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state_gdp_series

US Bureau of Economic Analysis state GDP series: real and current-dollar GDP by year for one state. $0.005 per call via x402 (USDC on Base); response includes a provenance chain and an Ed25519 attestation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
endNo
startNo
entityNo
paymentNoLegacy: base64 x402 payment header value. Prefer _meta["x402/payment"]; omit for a free quote.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / payment / description
      Previous value: -"Encoded x402 X-PAYMENT header value. Omit to receive the payment requirements (free quote)."New value: +"Legacy: base64 x402 payment header value. Prefer _meta[\"x402/payment\"]; omit for a free quote."
  2. First observed

TDQS

B3.4/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does notable work: it discloses pricing ($0.005/call via x402 on USDC/Base) and response trust features (provenance chain, Ed25519 attestation). It omits rate limits, retry/payment-failure behavior, and confirmation that the operation is read-only, but the cost and attestation details are genuinely useful context.

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 tightly packed sentences with the core subject front-loaded and no filler. Dense but appropriate; every clause adds 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 paid data-series tool with no output schema and no annotations, the description adequately covers what is returned (GDP types, per-state, per-year) plus payment and attestation, but omits parameter formats, pagination, and any usage conditions, leaving real gaps an agent would want filled.

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 only 25% (only 'payment' is documented), so the description must compensate. It loosely maps 'by year' to start/end and 'for one state' to entity, but gives no format details (e.g., state FIPS/abbreviation for entity, date format for start/end), leaving the two temporal params and entity largely undocumented.

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 resource (US BEA state GDP series), scope (real and current-dollar GDP, by year, for one state), and source. An agent can clearly tell what it returns, though it does not explicitly differentiate itself from sibling series tools like electricity_retail_series or cpi_us_monthly.

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?

There is no explicit when-to-use or when-not-to-use guidance, and no alternative tool is named. The mention of cost and payment describes mechanics rather than selecting conditions for the tool, leaving usage entirely 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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