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econ_series

US economic series: latest print, revisions, surprise vs labeled expectation. One tracked US economic series (BLS/BEA/Fed/Census via FRED/ALFRED): the latest print with first-release vs latest value (revisions never masquerade as print-day numbers), surprise against a labeled expectation — market-implied when a matching prediction market exists, else a trend model — the next scheduled release date, and a 12-observation mini-series. Public-domain federal data only. [HTTP: GET /v1/econ/:series · price $0.02 via x402 · docs https://x402-factory.com/docs/econ.series]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
seriesYesSeries slug, e.g. cpi, core-cpi, payrolls (GET /v1/econ/calendar lists all)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior4/5

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

With no annotations, the description carries the burden and does so well: it discloses the data provenance (public-domain federal data only), the payment requirement ($0.02 via x402), and the substantive semantics (first-release vs latest value, revisions never shown as print-day numbers, market-implied vs trend-model surprise). It omits rate limits or caching/refresh behavior, but the core behavioral profile is present.

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 payoff, then the data semantics, then the endpoint/pricing/docs footer. Dense but not padded, though the parenthetical asides make it read longer than needed for a one-parameter tool.

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

Completeness4/5

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

No output schema exists, and the description compensates by enumerating the returned fields (latest print, first-release vs latest, surprise, next release date, 12-observation mini-series). The only real gap is sibling differentiation against the per-series variants.

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?

Single parameter with 100% schema description coverage, so the schema already explains the 'series' slug, gives examples, and points at the calendar endpoint. The description adds the notion that only one series is tracked per call but no extra syntax or format detail.

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 (retrieve) and resource (one tracked US economic series) plus source lineage (BLS/BEA/Fed/Census via FRED/ALFRED). However, it never distinguishes itself from the near-identical siblings econ_series_cpi, econ_series_payrolls, etc., which an agent must choose between.

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?

No when-to-use statement, no routing to alternatives. The description implies the tool is the generic parametrized lookup but is silent on why one would pick it over econ_series_cpi or econ_series_payrolls, and only the schema mentions econ_calendar for enumerating slugs.

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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