DatoQA

list_us_economic_indicators

Read-onlyIdempotent

Discover three official BLS US monthly series, original units, seasonal adjustment, latest periods and freshness. Rolling ten calendar years, not a full archive. CPI is an index, payroll employment counts jobs in thousands. Read source notes.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_us_economic_indicators"
  }
}

Input Schema

Name	Required	Description	Default
No arguments

Output Schema

Name	Required	Description
`notice`	Yes
`source`	Yes
`country`	Yes
`endpoint`	Yes
`indicators`	Yes
`requested_window`	Yes
`independently_verified`	Yes	Official-source checks are not independent factual corroboration.
`refresh_interval_seconds`	Yes
`max_collection_age_seconds`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedSep 28, 2026

changedOutput schema / $schema

Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"

First observedSep 27, 2026

TDQS

A3.6/5.0

Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive, closed-world, so the safety profile needs no restatement. The description earns credit for behavioral context annotations can't carry: the three-series scope, the original-units/seasonal-adjustment framing, that CPI is an index while payroll counts jobs in thousands, and that ten years is a hard window rather than a full archive.

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 compact sentences, scope and units front-loaded, no filler. The trailing 'Read source notes.' is terse and only marginally useful, keeping it just short of a 5.

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?

A simple no-arg list tool with an output schema, so return shape needn't be re-explained. The description covers resource, units, time window and caveats, which is close to complete; the only gap is not identifying its sibling alternatives.

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?

The tool takes zero parameters (empty object schema, 100% coverage), so the baseline of 4 applies. There is nothing for the description to clarify on the input side.

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?

The description names a specific verb ('Discover') and a precise resource ('three official BLS US monthly series'), plus what each carries (original units, seasonal adjustment, periods, freshness). It does not, however, differentiate itself from the many list/get economic-indicator siblings, so an agent still has to infer why this exists alongside list_economic_indicators or get_us_economic_indicators.

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?

It bounds scope ('rolling ten calendar years, not a full archive') and points at source notes, which hints at expectations, but names no alternative tool and gives no explicit when-to-use vs when-not condition. The selection between this and its sibling indicator tools is entirely left 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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