Low Risk

optimize_prompt

Score AND optimize any LLM prompt using PQS. Returns the original score, an optimized version of the prompt, and dimension-by-dimension breakdown across 8 quality dimensions based on PEEM, RAGAS, G-Eval, and MT-Bench frameworks. Costs $0.025 USDC via x402. Use this when you want to improve a prom...

Handles credentials or secrets (api_key)

Part of the Pqs MCP server. Enforce policies on this tool with Intercept, the open-source MCP proxy.

AI agents call optimize_prompt to retrieve information from Pqs 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 optimize_prompt 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.

io-github-onchainaiintel-pqs-mcp-server.yaml
tools:
  optimize_prompt:
    rules:
      - action: allow

See the full Pqs policy for all 3 tools.

Tool Name optimize_prompt
Category Read
MCP Server Pqs MCP Server
Risk Level Low

Agents calling read-class tools like optimize_prompt have been implicated in these attack patterns. Read the full case and prevention policy for each:

Browse the full MCP Attack Database →

Other tools in the Read risk category across the catalogue. The same policy patterns (rate-limit, allow) apply to each.

What does the optimize_prompt tool do? +

Score AND optimize any LLM prompt using PQS. Returns the original score, an optimized version of the prompt, and dimension-by-dimension breakdown across 8 quality dimensions based on PEEM, RAGAS, G-Eval, and MT-Bench frameworks. Costs $0.025 USDC via x402. Use this when you want to improve a prompt before running it.. It is categorised as a Read tool in the Pqs MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on optimize_prompt? +

Add a rule in your Intercept YAML policy under the tools section for optimize_prompt. You can allow, deny, rate-limit, or validate arguments. Then run Intercept as a proxy in front of the Pqs MCP server.

What risk level is optimize_prompt? +

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

Can I rate-limit optimize_prompt? +

Yes. Add a rate_limit block to the optimize_prompt rule in your Intercept 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 optimize_prompt completely? +

Set action: deny in the Intercept policy for optimize_prompt. 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 optimize_prompt? +

optimize_prompt is provided by the Pqs MCP server (pqs-mcp-server). Intercept sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Let agents act without letting them run wild.

Deterministic policy on every MCP tool call. Per-identity grants. Full audit log.

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