Low Risk

geometric_confidence

Compute a composite geometric confidence score from validation signals. No Blueprint required — works on any validate result. Combines six weighted signals into a single confidence score: - Surface distance (how close to the constraint manifold) - Geometric health (projection quality, regulator, ...

Risk signalsHandles credentials or secrets (api_key)

Part of the Governance Platform server.

geometric_confidence is read-only, but an agent in a loop can still rack up calls and cost. PolicyLayer caps every call before it runs. Live in minutes.

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AI agents call geometric_confidence to retrieve information from Governance Platform without modifying any data. This is common in research, monitoring, and reporting workflows where the agent needs context before taking action. Because read operations don't change state, they are generally safe to allow without restrictions -- but you may still want rate limits to control API costs.

Even though geometric_confidence only reads data, uncontrolled read access can leak sensitive information or rack up API costs. An agent caught in a retry loop could make thousands of calls per minute. A rate limit gives you a safety net without blocking legitimate use.

Read-only tools are safe to allow by default. No rate limit needed unless you want to control costs.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "geometric_confidence": {}
  }
}

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These attack patterns abuse exactly the kind of access geometric_confidence gives an agent. Each links to the full case and the policy that stops it:

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Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so geometric_confidence only ever does what you allow.

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Other read tools across the catalogue. The same approach applies to each: allow, with a rate cap to control cost.

What does the geometric_confidence tool do? +

Compute a composite geometric confidence score from validation signals. No Blueprint required — works on any validate result. Combines six weighted signals into a single confidence score: - Surface distance (how close to the constraint manifold) - Geometric health (projection quality, regulator, closure) - Anomaly score (structural fingerprint deviation) - Stability score (batch drift) - Motif compliance (pattern violations) - Motif gate (enforcement decision) Returns confidence level (high/medium/low) and a recommendation. Different from analyze_anomaly and check_drift: those tools perform new analysis on raw data. geometric_confidence is post-hoc — it digests an already-computed state_vector and returns a single confidence number. Use this when you have a state_vector from a prior validate / get_execution_trace call and want a one-line summary of structural quality. Use analyze_anomaly when you need to know why something is anomalous; use check_drift when you need to compare against historical observations. Args: api_key: GeodesicAI API key (starts with gai_) state_vector: State vector dictionary, typically the state_vector field from a validate or get_execution_trace result. Returns: confidence: float in [0, 1] level: "high" / "medium" / "low" recommendation: text recommendation for the caller signals: per-signal contribution breakdown signal_weights: weights used in the composite. It is categorised as a Read tool in the Governance Platform MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on geometric_confidence? +

Register the Governance Platform MCP server in PolicyLayer and add a rule for geometric_confidence: 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 Governance Platform. Nothing to install.

What risk level is geometric_confidence? +

geometric_confidence is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit geometric_confidence? +

Yes. Add a rate_limit block to the geometric_confidence 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.

How do I block geometric_confidence completely? +

Set action: deny in the PolicyLayer policy for geometric_confidence. 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.

What MCP server provides geometric_confidence? +

geometric_confidence is provided by the Governance Platform MCP server (https://app.geodesiclabs.ai/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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