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genpark-voice-turn-taking-endpoint-detector-skill

genpark-voice-turn-taking-endpoint-detector-skill

Official
by Alpha-Park
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

calibrate_acoustic_thresholds

Adjust voice activity detection thresholds from measured ambient decibel frames to separate complete utterances from pause-filled partial turns.

Instructions

calibrate acoustic thresholds

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "ambient_frames_db": "<ambient_frames_db>"
    },
    "name": "calibrate_acoustic_thresholds"
  }
}

Input Schema

NameRequiredDescriptionDefault
ambient_frames_dbYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.1

TDQS

D1.3/5.0
Behavior1/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full behavioral burden, yet it discloses nothing about side effects, whether calibration mutates state, what permissions are needed, or how the ambient frames are consumed. The four-word description leaves every behavioral question unanswered.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The text is short, but its brevity reflects under-specification rather than tight writing. It is front-loaded only because there is nothing to front-load.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

A one-parameter tool with no annotations and no output schema still needs to explain the input's meaning and the operation's effect; the description provides neither. It is entirely inadequate for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The single required parameter 'ambient_frames_db' has 0% schema description coverage, and the description contributes no meaning about units, expected array length, or how the frames inform calibration. Nothing compensates for the documentation gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose2/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description is a verbatim lowercase restatement of the tool name 'calibrate_acoustic_thresholds' and adds no specificity about what is being calibrated or against what. It gives no way to distinguish this from siblings like analyze_turn_status or run_benchmark_turn_detection.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines1/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no indication of when this tool should be used, what preconditions apply, or how it differs from the sibling tools. An agent has no basis to choose it over its siblings.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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