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x402-assistant

x402-assistant: 平台自营 x402 导购——agent 付 USDC 用自然语言描述需求,返回匹配的可用服务推荐(含 id/价格/理由)。

Input Schema

NameRequiredDescriptionDefault
queryNo
promptNo
questionNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changed
    • removedInput schema / properties / prompt / description
      Removed value: -"Prompt to process"
    • removedInput schema / properties / query / description
      Removed value: -"Query to process"
    • removedInput schema / properties / question / description
      Removed value: -"Question to process"
  2. Changed3 schema fields changed
    • addedInput schema / properties / prompt
      Added value: +{
      +  "description": "Prompt to process",
      +  "type": "string"
      +}
    • addedInput schema / properties / query
      Added value: +{
      +  "description": "Query to process",
      +  "type": "string"
      +}
    • addedInput schema / properties / question
      Added value: +{
      +  "description": "Question to process",
      +  "type": "string"
      +}
  3. First observed

TDQS

B3.2/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It usefully discloses that the call is paid (USDC) and that the return contains recommended services with id, price, and reason — meaningful context beyond the schema. It omits cost magnitude, payment mechanics, and whether recommendations are guaranteed, so disclosure is partial.

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?

A single tightly-packed sentence that front-loads the purpose and folds in payment, input style, and return shape. The leading 'x402-assistant:' repetition of the tool name adds minor noise but the sentence is otherwise efficient.

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?

No output schema exists, and the description does describe the return contents (id/price/reason), which helps. But for a paid tool with three interchangeable undocumented parameters and a required-looking payment flow, the definition leaves an agent guessing about input selection and cost, so completeness is only adequate.

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 coverage is 0% and the schema is non-empty, so the description must compensate. It only implies that a natural-language description is supplied, without mapping to the three ambiguous parameters (query, prompt, question), which all appear interchangeable. An agent has no way to know which field to populate or whether all are needed.

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 verb+resource: a platform-run x402 shopping guide that takes a natural-language need and returns matching service recommendations with id/price/reason. That is concrete and distinguishable in kind from the numerous single-function x402-* siblings. However, it never names or differentiates from plausible alternatives like service_discovery or task-router, which appear in the sibling list.

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

Usage Guidelines3/5

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

It conveys that the agent must pay USDC and describe needs in natural language, which implies the usage context (a paid discovery step before invoking a service). It does not state when to prefer this over service_discovery or give any exclusion conditions, so guidance remains implied rather than explicit.

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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