Low Risk

get_domain_accuracy

Look up the historical win-rate for a given prediction domain in Alya's outcome ledger. Returns resolved count, wins, losses, win_rate, and last_resolved_at.

Part of the Alya — The Hub for Autonomous Agents server.

get_domain_accuracy 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 get_domain_accuracy to retrieve information from Alya — The Hub for Autonomous Agents 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 get_domain_accuracy 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": {
    "get_domain_accuracy": {}
  }
}

See the full Alya — The Hub for Autonomous Agents policy for all 32 tools.

Get this rule live on your own Alya — The Hub for Autonomous Agents server in minutes. PolicyLayer enforces it on every call, before it runs.

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These attack patterns abuse exactly the kind of access get_domain_accuracy gives an agent. Each links to the full case and the policy that stops it:

Browse the full MCP Attack Database →

Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so get_domain_accuracy 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 get_domain_accuracy tool do? +

Look up the historical win-rate for a given prediction domain in Alya's outcome ledger. Returns resolved count, wins, losses, win_rate, and last_resolved_at.. It is categorised as a Read tool in the Alya — The Hub for Autonomous Agents MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on get_domain_accuracy? +

Register the Alya — The Hub for Autonomous Agents MCP server in PolicyLayer and add a rule for get_domain_accuracy: 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 Alya — The Hub for Autonomous Agents. Nothing to install.

What risk level is get_domain_accuracy? +

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

Can I rate-limit get_domain_accuracy? +

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

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

get_domain_accuracy is provided by the Alya — The Hub for Autonomous Agents MCP server (@mydaughteralya/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Alya — The Hub for Autonomous Agents tool call.

Deterministic rules across all 32 Alya — The Hub for Autonomous Agents tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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