get_agent_outcome_panel
Per-agent "what did the compute buy" facts for the operator: trailing-14-day credits, runs (with self-maintenance share), human-accepted vs denied outputs, pending cards, last-accepted date, and a playing-house flag (activity with zero accepted output). Use when the operator asks whether an agent...
This record as markdown: /tools/com-getfreedomos-freedom-mcp/get-agent-outcome-panel.md
What get_agent_outcome_panel does on Freedom Mcp
AI agents call get_agent_outcome_panel to retrieve information from Freedom Mcp without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
agent_id | string | — | Optional: limit to one agent (uuid). Omit for the whole team. |
companyId | string | Yes | FreedomOS company id to act within (you must be a member). Required for company-scoped tools. |
Parameters from the server's own tool schema.
Why get_agent_outcome_panel is rated Low
This tool is purely informational—it aggregates and presents historical performance data for review by operators, executives, and managers. There are no mutations, deletions, code execution, or financial transactions. The low severity reflects that misuse would only expose internal metrics about agent performance, with no irreversible consequences or external impact.
From the tool's definition Tool retrieves and displays agent performance metrics: 'trailing-14-day credits, runs (with self-maintenance share), human-accepted vs denied outputs, pending cards, last-accepted date, and a playing-house flag'.
Attacks that exploit this kind of access
The rule that runs get_agent_outcome_panel 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 get_agent_outcome_panel, this is the rule to start with:
get_agent_outcome_panel is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Freedom Mcp, apply this rule, and every get_agent_outcome_panel call is checked against it from then on.
Questions about get_agent_outcome_panel
Per-agent "what did the compute buy" facts for the operator: trailing-14-day credits, runs (with self-maintenance share), human-accepted vs denied outputs, pending cards, last-accepted date, and a playing-house flag (activity with zero accepted output). Use when the operator asks whether an agent is worth its spend, what an agent has been doing, or why credits are being used — for executives and managers reviewing their AI team. It is categorised as a Read tool in the Freedom Mcp MCP Server, which means it retrieves data without modifying state.
get_agent_outcome_panel accepts 2 parameters: agent_id, companyId. Required: companyId. 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 get_agent_outcome_panel: 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.
get_agent_outcome_panel is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the get_agent_outcome_panel 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 get_agent_outcome_panel. 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.
get_agent_outcome_panel 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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