Get detailed information about a specific college baseball game including venue, weather, win predictions, play-by-play, and team stats. Use a match ID from the scoreboard.
| Name | Required | Description | Default |
|---|---|---|---|
| matchId | Yes | Highlightly match ID (from scoreboard results). e.g., "993144". |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnly, idempotent, and non-destructive behavior. The description adds value by disclosing the return categories (venue, weather, predictions, play-by-play, stats), giving the agent an expectation of the response shape without an output schema. No contradiction with 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?
Two concise sentences. The first sentence provides the purpose and scope, the second explains the required parameter source. No unnecessary words or repetition.
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?
Despite lacking an output schema, the description enumerates the major data types returned (venue, weather, win predictions, play-by-play, team stats), which sufficiently prepares an agent for typical use. Simple tool with one parameter, so this is adequately complete.
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 coverage is 100%: matchId is described as a 'Highlightly match ID (from scoreboard results)' with an example. The description repeats the scoreboard source but adds no new parameter semantics, so it meets the baseline without exceeding it.
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 function: 'Get detailed information about a specific college baseball game' and enumerates content areas (venue, weather, win predictions, play-by-play, team stats). This distinguishes it from sibling tools like bsi_get_scoreboard (list games) and bsi_get_player_stats (individual stats).
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 provides clear context by stating 'Use a match ID from the scoreboard', which implies a workflow: first consult the scoreboard, then this tool for details. It does not explicitly list when-not-to-use alternatives, but the prerequisite is helpful and distinguishes it from stat/ranking tools.
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.
