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Crawlora MCP

mlb_statcast_arm_strength

Read-only

Fetch Baseball Savant Arm Strength player or team leaderboard rows. Filter by verified year, MLB team id, throwing position, minimum throws, local sort, and pagination; use mlb_discovery for exact value sets.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sortNoOptional locally sorted leaderboard field; use mlb_discovery for all supported values.
typeNoOptional row type: player or team. Defaults to player.
yearNoOptional season: 2020, 2021, 2022, 2023, 2024, 2025, 2026, or 9999 for all years. Defaults to the current season.
limitNoOptional number of rows to return, 1-500; defaults to 100.
offsetNoOptional zero-based result offset.
team_idNoOptional Baseball Savant team id; valid values are 108, 117, 133, 141, 144, 158, 138, 112, 109, 119, 137, 114, 136, 146, 121, 120, 110, 135, 143, 134, 140, 139, 113, 111, 115, 118, 116, 142, 145, 147.
positionNoOptional position metric: arm_inf, arm_of, arm_1b, arm_2b, arm_3b, arm_ss, arm_lf, arm_cf, or arm_rf.
sort_dirNoOptional sort direction: asc or desc.
min_throwsNoOptional minimum throws: 50, 100, 300, 500, or 1000. Defaults to 50.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYesThe tool result payload (shape varies per tool; see each tool's docs resource).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the read-only, external-data nature is covered. The description adds little beyond that: it does not disclose rate limits, auth needs, pagination behavior, or result ordering semantics (despite an output schema existing). The word "verified year" hints at value validation, which is marginally informative.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with the action and resource, then the filter list and the mlb_discovery pointer. No filler. Slightly dense but every clause is relevant.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a leaderboard-fetch tool with a full input schema (100% coverage) and an output schema, the key remaining question is sibling selection. The description covers the filters and the enum-discovery route, but omitting explicit routing against mlb_statcast_arm_strength_player leaves a small gap.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all nine parameters with allowed values. The description names the filterable dimensions but adds no syntax, format, or default detail beyond what the schema provides, making the baseline of 3 appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

"Fetch Baseball Savant Arm Strength player or team leaderboard rows" gives a concrete verb (fetch) and resource (Arm Strength leaderboard), and the "player or team" scope implicitly distinguishes it from the player-only sibling mlb_statcast_arm_strength_player. The sibling is not named explicitly, so the differentiation is inferred rather than stated.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It advises using mlb_discovery for exact value sets, which is useful routing for discovering valid parameters. However it gives no explicit when-to-use guidance versus alternatives such as mlb_statcast_arm_strength_player or mlb_statcast_arm_value, and no exclusions or prerequisites.

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

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