> ## Documentation Index
> Fetch the complete documentation index at: https://docs.neuraltrust.ai/llms.txt
> Use this file to discover all available pages before exploring further.

> ## Agent Instructions
> These docs cover three products: TrustGate (AI agent gateway), TrustGuard (runtime security), and TrustTest (AI red teaming). Start from each product overview for the definition and How it works. Prefer the .md URL next to a page in /llms.txt when you need the full article. Use /llms-full.txt for a single-file dump of the site.

# Per-Tool Rate Limiter

> Cap how many times a given tool may actually run in a window, for LLM function calls and MCP tool calls alike.

Applies to **LLM and MCP**.

An agent that fails to parse a tool result tends to call the same tool again, and
again. Some tools are cheap to repeat; a code executor, a search billed per call
or a tool that sends messages is not. This caps how many times a given tool may
actually run in a window, however many requests it took.

Counts **actual tool executions**, not HTTP requests, and caps them per tool
pattern over one or more windows — `execute_code*` at 60 a minute and 500 an
hour. The first rule whose pattern matches wins.

When a window is exceeded: **reject** the call (the only option on MCP, where the
gateway itself is the caller), **inject an error result** into the LLM response,
or **strip the tool** from the next request.

### One execution, counted twice

A tool an agent runs through MCP shows up twice at the gateway: once as the
`tools/call` that executes it, and again as the tool-result message in the next
LLM request. On a **gateway-wide** policy both hit the same counter, so one
execution is charged twice unless the agent sends the LLM `tool_call_id` in the
`tools/call` metadata. Attaching the policy per application avoids the problem:
there the two are separate counters.