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agent-market-network

describe_network

Read-onlyIdempotent

Describe market capabilities, security, and payment boundaries.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNo
errorNo
fieldNo
statusNo
messageNo
constraintNo
error_typeNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed8 schema fields changed
    • addedOutput schema / properties / constraint / anyOf
      Added value: +[
      +  {
      +    "type": "string"
      +  },
      +  {
      +    "type": "null"
      +  }
      +]
    • removedOutput schema / properties / constraint / type
      Removed value: -"string"
    • addedOutput schema / properties / error_type / anyOf
      Added value: +[
      +  {
      +    "type": "string"
      +  },
      +  {
      +    "type": "null"
      +  }
      +]
    • removedOutput schema / properties / error_type / type
      Removed value: -"string"
    • addedOutput schema / properties / field / anyOf
      Added value: +[
      +  {
      +    "type": "string"
      +  },
      +  {
      +    "type": "null"
      +  }
      +]
    • removedOutput schema / properties / field / type
      Removed value: -"string"
    • addedOutput schema / properties / message / anyOf
      Added value: +[
      +  {
      +    "type": "string"
      +  },
      +  {
      +    "type": "null"
      +  }
      +]
    • removedOutput schema / properties / message / type
      Removed value: -"string"
  2. First observed

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already indicate the tool is read-only, idempotent, and non-destructive. The description adds high-level context on what is described (capabilities, security, payment boundaries) but does not disclose additional behavioral traits beyond the annotations.

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?

The description is a single sentence that is front-loaded with the verb 'Describe'. It is concise and free of extraneous information.

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 no parameters and a well-defined annotation set, the description provides a reasonable overview. However, it could mention the output schema or the nature of the returned data for completeness.

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?

There are no parameters, so schema coverage is trivially 100%. The description adds meaning by specifying the subject areas covered, which is appropriate for a parameterless tool.

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 the tool describes market capabilities, security, and payment boundaries. It is clear about the general subject matter but does not explicitly differentiate from sibling tools like 'network_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?

No guidance is provided on when to use this tool versus alternatives. The description implies usage for describing network aspects, but lacks explicit context or exclusions.

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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