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

macro_unemployment

US unemployment series (BLS, public domain). $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/macro/unemployment.

Input Schema

NameRequiredDescriptionDefault
endNoEnd period
startNoStart period

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?

Annotations declare openWorldHint=true and readOnlyHint=false, so the description's job is to explain why a data fetch is non-read-only — and it does: each call costs $0.005 in USDC on Solana, requiring an x402 challenge-then-retry handshake. That is genuinely valuable behavioral context an agent cannot infer from the annotations, though it omits coverage range, update cadence, and units.

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?

Three tightly packed sentences, front-loaded with what the series is and immediately followed by cost and the payment protocol. The x402 parenthetical is long but every clause is operationally necessary; nothing is filler.

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?

With no output schema, the description should at least signal the shape of the return (observations, units, frequency). It thoroughly covers cost and payment but leaves the response format and date syntax undocumented, which is a real gap for a first-call experience.

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%, so baseline is 3, but the schema descriptions are only 'Start period' and 'End period' with no format. The tool description adds nothing about whether these are ISO dates, years, or YYYY-MM, which is the exact ambiguity an agent needs resolved before its first call.

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 the specific resource (US unemployment series, BLS source) with enough topic specificity to separate it from siblings like macro_cpi, macro_payrolls, and macro_fed_rate. The retrieval verb is implied rather than stated, but for a series-fetch tool the resource naming carries the meaning.

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?

There is no explicit when-to-use or when-not-to-use guidance relative to macro_cpi/macro_payrolls, nor any statement of prerequisites such as date format or data frequency. The payment mechanics tell the agent how to invoke but not when this tool is the right choice over its macro siblings.

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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