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List market metrics

list_market_metrics
Read-only

Catalog of macro GA market metrics Windsock tracks (stable identifiers, labels, units, and whether each supports forecasting). Discover valid metric names before calling get_market_metric.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYes
metaYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, destructiveHint=false, and openWorldHint, so the safety profile is covered. The description adds useful behavioral context beyond that: the identifiers are stable and each entry flags forecasting support, telling the agent this is a durable reference catalog rather than a dynamic result set. Return-format details are omitted but are covered by the output schema.

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?

Two sentences, both front-loaded: what the catalog contains first, then the actionable ordering advice. No filler, no restatement of the title.

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?

An output schema exists, so the description need not explain return values, and with zero parameters there is no input semantics to document. The description covers purpose, contents, and the workflow relationship to get_market_metric, which is everything an agent needs to call it correctly.

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, which is the baseline 4 case. There is nothing for the description to clarify about inputs, and the empty schema is consistent with the described no-argument catalog 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?

States a specific verb and resource ('Catalog of macro GA market metrics Windsock tracks') and enumerates the fields returned (identifiers, labels, units, forecasting support). It clearly separates itself from get_market_metric, but does not distinguish itself from the sibling list_market_categories, which an agent could plausibly confuse it with.

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

Usage Guidelines4/5

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

Gives explicit sequencing guidance: 'Discover valid metric names before calling get_market_metric.' This is a clear when-to-use rule tied to a named sibling. It lacks any when-not guidance or differentiation from list_market_categories, so it stops short of a 5.

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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