Knuckles-Team Capability Discovery Workflow
CONCEPT:SYS-001
Discovery workflow that probes available capabilities across MCP servers. Tests tool introspection, not execution — useful for building capability maps.
Steps
Step 0: Audio Transcriber
Agent: scanner-agent
Tools: tun_tm_system, tun_tm_remote
Describe the capabilities of the transcribe_audio tool
Expected: transcribe, audio
Step 1: Data Science Mcp
Agent: analyzer-agent
Tools: graph_analyze, tun_tm_security
Describe the available data science tools and their parameters
Expected: dataset, tool
Step 2: Scholarx Mcp
Agent: remediator-agent
Tools: tun_tm_remote, tun_tm_inventory
List available research paper sources
Expected: source
Step 3: KG Persistence [depends_on: scholarx-mcp]
Agent: remediator-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
- Capability Discovery 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 — Audio Transcriber; Step 1 — Data Science Mcp; Step 2 — Scholarx Mcp
- 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.