dcl_evaluate_strict
STRICT Pre-Action Audit ($0.05). Runs the response against a broader, higher-bar "strict" policy: the union of all forbidden phrases from the default, anti-jailbreak, and safety policies (8 phrases total), with a 0.85 minimum-confidence threshold instead of the default policy's 0.7. Each matched ...
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What dcl_evaluate_strict does on Dcl Trust Oracle
AI agents call dcl_evaluate_strict to permanently remove resources in Dcl Trust Oracle, typically in cleanup and lifecycle workflows. It does its job in a single call, and there is no undo.
| Parameter | Type | Required | Description |
|---|---|---|---|
agent_id | string | Yes | Identifier of the agent that produced the response. |
response | string | Yes | The agent or LLM response text to audit. |
Parameters from the server's own tool schema.
Why dcl_evaluate_strict is rated Critical
An AI agent that decides to call dcl_evaluate_strict doesn't hesitate, doesn't double-check, and doesn't stop at one. Whatever it removes from Dcl Trust Oracle is gone. There is no undo for destructive operations.
Risk signalsBulk/mass operation — affects multiple targets
Attacks that exploit this kind of access
The rule that runs dcl_evaluate_strict safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Dcl Trust Oracle, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For dcl_evaluate_strict, this is the rule to start with:
dcl_evaluate_strict 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 Dcl Trust Oracle, apply this rule, and every dcl_evaluate_strict call is checked against it from then on.
Questions about dcl_evaluate_strict
STRICT Pre-Action Audit ($0.05). Runs the response against a broader, higher-bar "strict" policy: the union of all forbidden phrases from the default, anti-jailbreak, and safety policies (8 phrases total), with a 0.85 minimum-confidence threshold instead of the default policy's 0.7. Each matched phrase costs 0.4 confidence; if confidence falls below 0.85, or any phrase matches, the verdict is NO_COMMIT with reason listing every match found. Use this instead of dcl_evaluate_fast when the cost of a false COMMIT is high — e.g. before an irreversible or high-stakes agent action — since it catches jailbreak- and safety-adjacent phrasing that the plain default policy would miss. It is categorised as a Destructive tool in the Dcl Trust Oracle MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.
dcl_evaluate_strict accepts 2 parameters: agent_id, response. Required: agent_id, response. The full parameter table on this page comes from the server's own tool schema.
Register the Dcl Trust Oracle MCP server in PolicyLayer and add a rule for dcl_evaluate_strict: 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 Dcl Trust Oracle. Nothing to install.
dcl_evaluate_strict 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 dcl_evaluate_strict 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 dcl_evaluate_strict. 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.
dcl_evaluate_strict is provided by the Dcl Trust Oracle MCP server (https://mcp.fronesislabs.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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