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US macro indicators

macro_series

US macroeconomic series (CPI, unemployment, fed funds, 10-year treasury, real GDP). Pass an id for one series, omit to list what's available. Paid: call without x_payment to receive this call's exact terms (amount, asset, network), sign them, then call again with x_payment. The free pricing tool lists every price at once.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNoSeries id; omit to list available series
x_paymentNoOptional signed x402 payment payload (base64, what the X-PAYMENT header carries). Omit to receive the exact payment terms; sign them (e.g. @x402/fetch) and call again with this argument to settle and get the data.

TDQS

A4.7/5.0
Behavior4/5

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 discloses the paid nature and the two-step payment process, which is a key behavioral trait. It does not detail error handling or output format, but for a listing/data tool, this is sufficient. The payment flow is transparently explained.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences, front-loaded with the main purpose, then usage, then payment. No wasted words. Each sentence earns its place.

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

Completeness5/5

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

For a tool with two optional parameters and a payment flow, the description covers all necessary context: available data types, how to retrieve a single series, how to list all, and the exact payment protocol. It is complete and self-contained.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3. The description adds value by explaining the semantic difference between passing an id vs omitting it, and elaborating the x_payment parameter's role in the payment flow beyond the schema's description. It reinforces and clarifies parameter usage.

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?

The description clearly states the tool provides US macroeconomic series (CPI, unemployment, fed funds, 10-year treasury, real GDP) and explains the two modes: pass an id for one series, omit to list available series. This is a specific verb+resource, and the mention of the pricing tool distinguishes it from siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicit usage guidance is provided: how to use id (pass/omit), and the payment flow (call without x_payment to get terms, sign, then call again with x_payment). It also explicitly points to an alternative: 'The free `pricing` tool lists every price at once.'

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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TDQS

A4.2/5.0
Disambiguation5/5

Each tool targets a distinct data area or action: coverage vs find_data vs request_data are clearly separate (metadata, search, and suggestion box), and the three holdings tools (holdings_changes, manager_holdings, security_holders) each address a different question (changes, portfolio, owners). No two tools have ambiguous boundaries.

Naming Consistency5/5

All tool names use consistent lowercase snake_case (coverage, find_data, fx_rate, request_data, etc.). While some are verb phrases and others are noun phrases, the naming style is uniform and predictable, making it easy to guess tool purposes.

Tool Count5/5

Twelve tools is a well-scoped size for a financial data API server. Each tool covers a distinct data domain, and there is no excessive redundancy or crowding. The count is within the ideal 3-15 range.

Completeness4/5

The tool set covers a broad range of financial data needs: SEC filings, holdings, insider activity, IPO, macro, and FX. Minor gaps exist (e.g., no direct company fundamentals or full filing text), but the request_data tool provides a path to fill missing datasets, so agents are not at a dead end.

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