benchmark_voice_latency
Calculate theoretical latency for one or more voice pipeline configurations. Breaks down STT, LLM (first token + completion), and TTS latency. Shows total and user-perceived latency (with streaming optimizations). Rates each config as excellent/good/acceptable/poor. Knowledge-based, no live measu...
This record as markdown: /tools/io-github-homenshum-nodebench/benchmark-voice-latency.md
What benchmark_voice_latency does on Nodebench
AI agents call benchmark_voice_latency to retrieve information from Nodebench without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
Why benchmark_voice_latency is rated Low
This is a computational analysis tool that takes voice pipeline configurations as input and returns calculated latency metrics and ratings. It has no side effects, does not modify any data, does not execute external operations, and does not affect system state. It reads configuration parameters, performs mathematical calculations, and returns results—characteristic of a Read category tool.
From the tool's definition The tool 'Calculate theoretical latency for one or more voice pipeline configurations' and 'Shows total and user-perceived latency' indicates data retrieval and analysis.
Attacks that exploit this kind of access
The rule that runs benchmark_voice_latency safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Nodebench, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For benchmark_voice_latency, this is the rule to start with:
benchmark_voice_latency is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Nodebench, apply this rule, and every benchmark_voice_latency call is checked against it from then on.
Questions about benchmark_voice_latency
Calculate theoretical latency for one or more voice pipeline configurations. Breaks down STT, LLM (first token + completion), and TTS latency. Shows total and user-perceived latency (with streaming optimizations). Rates each config as excellent/good/acceptable/poor. Knowledge-based, no live measurements. It is categorised as a Read tool in the Nodebench MCP Server, which means it retrieves data without modifying state.
Register the Nodebench MCP server in PolicyLayer and add a rule for benchmark_voice_latency: 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 Nodebench. Nothing to install.
benchmark_voice_latency is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the benchmark_voice_latency 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.
Set action: deny in the PolicyLayer policy for benchmark_voice_latency. 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.
benchmark_voice_latency is provided by the Nodebench MCP server (nodebench-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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