| name | sparkgen-workflow |
| description | View, validate, and edit the ai_workflow.yaml configuration |
| user_invokable | true |
| auto_invokable | true |
| auto_invoke_hint | Invoke when the user discusses workflow, orchestration, handoffs, or ai_workflow.yaml |
| arguments | <show|validate|add-handoff|set-pattern|env-override|edit> |
SparkGen Workflow
Manage the central workflow configuration in config/ai_workflow.yaml.
Dynamic Context
Before any action:
- Read
config/ai_workflow.yaml — the single source of truth
- If server is running, fetch live config:
curl -sf http://localhost:8000/v1/workflow -H "X-API-Key: ${API_KEY:-dev-local-key}"
Actions
Show Workflow (/sparkgen-workflow show)
Parse and display config/ai_workflow.yaml in a readable format:
- LLM: provider, model, region
- Embedding: provider, model
- Agents: name, role, tools (table format)
- Orchestration: pattern, entry_agent, max_iterations
- Handoffs: from → to (condition) for each rule
- Guardrails: enabled, active sets
- RAG: enabled, default mode, knowledge bases
- Environment overrides: list which environments have overrides
Validate Workflow (/sparkgen-workflow validate)
python -c "from app.config.workflow_loader import load_workflow; w = load_workflow(); print(f'Workflow loaded: {w[\"name\"]}, {len(w.get(\"agents\", []))} agents')"
Check for:
- YAML syntax errors
- Missing required fields
- Agent references in handoffs match defined agents
- Tool references in agents match defined tools
- Prompt files referenced actually exist
Add Handoff (/sparkgen-workflow add-handoff <from> <to> <condition>)
Add a new routing rule to the handoffs: section:
- from: <from_agent>
to: <to_agent>
condition: "<condition_expression>"
Then validate the workflow.
Set Pattern (/sparkgen-workflow set-pattern <single_agent|router_manager>)
Update orchestration.pattern in the workflow YAML:
single_agent: Only one agent, no routing
router_manager: Main agent routes to specialists based on intent
Validate that the pattern matches the agent count (single_agent requires 1 agent).
Environment Override (/sparkgen-workflow env-override <env_name> <section> <key> <value>)
Add or update an environment-specific override in the environments: section:
environments:
<env_name>:
<section>:
<key>: <value>
Edit (/sparkgen-workflow edit)
Open config/ai_workflow.yaml for direct editing. After changes, always run validate.
Workflow Structure Reference
The YAML has 13 sections: version, name, description, llm, embedding, knowledge_bases, rag, tools, memory, guardrails, prompts, agents, orchestration, handoffs, observability, evaluation, environments.