apisports_baseball_games

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

Annotations already mark this as read-only, idempotent, and open-world, but the description adds critical behavioral context: the return shape is from vendor docs and unverified, innings are keyed by number-as-string, and the tool requires an API key. These disclosures go well beyond what annotations provide.

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 moderately sized but every part earns its place: purpose, return shape, caveat about unverified shape, example, and auth requirement. The return shape is lengthy but justifiable given there is no output schema. Could be slightly tighter, but overall it is well-structured.

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?

The description covers purpose, filtering, return shape, authentication, and an example, which is quite complete for a read-only tool with no output schema. It also highlights a key caveat about data reliability and points to the deeper official MLB provider. It lacks details on error handling or rate limits, but these are not critical for a simple query 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?

Schema description coverage is 100%, so parameters are already documented. The description adds a concrete example ({"date": "2024-07-04"}) and reinforces that the tool filters by date or league, but it does not add new meaning to team, league, or season parameters beyond the schema 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 what the tool does: 'Baseball games (MLB, NPB, KBO and others) by date or league.' It names specific leagues and the filter dimensions. It also differentiates this tool from the official `mlb` provider, making it distinguishable from siblings.

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?

The description implies when to use this tool: for baseball games by date or league. It also provides an alternative recommendation by noting that the keyless official `mlb` provider offers deeper data for MLB. However, it does not explicitly enumerate exclusions or edge cases, which keeps it from a 5.

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