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

news_search

Search global news coverage (GDELT). $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/news/search.

Input Schema

NameRequiredDescriptionDefault
qYesQuery
daysNoLookback days
langNoLanguage filter
limitNoResult limit

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior4/5

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

Adds substantial context the annotations do not carry: per-call pricing ($0.005 USDC on Solana), the x402 challenge-and-retry payment flow, and the underlying HTTP endpoint. This also explains why readOnlyHint=false — the call involves a payment side effect — so annotations and description are coherent.

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?

Front-loaded with the purpose, then payment mechanics and endpoint in compact clauses. Every sentence carries operational weight, though the x402 retry instructions are dense enough that an agent could mis-parse the _meta key syntax on first read.

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?

There is no output schema, and the description never says what a search returns (article list, clusters, fields, pagination). For a monetized search endpoint where the result shape determines follow-up calls, this is a meaningful gap, even though payment behavior is well covered.

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 coverage is 100% but the parameter descriptions are terse ('Query', 'Lookback days', 'Language filter', 'Result limit'), and the tool description adds nothing about formats (e.g. days as string, query syntax, language codes). Baseline 3 is appropriate since the schema does the work without compensating detail.

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?

States a specific verb and resource ('Search global news coverage (GDELT)') so the agent knows exactly what the tool does. It could be sharper against siblings like gdelt_news_clusters or news_trending, but the GDELT label already distinguishes the general news-search scope.

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?

Explains the payment workflow but gives no guidance on when to use this versus gdelt_news_clusters, news_trending, news_timeline, or cited_answer_search. The agent must infer selection from the name alone.

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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