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Glama

market_clock

Check US equities market status: whether it's open, next open/close times, and upcoming sessions via Alpaca. Crypto trades 24/7 and is unaffected.

Instructions

[Trading Data API] US equities market clock (is_open, next_open/close) + upcoming sessions, via Alpaca — US equities market clock (is_open, next_open/close) + upcoming sessions, via Alpaca. Crypto endpoints are 24/7 and unaffected.

Example: /v1/market-clock

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNoOptional. Upcoming session days to include (default 3, max 30; 0 to omit).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.1

TDQS

B3.2/5.0
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 data source (Alpaca) and that the tool is scoped to equities rather than crypto, and the read-only nature is clear from 'clock'. It omits any mention of auth requirements, rate limits, failures at session boundaries, or timezone semantics for next_open/close.

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 repeated verbatim ('US equities market clock (is_open, next_open/close) + upcoming sessions, via Alpaca' appears twice), wasting roughly half the text. The endpoint example and the crypto caveat are useful, but the duplication is a structural defect in an otherwise short description.

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?

With no output schema, the description must convey the return shape, and it does list the key fields (is_open, next_open/close) plus upcoming sessions. It does not explain the structure of the upcoming-sessions array or how next_open/close are formatted, so an agent still has gaps for a data-returning tool.

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?

There is a single optional parameter with 100% schema description coverage, including default, max, and the 0-to-omit behavior, so the description adds nothing beyond the schema. Baseline 3 applies when the schema already does the work.

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 equities market clock) and enumerates the returned fields (is_open, next_open/close) plus upcoming sessions, with the data provider (Alpaca) identified. It does not name or distinguish itself from any sibling tool, but no sibling in the list covers market session timing, so the purpose is unambiguous.

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 note that 'Crypto endpoints are 24/7 and unaffected' implicitly scopes usage to US equities sessions, which helps an agent decide when this tool applies. However, there is no explicit when-to-use/when-not-to-use guidance or alternative routing, and the sibling list contains no direct competitor to point at.

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