dcl_evaluate_secrets
POST-ACTION Secret & Credential Leak Scan ($0.02). Regex-based scan across 8 categories (API keys, cloud credentials, tokens/JWTs, private keys, DB URLs, connection strings, env assignments, webhook secrets, internal endpoints with auth). Any finding results in NO_COMMIT.
This record as markdown: /tools/com-fronesislabs-dcl-trust-oracle/dcl-evaluate-secrets.md
What dcl_evaluate_secrets does on Dcl Trust Oracle
AI agents call dcl_evaluate_secrets to retrieve information from Dcl Trust Oracle 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 | Yes | Identifier of the agent that produced the response. |
response | string | Yes | The text to scan for exposed API keys, tokens, private keys, DB URLs, and other credentials. |
Parameters from the server's own tool schema.
Why dcl_evaluate_secrets is rated Low
Scans output for secrets without modifying, deleting, or executing code; purely detective.
From the tool's definition POST-ACTION scan, findings result in NO_COMMIT, no modification or deletion
Attacks that exploit this kind of access
The rule that runs dcl_evaluate_secrets 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_secrets, this is the rule to start with:
dcl_evaluate_secrets 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 Dcl Trust Oracle, apply this rule, and every dcl_evaluate_secrets call is checked against it from then on.
Questions about dcl_evaluate_secrets
POST-ACTION Secret & Credential Leak Scan ($0.02). Regex-based scan across 8 categories (API keys, cloud credentials, tokens/JWTs, private keys, DB URLs, connection strings, env assignments, webhook secrets, internal endpoints with auth). Any finding results in NO_COMMIT. It is categorised as a Read tool in the Dcl Trust Oracle MCP Server, which means it retrieves data without modifying state.
dcl_evaluate_secrets 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_secrets: 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_secrets 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 dcl_evaluate_secrets 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_secrets. 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_secrets 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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