clear_pipeline_learnings
Reset all learnings for a pipeline and start fresh. Use when user says "forget what you learned", "start fresh with the style", "reset the learnings", or "clear the feedback history". [write-tier — first use may require a manager's approval; a from-now-on approval makes future calls seamless, a j...
This record as markdown: /tools/com-getfreedomos-freedom-mcp/clear-pipeline-learnings.md
What clear_pipeline_learnings does on Freedom Mcp
AI agents call clear_pipeline_learnings to permanently remove resources in Freedom Mcp, typically in cleanup and lifecycle workflows. It does its job in a single call, and there is no undo.
| Parameter | Type | Required | Description |
|---|---|---|---|
companyId | string | Yes | FreedomOS company id to act within (you must be a member). Required for company-scoped tools. |
pipeline_id | string | Yes | Pipeline ID (get from list_pipelines) |
output_format | string | — | Optional. Only clear learnings for a specific format. If not specified, clears all formats. |
Parameters from the server's own tool schema.
Why clear_pipeline_learnings is rated Critical
Irreversibly wipes all accumulated pipeline learnings and feedback history.
From the tool's definition Reset all learnings... start fresh... clear the feedback history
Attacks that exploit this kind of access
The rule that runs clear_pipeline_learnings safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Freedom Mcp, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For clear_pipeline_learnings, this is the rule to start with:
clear_pipeline_learnings is removed from the agent's tool list entirely, so the agent never calls it. The rest of the server keeps working.
The button opens the PolicyLayer dashboard: create your workspace, connect Freedom Mcp, apply this rule, and every clear_pipeline_learnings call is checked against it from then on.
Questions about clear_pipeline_learnings
Reset all learnings for a pipeline and start fresh. Use when user says "forget what you learned", "start fresh with the style", "reset the learnings", or "clear the feedback history". [write-tier — first use may require a manager's approval; a from-now-on approval makes future calls seamless, a just-once approval re-asks next time.]. It is categorised as a Destructive tool in the Freedom Mcp MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.
clear_pipeline_learnings accepts 3 parameters: companyId, pipeline_id, output_format. Required: companyId, pipeline_id. The full parameter table on this page comes from the server's own tool schema.
Register the Freedom MCP server in PolicyLayer and add a rule for clear_pipeline_learnings: 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 Freedom Mcp. Nothing to install.
clear_pipeline_learnings is a Destructive tool with critical risk. Critical-risk tools should be blocked by default and only enabled with explicit human approval.
Yes. Add a rate_limit block to the clear_pipeline_learnings 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 clear_pipeline_learnings. 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.
clear_pipeline_learnings is provided by the Freedom MCP server (https://twuluxmoognlwtmaoqgo.supabase.co/functions/v1/freedom-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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