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search_sellers

Find paid x402 data services AI agents can buy, inside one category, ranked. Use before paying any seller.

Input Schema

NameRequiredDescriptionDefault
qNotext to match in name or address
sortNoaccuracy ranks by the low end of the 95% range of paid answers judged correct
limitNo
cursorNo
categoryYescategory slug or its name in any of 19 languages, e.g. crypto-prices, 加密货币价格, 暗号資産の価格, cotización cripto (see list_categories)
answeringNo
max_priceNomax USDC per call
min_buyersNo
min_accuracyNokeep sellers whose 95% range of correct paid answers starts at or above this share (0 to 1)
tools_honouredNoAI chat sellers only: keep those whose checked calls passed an agent's tools to the model and never dropped them

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.9/5.0
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. It says results are 'ranked' but never states the default ranking, result shape, pagination behavior (a cursor param exists), or rate/cost limits, which are significant gaps for a 10-parameter search tool.

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 tight sentences, front-loaded with the core purpose and followed by the usage cue. Nothing is redundant, though the brevity comes at the cost of the behavioral detail noted elsewhere.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with 10 parameters, no annotations, no output schema, and partial schema coverage, this description is far too thin. An agent gets no sense of the returned result structure or pagination mechanics, which are essential for correct invocation.

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 60%, leaving limit, cursor, answering, and min_buyers undocumented in both schema and description. The description only reaffirms single-category scoping ('inside one category') and ranking, adding no meaning to the filter or sort parameters beyond what the schema already encodes.

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?

Names a specific verb ('Find') and resource ('paid x402 data services AI agents can buy'), and scopes it to a single category with ranking. It doesn't explicitly contrast itself with siblings like check_seller or list_categories, but the resource and domain are distinctive enough to separate it from them.

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?

The phrase 'Use before paying any seller' gives one concrete timing cue for invocation, which is more than nothing. However, it names no alternatives and doesn't clarify how this differs from check_seller when the agent already knows a seller, leaving the when-not condition to inference.

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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