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Glama

earnings_calendar

Retrieve upcoming US equity earnings announcement schedules with report dates, before/after-market timing, analyst EPS estimates, market cap, and prior-year actual EPS.

Instructions

[Trading Data API] US equity earnings announcement calendar: report date, before/after-market timing, analyst EPS estimate + count, market cap, and prior-year actual EPS — US equity earnings announcement calendar: report date, before/after-market timing, analyst EPS estimate + count, market cap, and prior-year actual EPS. Sourced live from Nasdaq's public calendar.

Example: /v1/earnings-calendar?date=2026-07-14&days=3

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateNoOptional. Start date YYYY-MM-DD (default: today).
daysNoOptional. Days to scan forward from date (default 1, max 7).
symbolNoOptional. Filter to one ticker within the scanned range.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.1

TDQS

C2.9/5.0
Behavior3/5

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

With no annotations, the description carries the full burden: it discloses the upstream source ('Sourced live from Nasdaq's public calendar') and the exact payload fields, which is genuinely useful. It omits any mention of auth requirements, rate limits, or freshness/latency guarantees in spite of advertising a 'live' feed.

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

Conciseness2/5

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

The core sentence is duplicated verbatim ('...US equity earnings announcement calendar: report date, before/after-market timing...'), wasting a large share of the text. The useful content (source, example) is present, but the repetition is a clear structural defect.

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

Completeness3/5

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

For a read-only fetch with full schema coverage and no output schema, the description is adequate: it tells the agent the domain, the source, and the returned fields. It falls short by never disambiguating against the similar macro_calendar sibling or noting any operational constraints.

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 description coverage is 100%, so all three optional parameters (date, days, symbol) are already documented with defaults and bounds in the schema. The description adds nothing beyond echoing date/days in the example URL, so the baseline 3 applies.

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 resource ('US equity earnings announcement calendar') and enumerates the returned data (report date, timing, EPS estimate + count, market cap, prior-year actual EPS), so an agent knows exactly what it fetches. It does not, however, distinguish itself from the sibling macro_calendar, leaving the boundary between the two calendars unstated.

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?

There is no when-to-use guidance and no alternative named — notably macro_calendar sits in the sibling list and is never contrasted. The only hint of usage is the embedded example URL, which shows syntax rather than selection criteria.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.