Low Risk

estimate_cost_batch

Estimates costs for multiple LLM tasks in a single call. Each task can provide prompt_text, a task description, or explicit token counts. Returns per-task token-resolution metadata, aggregate totals, and the cheapest context-compatible model for the whole batch.

Risk signalsHigh parameter count (13 properties)

Part of the TokenOracle server.

estimate_cost_batch 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 estimate_cost_batch to retrieve information from TokenOracle 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 estimate_cost_batch 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": {
    "estimate_cost_batch": {}
  }
}

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

Estimates costs for multiple LLM tasks in a single call. Each task can provide prompt_text, a task description, or explicit token counts. Returns per-task token-resolution metadata, aggregate totals, and the cheapest context-compatible model for the whole batch.. It is categorised as a Read tool in the TokenOracle MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on estimate_cost_batch? +

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

What risk level is estimate_cost_batch? +

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

Can I rate-limit estimate_cost_batch? +

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

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

estimate_cost_batch is provided by the TokenOracle MCP server (VictoryInTech/TokenOracle-MCP). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every TokenOracle tool call.

Deterministic rules across all 9 TokenOracle tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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