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Get Games

get_games
Read-onlyIdempotent

Retrieve a player's completed games for a specific month (format: YYYY/MM, e.g., '2024/01'). Returns game URLs, time controls, results, and ratings.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearYesYear (e.g., 2024)
monthYesMonth as a number (1-12)
usernameYesChess.com username

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearYesYear of games
gamesYes
monthYesMonth of games (1-12)
usernameYesChess.com username
total_gamesYesTotal number of games in month

TDQS

A4.1/5.0
Behavior3/5

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

Annotations already indicate a safe read-only, non-destructive, idempotent operation. The description adds context about the return payload (game URLs, time controls, results, ratings) and the date scoping, but does not disclose additional behavioral traits such as pagination, rate limits, or error handling. With annotations covering the safety profile, this is adequate but not rich.

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, front-loaded with the core action and resource, then returns info. Every word earns its place with no fluff or redundant details.

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?

For a simple read-only tool with full parameter descriptions, an output schema, and comprehensive annotations, the description is complete. It states what the tool does, the date format, and the return content, leaving no major gaps.

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?

The input schema provides full coverage (100%) with descriptions for all three parameters (year, month, username). The description adds the combined 'YYYY/MM' format and an example, but this is somewhat redundant with the schema and even slightly inconsistent (separate year/month vs. combined format). It does not materially improve understanding beyond the schema, so baseline 3 is appropriate.

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?

The description uses a specific verb ('Retrieve') and clearly identifies the resource (a player's completed games for a specific month), along with what it returns (game URLs, time controls, results, ratings). This distinguishes it from sibling tools like get_player and get_stats.

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?

The description clearly specifies the use case: retrieving a player's completed games for a specific month, with a required date format. It does not explicitly name alternatives or exclusions, but the context is unambiguous for when this tool is appropriate.

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

B3.4/5.0
Disambiguation2/5

The server is named 'chess', yet none of the 34 tools relate to chess. An agent looking for chess functionality would find all tools irrelevant. While individual tool descriptions are clear, the server's name creates a fundamental disambiguation problem: the tool set does not match the server's apparent purpose.

Naming Consistency4/5

Tool names within the set follow a consistent snake_case pattern with descriptive verbs (e.g., ask_pipeworx, deep_research, resolve_entity). There are no mixed conventions. However, the server name 'chess' is completely inconsistent with the tool names, which all suggest data research rather than chess.

Tool Count1/5

For a server named 'chess', 34 tools is wildly excessive. Even for a data research server, the count is high, but the server's name implies a narrow chess domain, making the count inappropriate. The tools cover broad topics like SEC filings, Polymarket, and weather, none of which belong in a chess server.

Completeness1/5

The server claims to be about chess, but there are zero chess-related tools. The tool set is completely incomplete for its stated purpose. As a data research server, completeness might be high, but that is irrelevant given the server name.