Knuckles-Team Observability And Research Workflow
CONCEPT:RESEARCH-001
Combined observability check with research discovery. Validates Langfuse is healthy while concurrently searching for papers on agent observability.
Steps
Step 0: Langfuse Configuration Inventory [skill: langfuse-mcp]
Agent: search-agent
Tools: sx_search, graph_query
Check Langfuse health, list all score configs, and list all datasets
Expected: health, score, dataset
Step 1: Scholarx Mcp
Agent: analyzer-agent
Tools: graph_analyze, sx_storage
Search for recent papers on LLM observability and agent tracing
Expected: paper, observability
Step 2: Langfuse Project Inventory [skill: langfuse-mcp]
Agent: synthesizer-agent
Tools: graph_analyze, document_tools
List all current projects in the Langfuse instance
Expected: project
Step 3: KG Persistence [depends_on: Step 2]
Agent: synthesizer-agent
Tools: graph_write
Persist workflow results as nodes and edges in the Knowledge Graph. Create appropriate typed nodes with metadata and link to existing domain entities.
Output
- Observability And Research results persisted in KG
- Structured report (MD/PDF)
- Audit trail with timestamps and agent attributions
Execution
Run this workflow as a dependency-ordered DAG. Steps with no unmet depends_on run in parallel; dependents run after their prerequisites complete.
- Run first (in parallel): Step 0 — Langfuse Configuration Inventory; Step 1 — Scholarx Mcp; Step 2 — Langfuse Project Inventory
- After level 0: Step 3 — KG Persistence
Execution: If graph-os is reachable, offload the whole DAG via graph_orchestrate action=execute_workflow (or the kg-delegate skill) for true parallel/swarm execution. Otherwise execute the steps natively in dependency order: run steps with no unmet depends_on in parallel, then their dependents.