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NeuroDynamic Audio and LLM APIs

NeuroDynamic Audio and LLM APIs

by Hy1ander
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

transcribe_file

Transcribe audio files up to 60 seconds or 12 MiB via paid purchase. Provide the filename and purchase ID to convert speech to text.

Instructions

Buy transcription of a caller-provided audio file (60 seconds/12 MiB maximum). Filename must be a basename within owner-configured NEURODYNAMIC_INPUT_DIR; file must be mode 0600. It is uploaded only for an explicit purchase. Never provide a path outside that directory.

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": {
      "filename": "<filename>",
      "purchase_id": "<purchase_id>"
    },
    "name": "transcribe_file"
  }
}

Input Schema

NameRequiredDescriptionDefault
filenameYes
languageNoen
purchase_idYes
confirm_purchaseNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.7/5.0
Behavior4/5

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

Goes beyond annotations by disclosing that this operation triggers a purchase/upload, requires a specific file mode and directory, and must not be used with paths outside that directory. It is consistent with readOnlyHint=false and does not contradict any annotation.

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

Conciseness5/5

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

Three dense sentences with no filler. Purpose, limits, security constraints, and the path warning are all front-loaded and each sentence earns its place.

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

Completeness3/5

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

Covers purpose, file constraints, and purchase trigger well, and the output schema likely covers return values. However, the purchase workflow parameters are poorly explained, leaving an agent uncertain how to properly supply purchase_id and confirm_purchase.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate. It richly documents filename constraints, but says nothing about how purchase_id originates or that confirm_purchase must be true to execute the purchase; language is also undocumented. The 'explicit purchase' line only weakly covers confirm_purchase.

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

Purpose4/5

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

States the exact action ('Buy transcription') and resource ('caller-provided audio file') with size/duration limits. It does not explicitly name sibling alternatives, but the buy-transcription scope is clearly distinct from catalogue, quote, payment_status, and budget_status.

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

Usage Guidelines4/5

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

Gives clear operating conditions: the file must be within an owner-configured directory, mode 0600, and uploaded only for an explicit purchase. It does not explicitly route to alternatives or describe the purchase workflow, but the context is sufficient for basic selection.

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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