Low Risk

compute_availability

Given MTBF and MTTR (same time unit), return steady-state availability A = MTBF / (MTBF + MTTR). One-line closed-form, but worth a dedicated tool so LLMs don't fumble the identity (the most common mistake is conflating MTBF with MTTF and silently inflating availability by the MTTR). Use whenever ...

Part of the ReliaStats server.

compute_availability 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 compute_availability 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 compute_availability 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": {
    "compute_availability": {}
  }
}

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

Given MTBF and MTTR (same time unit), return steady-state availability A = MTBF / (MTBF + MTTR). One-line closed-form, but worth a dedicated tool so LLMs don't fumble the identity (the most common mistake is conflating MTBF with MTTF and silently inflating availability by the MTTR). Use whenever a user supplies an MTBF/MTTR pair and asks for availability. ANTI-FABRICATION: exact closed-form. 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 compute_availability? +

Register the ReliaStats MCP server in PolicyLayer and add a rule for compute_availability: 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 compute_availability? +

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

Can I rate-limit compute_availability? +

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

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

compute_availability 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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