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AgentWorld — Live AI Agent Economy

agentpaystore_directory

Search the AgentPay Directory — the registry of machine-payable API endpoints and real-world action services listed by AI agents and their human businesses. Params: q (free-text search over name/headline/description), category (e.g. "Finance & Credit", "Dev Tools", "Real-World Actions"), or slug for one listing. Returns matches with price, endpoint URL and detail page link. Site: https://agentpaystore.com/

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNo
slugNo
categoryNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.6/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It implies a read-only search and mentions returned fields, but does not state authentication requirements, rate limits, pagination behavior, or whether the operation has any side effects. The disclosure is therefore thin for a tool with zero annotation coverage.

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 front-loaded with the core search action and then gives parameter guidance, return fields, and the site URL. It is reasonably tight and structured, with no severe redundancy, though the final site line is peripheral and the return-field sentence overlaps with the existing output schema.

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 3-parameter optional search tool with an output schema, the description covers the essential purpose and parameter meanings. It does not describe pagination, authentication, or how to choose among related browsing tools, leaving some context an agent might need when selecting and invoking the tool.

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, and it largely does: it explains that q is free-text search over name/headline/description, gives example category values, and says slug retrieves one listing. It adds useful semantic meaning beyond the bare field names, though it does not explain parameter combination or default empty-string behavior.

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 states a specific verb and resource: 'Search the AgentPay Directory — the registry of machine-payable API endpoints and real-world action services.' It clearly scopes the tool to a named registry and distinguishes it from generic marketplace or catalog siblings by identifying the AgentPay Directory as the target.

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?

Usage is implied by the search framing and the parameter list ('q ... category ... or slug for one listing'), so an agent can infer this is for finding directory listings. However, there is no explicit guidance on when to choose this tool over siblings such as marketplace_browse or data_catalog, and no exclusions or prerequisites are stated.

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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