get_mlb_schedule

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

No annotations are provided, so the description carries the full burden. It describes the tool as a retrieval operation, which implies read-only behavior, and specifies the return format. However, it lacks details on error handling, rate limits, or authentication needs, leaving behavioral gaps for a tool with no annotation coverage.

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 well-structured and front-loaded with the core purpose, followed by clear sections for arguments and returns. Each sentence adds value without redundancy, making it efficient and easy to parse for an AI agent.

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?

Given no annotations, 3 parameters with 0% schema coverage, and no output schema, the description is largely complete for a read-only tool. It covers purpose, parameters, and return format. However, it lacks some behavioral context like error cases or performance hints, which could enhance completeness.

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 description adds significant meaning beyond the input schema, which has 0% description coverage. It explains each parameter's purpose, optional nature, defaults, and formats (e.g., 'YYYY-MM-DD' for dates, team ID as integer), and clarifies that 'team_id' defaults to None for all teams, compensating fully for the schema's lack of documentation.

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 the tool's purpose with specific verbs ('retrieves') and resources ('MLB game schedule'), distinguishing it from sibling tools like 'get_daily_results' and 'mlb_team_result' which likely focus on results rather than schedules. It specifies the scope includes date ranges and optional team filtering.

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 usage by mentioning optional parameters for date ranges and team filtering, but does not explicitly state when to use this tool versus alternatives like the sibling tools. No exclusions or specific contexts are provided beyond the basic functionality.

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