run_workflow
Start a multi-step workflow pipeline and return its session id and definition_sha immediately by default — the fingerprint of the definition this run resolved, comparable against the one plan_workflow reported. Poll get_workflow_session for each step's model/provider and output. synthesis. Steps ...
This record as markdown: /tools/com-meta-council-decision-intelligence/run-workflow.md
What run_workflow does on Meta Council
AI agents invoke run_workflow to trigger actions in Meta Council. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call: builds kicked off, notifications sent, workflows started.
| Parameter | Type | Required | Description |
|---|---|---|---|
query | string | Yes | The input to run the pipeline on. Be specific, e.g. 'Analyze NVDA as an investment'. |
workflow | string | Yes | The workflow slug (from list_workflows), e.g. 'live_market_pipeline', 'due_diligence', 'coding_tdd'. |
parameters | object | — | Values for the workflow's declared parameters, as a flat name-to-value object, e.g. {"region": "EU"}. Omitted names use their declared defaults. Workflows that |
step_models | object | — | Per-run model choices, keyed by zero-based step index, exactly as supplied to plan_workflow. IDs are catalog-validated; existing key, tier and platform fallback |
wait_seconds | integer | — | Optional synchronous wait; default 0 returns immediately. |
idempotency_key | string | — | Caller-supplied key: sending the same key again returns the run that already exists instead of starting a second, paid run. Use a stable key derived from your o |
Parameters from the server's own tool schema.
Why run_workflow is rated High
run_workflow triggers real processes with real consequences. An agent gone sideways doesn't fire it once. It starts dozens of builds, sends mass notifications, or burns through compute before anyone looks up.
Attacks that exploit this kind of access
The rule that runs run_workflow safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Meta Council, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For run_workflow, this is the rule to start with:
run_workflow stays usable, but rate-capped: a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Meta Council, apply this rule, and every run_workflow call is checked against it from then on.
Questions about run_workflow
Start a multi-step workflow pipeline and return its session id and definition_sha immediately by default — the fingerprint of the definition this run resolved, comparable against the one plan_workflow reported. Poll get_workflow_session for each step's model/provider and output. synthesis. Steps run on YOUR configured provider keys, so a pipeline can chain models across providers. If a step is a human checkpoint, returns the session id to advance. Requires authentication. It is categorised as a Execute tool in the Meta Council MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
run_workflow accepts 6 parameters: query, workflow, parameters, step_models, wait_seconds, idempotency_key. Required: query, workflow. The full parameter table on this page comes from the server's own tool schema.
Register the Meta Council MCP server in PolicyLayer and add a rule for run_workflow: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Meta Council. Nothing to install.
run_workflow is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the run_workflow rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for run_workflow. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
run_workflow is provided by the Meta Council MCP server (https://meta-council.com/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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