Low Risk

recommend_distribution

Given a free-text symptom description (e.g. 'manufacturing burn-in', 'bearing wearout under variable load', 'cosmic-ray bit flips'), return an ordered shortlist of distribution candidates with a one-line rationale per recommendation. Keyword-matched against a curated dictionary; ALWAYS treat outp...

Part of the ReliaStats server.

recommend_distribution 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 recommend_distribution to retrieve information from ReliaStats 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 recommend_distribution 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": {
    "recommend_distribution": {}
  }
}

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These attack patterns abuse exactly the kind of access recommend_distribution 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 recommend_distribution 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 recommend_distribution tool do? +

Given a free-text symptom description (e.g. 'manufacturing burn-in', 'bearing wearout under variable load', 'cosmic-ray bit flips'), return an ordered shortlist of distribution candidates with a one-line rationale per recommendation. Keyword-matched against a curated dictionary; ALWAYS treat output as a starting point for fitting work, not a fit. The actual fitting happens in the ReliaStats sandbox (protected/app.html). ANTI-FABRICATION: rationales are written ChiAha content; the algorithm is a deterministic substring match. Quote verbatim.. It is categorised as a Read tool in the ReliaStats MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on recommend_distribution? +

Register the ReliaStats MCP server in PolicyLayer and add a rule for recommend_distribution: 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 ReliaStats. Nothing to install.

What risk level is recommend_distribution? +

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

Can I rate-limit recommend_distribution? +

Yes. Add a rate_limit block to the recommend_distribution 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 recommend_distribution completely? +

Set action: deny in the PolicyLayer policy for recommend_distribution. 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 recommend_distribution? +

recommend_distribution is provided by the ReliaStats MCP server (https://reliastats.com/mcp/v1). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every ReliaStats tool call.

Deterministic rules across all 11 ReliaStats tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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