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Your first agent workflow

Goal: stand up a three-node agentic loop driven by WorkflowRuntime, see it through one complete iteration, inspect the immutable agent_runs_v2 rows it produces.

Why​

AgentSpec + AgentRuntime is AlphaSwarm's "skill artifact" — every agent run is hash-locked into agent_spec_versions and audited through agent_runs_v2. Combined with the additive WorkflowRuntime (orchestration adapter pattern), this is how AlphaSwarm composes multi-agent pipelines without losing replay or kill-switch semantics. See Concept: workflow studio.

Step 1 — author the workflow​

Create configs/workflows/my_first_workflow.yaml:

name: MyFirstResearchLoop
adapter_kind: graph
nodes:
  - id: research
    agent_spec: configs/agents/research_lite.yaml
    inputs:
      universe: [SPY, QQQ, IWM]
      lookback_days: 30
  - id: selection
    agent_spec: configs/agents/selection_lite.yaml
    depends_on: [research]
  - id: trader
    agent_spec: configs/agents/trader_paper.yaml
    depends_on: [selection]
edges:
  - { from: research, to: selection }
  - { from: selection, to: trader }
cost_caps:
  per_node_max_tokens: 4000
  per_run_max_usd: 0.50
halt_check_seconds: 5

Step 2 — snapshot + run​

curl -X POST http://localhost:8000/workflows/MyFirstResearchLoop/run \
    -d '{}'

WorkflowRuntime:

  1. Hash-locks the spec into workflow_spec_versions.
  2. Reads each referenced AgentSpec and hash-locks them into agent_spec_versions.
  3. Begins traversing the DAG, calling each agent through AgentRuntime.
  4. Emits canonical progress frames per AGENTS rule 4.
  5. Writes agent_runs_v2 and workflow_runs rows.

Step 3 — watch the breadcrumbs​

The operator UI renders the workflow live at /workflows/runs/<run_id>. From the CLI:

docker exec alphaswarm-api python -c "from alphaswarm.ws.broker import subscribe; \
    [print(m) for m in subscribe('<run_task_id>')]"

Step 4 — inspect the ledger​

SELECT id, workflow_name, status, started_at, ended_at, total_tokens, total_cost_usd
FROM workflow_runs ORDER BY started_at DESC LIMIT 1;

SELECT id, agent_name, node_id, status, total_tokens
FROM agent_runs_v2
WHERE workflow_run_id = '<from_above>'
ORDER BY started_at;

You should see three agent_runs_v2 rows — one per node.

Step 5 — replay​

curl -X POST http://localhost:8000/workflows/runs/<workflow_run_id>/replay

Same hash-locked spec versions, new run row.

Step 6 — halt​

The kill switch fans out:

curl -X POST http://localhost:8000/workflows/halt

Every running workflow stops; agent_runs_v2 rows close with status=halted.

Verify​

  • workflow_spec_versions row with a spec_hash.
  • Three agent_spec_versions rows (one per node).
  • One workflow_runs row + three agent_runs_v2 rows.
  • Total cost in USD ≤ per_run_max_usd from the spec.
  • Replay produces a new workflow_runs row but reuses the same spec-version rows.

What next​