Knuckles-Team Dietician And Chef Workflow
CONCEPT:HEALTH-001
Generates a customized healthy meal plan, adds selected recipes, and compiles an organized, scaled household shopping list in Mealie using mealie-mcp tools.
Steps
Step 0: Dietician Chef
Agent: data-collector
Tools: graph_query
Generate a customized weekly meal plan matching the user's calorie targets. Register/add the planned meals to Mealie using the mealie_recipes and mealie_organizer tools.
Expected: mealplan, recipes
Step 1: Mealie Mcp
Agent: analyzer-agent
Tools: graph_analyze
Compile and organize a consolidated grocery shopping list for the planned weekly meals. Use the mealie_households tools to add the required recipe ingredients scaled for the household into a clean, categorized Mealie shopping list.
Expected: shopping_list, ingredients
Step 2: KG Persistence [depends_on: mealie-mcp]
Agent: analyzer-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
- Dietician And Chef results persisted in KG
- Structured report (MD/PDF)
- Audit trail with timestamps and agent attributions
Human Oversight Required
✅ Critical decisions require human review and approval.
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 — Dietician Chef; Step 1 — Mealie Mcp
- After level 0: Step 2 — 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.