failed Images (if errors found)
dispatch("jobs.get_failed_images", {"limit": 50})
4. Check Model/GPU Status
dispatch("diagnostics.get_model_status", {})
5. Check Active Jobs (if processing expected)
On is-be-mcp: dispatch("jobs.get_runner_status", {}) and/or dispatch("jobs.get_recent_jobs", {}). If search finds no matching action, use optional is-be-live with MCP_SSE_PROFILE=full for legacy raw tools.
6. Read Debug Log (for detailed errors)
dispatch("logs.read_debug_log", {"lines": 100}) or dispatch("logs.search_logs", {"pattern": "error|failed"})
Server Selection
- Default:
is-be-mcp → search / dispatch
- Optional SSE:
is-be-live (same compact tools when WebUI is running)
execute_code / full legacy raw tools: is-be-live + MCP_SSE_PROFILE=full + ENABLE_MCP_EXECUTE_CODE=1 when needed
Terminology
Align with product UI: pipeline stages are Discovery → Inspection → Quality Analysis → Similarity Clustering → Tagging; DB uses phase_code; REST uses scoring / tagging / clustering. See docs/technical/PIPELINE_TERMINOLOGY.md.
References