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NeuroDynamic Audio and LLM APIs

NeuroDynamic Audio and LLM APIs

by Hy1ander
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

payment_status

Read-onlyIdempotent

Check saved purchase metadata and query payment recovery status for free. Find out if a purchase can be recovered without signing or paying.

Instructions

Read saved purchase metadata and, for LLMs, query payment recovery for free. Never signs or pays; cannot restore LLM output the merchant does not retain.

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": {
      "purchase_id": "<purchase_id>"
    },
    "name": "payment_status"
  }
}

Input Schema

NameRequiredDescriptionDefault
purchase_idYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.2/5.0
Behavior4/5

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

Annotations already mark it read-only, open-world, idempotent, and non-destructive. The description adds useful non-obvious caveats: it never signs or pays, and it cannot restore LLM output the merchant does not retain. This goes beyond the annotations without contradicting them.

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?

Two short sentences, with the core action front-loaded and constraints following. The phrasing is a little dense, but there is no wasted content.

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?

For a simple one-parameter read-only tool with an output schema and strong annotations, the caveats cover the main behavioral concerns. However, the description omits when to use this instead of sibling status/JSON tools and does not define purchase_id, so it is not fully self-contained.

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?

The schema has 0% description coverage for the single required purchase_id. The description does not explain the parameter format, provenance, or expected values beyond implying the tool reads saved purchase data, so it does not compensate for the missing schema description.

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?

The description states a specific action and resource: reading saved purchase metadata, with an additional LLM-specific payment recovery query. It is reasonably clear and distinct from siblings like purchase_json or budget_status, though it never explicitly names a sibling or says 'payment status'.

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

Usage Guidelines2/5

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

There is no guidance about when to select payment_status over siblings such as purchase_json, quote, or budget_status. The phrase 'for LLMs' hints at an audience, but it does not state conditions, prerequisites, or alternatives.

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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