games_get_win_probabilitiesFetch win probability timeline samples for a sports event using sport, league, and event ID. Retrieve curve data across the entire game for analysis and visualization.
Fetch high-density win probability timeline curve samples across an entire game.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| sport | Yes | ||
| league | Yes | ||
| event_id | Yes | ||
| competition_id | No |
Changes observed during successful MCP inspections.
v1.2.9Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false and openWorldHint=true, so safety and idempotency are covered structurally. The description adds scope value ('high-density' sample volume, 'across an entire game'), but says nothing about pagination, the effect of the limit parameter, or data freshness. With annotations carrying the safety profile, this partial addition merits a 3.
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?
A single front-loaded sentence with no filler, leading with the verb and the resource. It is efficient, though the phrase 'high-density ... curve samples' is jargon-heavy without explaining what a sample contains.
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?
No output schema exists, so the description should describe the returned probability timeline structure and the five undocumented parameters. For a 5-parameter, 0%-coverage tool with no output schema, one sentence is materially incomplete.
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 0% for all five parameters, so the description must compensate and it does not. Required sport/league/event_id, the limit default of 50, and the nullable competition_id are never explained; 'across an entire game' only vaguely gestures at event scoping and conflicts with a limit-based sample count.
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 states a concrete verb ('Fetch') and resource ('win probability timeline curve samples') and scopes it to 'an entire game', so an agent knows what data comes back. It does not name or contrast any sibling (e.g. games_get_game_predictor, games_get_play_by_play), so the boundary with related prediction/play tools is left to inference.
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?
There is no when-to-use or when-not-to-use guidance and no alternative tool is named, despite several siblings (games_get_game_predictor, games_get_play_by_play, games_get_game_situation) that plausibly overlap. Usage is only implied by the resource name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.