dcl_evaluate_quality
PRE-ACTION Content Quality & Drift Check ($0.03). Runs the "content_quality" policy: flags 12 absolutist or unverifiable-claim phrases (e.g. "guaranteed returns", "100% accurate", "studies show", "without a doubt") with a 0.85 minimum-confidence threshold — the highest bar of any single-policy to...
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What dcl_evaluate_quality does on Dcl Trust Oracle
AI agents call dcl_evaluate_quality 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 agent or LLM response text to check for quality and drift. |
Parameters from the server's own tool schema.
Why dcl_evaluate_quality is rated Low
Tool evaluates and flags content without modifying, deleting, or executing external operations.
From the tool's definition checks content, flags phrases, returns NO_COMMIT, analyzes output quality
Attacks that exploit this kind of access
The rule that runs dcl_evaluate_quality 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_quality, this is the rule to start with:
dcl_evaluate_quality 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_quality call is checked against it from then on.
Questions about dcl_evaluate_quality
PRE-ACTION Content Quality & Drift Check ($0.03). Runs the "content_quality" policy: flags 12 absolutist or unverifiable-claim phrases (e.g. "guaranteed returns", "100% accurate", "studies show", "without a doubt") with a 0.85 minimum-confidence threshold — the highest bar of any single-policy tool. Returns NO_COMMIT if any phrase matches or confidence falls below 0.85, with reason listing the matched phrase(s). Use this to catch overconfident or unsubstantiated claims in generated content — a different concern from jailbreak or safety phrasing — e.g. before publishing agent-written copy or reports. It is categorised as a Read tool in the Dcl Trust Oracle MCP Server, which means it retrieves data without modifying state.
dcl_evaluate_quality 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_quality: 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_quality 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_quality 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_quality. 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_quality 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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