Leaderboards for a league and optional season: most runs or most wickets, from ball-by-ball archives. Leagues include mlc, ipl, bbl, psl, cpl and international cricket.
| Name | Required | Description | Default |
|---|---|---|---|
| kind | No | 'batting' (default) or 'bowling' | |
| year | No | optional season year, e.g. '2026' | |
| limit | No | how many players to return (default 10) | |
| league | Yes | league code, e.g. 'mlc', 'ipl', 'bbl' |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, covering the safety profile. The description adds useful context by noting the data source is ball-by-ball archives and clarifies the available metrics. It does not describe result ordering, default kind/limit, or pagination, but those defaults are in the schema.
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 with no fluff. The purpose is front-loaded, and the supported leagues and data source are listed efficiently. Every word adds value.
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?
For a simple read-only leaderboard tool with fully documented params and a safety profile from annotations, the description is largely complete. It could optionally state what fields the leaderboard returns, but 'most runs or most wickets' already conveys the core output. The lack of an output schema is mitigated by the clarity of 'leaderboard.'
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 the baseline is 3. The description reinforces that 'kind' maps to runs vs wickets and that 'year' is optional, but it does not add meaning beyond the schema's own parameter 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 the tool provides leaderboards for a league and optional season, with most runs or most wickets as the key metrics. It names specific supported leagues, which adds concreteness. However, it lacks an explicit verb and does not distinguish itself from sibling cricket stats tools like phase_stats or team_form.
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 the tool: whenever you need league leaderboards for runs or wickets. It gives no explicit alternatives or when-not-to-use guidance, nor does it mention conditions that would favor a sibling tool. Usage context is present but left to inference.
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 distinguishable cricket data need: reference, match status, archives, player splits, team/venue stats, and probability. The only mild overlap is cricket_market_odds and cricket_win_probability, both returning probability-like output, but their descriptions make the market-vs-model distinction clear enough.
All tools share the cricket_ prefix and mostly use descriptive noun phrases such as cricket_player_career and cricket_venue_stats. cricket_explain_term breaks the pattern slightly as the only verb-led name, so the set is highly consistent but not perfectly uniform.
Eleven tools is well within the ideal range for a domain-specific cricket data server. Each tool covers a meaningful slice of the domain—explainer, live matches, archived scorecards, player/team/venue stats, leaderboards, and probabilities—without feeling bloated.
The surface covers most core cricket analytics workflows: lookup, live scores, career and phase stats, head-to-heads, team form, venue behavior, leaderboards, and win probability. Minor gaps exist such as detailed live ball-by-ball commentary or series-level schedules, but agents can generally accomplish common cricket questions without dead ends.