balldontlie_nba_games

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

Annotations already state readOnlyHint, openWorldHint, and idempotentHint. The description adds valuable context: the exact return shape, the pitfall that the away team is 'visitor_team' not 'away_team', a clear warning that the shape is unverified and should be inspected, and the need for an API key. This goes beyond the annotations and helps the agent avoid misinterpreting payloads.

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

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

The description is structured into distinct sections (what it does, return shape, caveats, example, auth). Each sentence serves a purpose, and the necessary vendor-doc warnings are included without being overly verbose. Slightly longer than ideal, but the content justifies the length.

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

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

Without an output schema, the description effectively provides the return shape and warns about its unverified nature. It also covers authentication and gives a usage example. However, it does not explain pagination behavior (e.g., how to use 'cursor' with 'meta.next_cursor') or whether filters can be combined, leaving some gaps for a complex data-retrieval tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema covers 100% of parameters with descriptions, so the baseline is 3. The description adds a concrete example for the 'dates' parameter and clarifies the intended usage of 'season' and 'team' conceptually, enhancing the schema's factual descriptions.

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

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

The description clearly states 'NBA games by date, season or team', identifying the resource (NBA games) and the main filter dimensions. It does not explicitly differentiate from sibling tools like apisports_basketball_games or sportsdataio_nba_games_by_date, but the provider-specific name and scope make it unambiguous enough.

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

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

There is no explicit guidance on when to use this tool versus alternatives, nor any mention of when not to use it. The example shows a simple date query, which implies usage, but the description lacks any comparative direction among the many NBA games tools in the sibling list.

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