NeuroDynamic Audio and LLM APIs

Overview Schema Source Related Servers Discussions Admin

purchase_json

Purchase narration or LLM text using an owner-funded wallet by providing a unique purchase ID and confirmation; output is saved to your private state directory.

Instructions

Buy narration or LLM text using an owner-funded local wallet. Read schema and quote first. Supply a unique purchase_id once; reuse it after uncertainty, never invent a replacement. Saves output to the caller's private state directory. Narration body: input, voice. LLM body requires input, adult=true, third_party_processing=true, terms_version=2026-09-11-llm-v1 and optional max_tokens. Only assert these acknowledgements with the user's authority.

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": {
      "service": "<service>",
      "body": "<body>",
      "purchase_id": "<purchase_id>"
    },
    "name": "purchase_json"
  }
}

Input Schema

Name	Required	Description	Default
`body`	Yes
`service`	Yes
`purchase_id`	Yes
`confirm_purchase`	No

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Sep 15, 2026

TDQS

A4.5/5.0

Behavior4/5

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

Annotations already indicate readOnlyHint=false, destructiveHint=false, and idempotentHint=false. The description adds valuable behavioral context: the purchase is owner-funded, output is saved to the caller's private state directory, and acknowledgements must only be asserted with the user's authority. It does not contradict annotations.

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

Conciseness4/5

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

The description is dense but well-organized, front-loading the core action and then detailing requirements. Every sentence adds value, though the final sentence about acknowledgements could be clearer.

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

Completeness4/5

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

Given the tool's complexity (nested body object, multiple service types, idempotency concerns) and the presence of an output schema, the description covers the critical usage context well. It could mention confirm_purchase's role, but the overall guidance is strong.

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

Parameters4/5

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 explains the body structure for both narration and LLM services, and clarifies the purchase_id uniqueness requirement. It does not explain confirm_purchase, but the schema's default false and the description's emphasis on purchase_id reuse partially cover the semantics.

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

Purpose5/5

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

The description clearly states the tool's purpose: buying narration or LLM text using an owner-funded local wallet. It distinguishes the two service types (narration vs LLM) and names the required body fields for each, which differentiates it from siblings like quote and catalogue.

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

Usage Guidelines5/5

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

The description explicitly instructs the agent to read the schema and quote first, and to supply a unique purchase_id once, reusing it after uncertainty rather than inventing a replacement. It also specifies the exact required fields for LLM body, which is strong usage guidance.

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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