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Get the economic calendar

macro_calendar
Read-onlyIdempotent

Return economic events in chronological order for a date range, with optional country and impact filters.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoThe maximum number of results to return.
impactNo
countryNo
end_dayYesA calendar day in YYYY-MM-DD format.
start_dayYesA calendar day in YYYY-MM-DD format.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYes
metaYes
billingYes
warningsYes

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, openWorldHint=true, and destructiveHint=false, covering the safety profile. The description adds the chronological ordering behavior and filter semantics, which is useful beyond annotations. However, it doesn't disclose pagination behavior, timezone handling, or whether both start/end days are inclusive, which would be relevant for a date-range query tool.

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?

Single sentence, front-loaded with the primary function (return economic events), then scope (chronological, date range) and features (filters). No wasted words and reasonably structured, though it could enumerate the filter options more explicitly.

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?

This is a moderate-complexity list/query tool with a good output schema and strong annotations. For a filtered calendar listing, the description covers the essential purpose and filters. Given the output schema exists and annotations are comprehensive, the description is adequate. Minor gaps around limit semantics and default behavior don't significantly impair usability.

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 60%, and the required parameters (start_day, end_day) have schema descriptions mentioning YYYY-MM-DD format. The description adds the semantic of chronological ordering but doesn't clarify parameter semantics beyond what the schema provides. The impact and country filters are well-described in the schema with enum/pattern constraints. The limit parameter is documented in schema. Baseline 3 is appropriate since the description doesn't meaningfully extend schema explanations.

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 states a specific verb+resource (return economic events) with clear scope (chronological order, date range) and mentions optional filters (country, impact). It clearly distinguishes from sibling tools like macro_indicator and macro_current_conditions which focus on single data points rather than calendar events. Purpose is clear though it doesn't explicitly name an alternative.

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

Usage Guidelines3/5

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

The description implies usage for retrieving economic events in a date range but gives no explicit when/when-not guidance or exclusion criteria. Sibling tools like macro_indicator and macro_current_conditions suggest alternative tools exist for specific indicators, but the description doesn't clarify when to choose this over those alternatives. Context is implied but not stated explicitly.

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

A3.7/5.0
Disambiguation5/5

Each tool targets a distinct resource-action combination (catalog items, datasets, macro data, market data, news, politics, account). Even within the market_ prefix, tools are clearly separated by resource type (quote, fundamentals, earnings, ratings, profile). No two tools appear to perform the same operation.

Naming Consistency4/5

The naming follows a consistent noun_verb pattern with domain prefixes: catalog_, datasets_, macro_, market_, news_, politics_. The verb style is consistent (describe, list, search, request, submit, return-type verbs like indicator and quote). Slight deviation with account_request_upgrade vs account_upgrade_status, and some verbs double as noun forms (quote, indicator, preview), but overall the convention is predictable.

Tool Count4/5

At 28 tools, the count is on the high side, but it serves a broad data platform spanning seven distinct domains (catalog, datasets, macro, market, news, politics, account). Each domain earns multiple tools to cover its surface, and the domains are broad enough to justify the volume. Slightly heavy, but reasonable given the scope.

Completeness4/5

The surface covers the full discovery-to-delivery workflow for data: list, describe, preview, request (catalog), plus direct dataset access. Market data has symbols search, quotes, price history, fundamentals, earnings, ratings, ETFs, and profile. Minor gaps include no bulk quote or multi-ticker endpoints, and there's no tool for reading an existing catalog request's status, but core workflows are well-covered.

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