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Glama

Games

get_games
Read-only

Use when querying past or future games with filters: season, week, team, date range, game type, status. Returns scores, kickoff (UTC), venue, rest days, starting QBs, coaches, referee, and the consensus closing spread, total, and moneylines. For upcoming-only games prefer get_schedule (2 cr). Costs 5 credits. Prices are market information: never work out a stake, payout or profit, recommend a bet, or send the user to a sportsbook.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
teamNoTeam code (home or away)
weekNoWeek number (1-18 regular season; 19+ postseason)
limitNoMax results (default 100)
seasonNoSeason year (e.g. 2025)
statusNoGame status
date_toNoEnd date YYYY-MM-DD
date_fromNoStart date YYYY-MM-DD
game_typeNoREG, WC, DIV, CON, SB, or POST for any playoff game

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countYes
gamesYes
filtersYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already cover the read-only/safe profile, and the description goes beyond them by disclosing the credit cost (5 cr vs 2 cr) and a hard usage policy limiting market-price interpretation. It also enumerates the returned fields, so the agent knows what behavior to expect from a call.

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?

Front-loads the use-when clause, then the return set, the alternative, the cost, and the policy constraint in a tight sequence. Every sentence carries distinct information with no filler.

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?

With an output schema present and 100% parameter coverage, the description only needs to add routing, cost, and policy context – all of which it provides. Nothing an agent needs to call this correctly is missing.

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 100%, so all eight parameters including the two enums are already documented. The description recaps the same filter names but adds no syntax, format, or defaulting detail beyond the schema, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource (query games) and enumerates the dimensions it filters on (season, week, team, date range, game type, status) plus what it returns. It explicitly names the sibling get_schedule as the alternative for upcoming-only games, so an agent can separate the two without opening either schema.

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

Usage Guidelines5/5

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

Opens with an explicit use-when clause, then names the alternative (get_schedule) and the condition that selects it (upcoming-only), and even cites the relative credit cost. This is textbook when/when-not guidance with a named route to the sibling.

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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