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ExchangeRebel — pay-per-call APIs for AI agents (x402 on Solana)

books_search

Search books (Open Library, metadata only). $0.005 per call — USDC on Solana via x402 (over MCP: call without payment to get the PaymentRequired challenge, then retry with the payment at _meta["x402/payment"]). HTTP equivalent: GET https://exchangerebel.com/toll/books/search.

Input Schema

NameRequiredDescriptionDefault
qNoGeneral query
limitNo1-25, default 10
titleNoTitle terms
authorNoAuthor terms

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.4/5.0
Behavior4/5

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

Annotations say readOnlyHint=false, which looks odd for a 'metadata only' search, but the description explains the reason: the call is billable ($0.005 USDC on Solana via x402), so invoking it has a real side effect. It also discloses the two-step payment handshake and the HTTP equivalent, context the annotations cannot convey. This is detailed, but return shape and any rate/limit behavior on the paid endpoint are not described.

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?

Purpose is front-loaded in five words, then cost, then the payment retry protocol — a sensible priority order for an agent that must decide whether to spend money. The trailing HTTP-equivalent URL is useful but is the one element that could be trimmed without losing invocation-relevant information.

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 zero-required-parameter, four-field search with no output schema, the description covers the essential operational risk (cost and payment flow) but omits anything about result content or how many fields are matched. Given the crowded books_* sibling set, an agent could construct a valid call but not confidently pick this tool over its neighbors.

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 100%, so q, title, author and limit are already documented in the schema (including the 1-25 limit range and default of 10). The description adds no semantics about how these parameters combine or which fields are searched, so the baseline 3 applies.

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?

States a specific verb and resource ('Search books') and scopes it ('Open Library, metadata only'), so an agent knows it queries a bibliographic index rather than full text or files. It does not, however, distinguish itself from the many sibling lookup tools (books_title, books_author, books_isbn, books_works), so the agent cannot tell from the description alone which entry point to prefer.

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?

The description gives no when-to-use guidance and no exclusions; it never says whether this general search subsumes books_title/books_author or should be avoided when a specific identifier is known. The only operational instructions concern payment (call first, get PaymentRequired, retry with _meta["x402/payment"]), which is invocation mechanics rather than tool selection guidance.

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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