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payanagent_discover

Search the PayanAgent marketplace — 24,000+ live x402 services (native offers + the whole x402 ecosystem in one catalog) plus agents and open requests — with a free-text query. Results include receipt-derived seller trust scores.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax results per bucket (default 50, max 200).
queryYesFree-text search query.
categoryNoOptional offer category filter.
offerTypeNo
maxPriceCentsNoOptional max offer price (cents).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed5 schema fields changed
    • removedInput schema / $schema
      Removed value: -"http://json-schema.org/draft-07/schema#"
    • removedInput schema / additionalProperties
      Removed value: -false
    • addedInput schema / properties / category / description
      Added value: +"Optional offer category filter."
    • addedInput schema / properties / maxPriceCents / description
      Added value: +"Optional max offer price (cents)."
    • addedInput schema / properties / offerType
      Added value: +{
      +  "enum": [
      +    "api",
      +    "download"
      +  ],
      +  "type": "string"
      +}
  2. First observed

TDQS

A4/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden. It adds behavioral context (receipt-derived trust scores, coverage of 24,000+ services) but does not disclose auth needs, rate limits, or result format. The description is adequate for a read-like search tool but could be richer.

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?

Two sentences, front-loaded with the core action and scope, no fluff. Every word adds value.

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?

For a search tool with 5 parameters and no output schema, the description adequately covers the main functionality and a key output feature (trust scores). It does not explain bucket behavior or result structure, but the context is sufficient for typical use.

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

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is high (80%), so the baseline is 3. The description adds minimal parameter-specific meaning beyond the schema (e.g., 'per bucket' hints at limit). It does not significantly augment understanding of parameters like maxPriceCents or category beyond what the schema provides.

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 it searches the PayanAgent marketplace, listing specific content types (24,000+ services, agents, open requests) and a free-text query. This effectively distinguishes it from sibling tools like payanagent_list_offers or payanagent_agent, which target narrower subsets.

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

Usage Guidelines4/5

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

The description implies this is for broad discovery across multiple categories, but does not explicitly state when to use it versus siblings or provide exclusions. However, the context of a general marketplace search is clear, offering adequate guidance despite lacking explicit 'when-not-to-use' language.

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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