plan_workflow
Preview what a workflow WOULD do, without running it. Costs nothing and runs no models: returns the step execution order, each step's role/model/max_tokens and whether it pauses for a human checkpoint, the workflow's declared parameters (validated if you supply values), which required integration...
This record as markdown: /tools/com-meta-council-decision-intelligence/plan-workflow.md
What plan_workflow does on Meta Council
AI agents use plan_workflow to create or update resources in Meta Council, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Meta Council environment.
| Parameter | Type | Required | Description |
|---|---|---|---|
workflow | string | Yes | The workflow slug (from list_workflows), e.g. 'due_diligence'. |
parameters | object | — | Optional values for the workflow's declared parameters, as a flat name-to-value object, e.g. {"region": "EU"}. Supply them to have them validated; omit to skip |
step_models | object | — | Optional per-run model choices, keyed by zero-based step index (for example {"0": "claude-sonnet-4-6"}). Uses the same catalog validation as run_workflow; send |
Parameters from the server's own tool schema.
Why plan_workflow is rated Medium
An AI agent can call plan_workflow faster than any human can review: one bad instruction and it creates or modifies resources in Meta Council by the hundred, each call as confident as the last.
Attacks that exploit this kind of access
The rule that runs plan_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 plan_workflow, this is the rule to start with:
plan_workflow stays usable, but capped: an agent stuck in a loop can't make hundreds of changes 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 plan_workflow call is checked against it from then on.
Questions about plan_workflow
Preview what a workflow WOULD do, without running it. Costs nothing and runs no models: returns the step execution order, each step's role/model/max_tokens and whether it pauses for a human checkpoint, the workflow's declared parameters (validated if you supply values), which required integrations your account already has credentials on file for, an upper-bound cost estimate, and definition_sha — a fingerprint of the definition this plan was built from, which tells you whether the definition changed between planning and running but never hands back the definition itself. Starts no session and records no usage. Use before run_workflow to check a pipeline fits before spending on it. Requires authentication. It is categorised as a Write tool in the Meta Council MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
plan_workflow accepts 3 parameters: workflow, parameters, step_models. Required: 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 plan_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.
plan_workflow is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the plan_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 plan_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.
plan_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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