Get schedule records returned for a college baseball team, including past results and upcoming games when the source provides them.
| Name | Required | Description | Default |
|---|---|---|---|
| team | Yes | Team name or slug (e.g., "texas", "lsu", "florida-state"). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare the operation as read-only, idempotent, and non-destructive, so the description adds value by noting the caveat 'when the source provides them,' indicating that schedule data completeness may vary. This is useful behavioral context beyond the structured annotations.
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 a single sentence that front-loads the main action and includes only necessary information. Every word contributes to understanding the tool's purpose and limitations, with no redundancy or filler.
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?
With one simple parameter fully described in the schema and annotations covering safety, the description is sufficiently complete for selection and invocation. The only minor gap is the lack of detail about the exact structure of 'schedule records,' but this is not critical for using the tool correctly.
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 input schema provides a comprehensive description for the 'team' parameter with examples, so the description does not add additional parameter semantics. Baseline 3 applies because schema coverage is 100% and the description does not need to compensate.
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 retrieves schedule records for a college baseball team, with a specific verb ('Get') and resource ('schedule records'). It also clarifies scope ('past results and upcoming games') and distinguishes from sibling tools like scoreboard or standings by focusing on the team's schedule.
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 when a team's schedule is needed, but it does not explicitly compare with sibling tools or state when not to use this tool. No alternatives or exclusions are mentioned, so it relies on contextual inference rather than explicit guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct resource: game details, player stats, rankings, scoreboard, standings, team schedules, and web search. There is no overlap between these purposes, and the descriptions make the boundaries clear.
Six tools follow a consistent 'bsi_get_<resource>' pattern, while 'bsi_search_intel' deviates by using 'search' instead of 'get'. This is a minor inconsistency but still readable and predictable overall.
With 7 tools, the set is well-scoped and each tool serves a distinct function. The count is appropriate for a sports information server, not too thin or overbearing.
The tool set covers major aspects of college baseball: games, players, rankings, live scores, standings, schedules, and narrative context via web search. No significant gaps are apparent, and the search tool provides a fallback for any uncovered queries.
