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Crawlora MCP

mlb_statcast_active_spin

Read-only

Fetch Baseball Savant Active Spin pitcher rows by season/calculation method, minimum pitches, and throwing hand, with local sorting and pagination. Use mlb_discovery for the exact season and filter sets; the SVG chart and CSV output are separate.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
minNoOptional minimum pitch count: 50, 100, 250, 500, 750, 1000, 1500, 2000, 2500, or 3000. Defaults to 50.
handNoOptional pitcher throwing hand: R or L; blank includes both.
sortNoOptional local table sort field from mlb_discovery.
yearNoOptional season and calculation method from mlb_discovery; defaults to the current spin-based season.
limitNoOptional number of rows, 1-500; defaults to 100.
offsetNoOptional zero-based row offset, 0-5000.
sort_dirNoOptional sort direction: asc or desc.

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

A3.8/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so safety is covered. The description adds useful behavior: results are sorted and paginated locally, and the SVG chart/CSV output are separate artifacts. It does not describe pagination limits, defaults, or upstream auth/rate behavior, so 3 is appropriate.

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

Conciseness5/5

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

Two sentences, zero filler. The primary fetch scope is front-loaded, followed immediately by the dependency (mlb_discovery) and the exclusion (chart/CSV are separate).

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?

With an output schema present, return values need not be explained, and the description correctly focuses on input sourcing and local pagination. It omits how pagination interacts with the local sorting/offset range, a minor gap but not one that blocks correct invocation.

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 coverage is 100%, so the schema already documents all seven parameters including valid min values, hand, sort, limit, and offset ranges. The description only restates the categories (season, min pitches, hand) without adding syntax or constraints, which is the baseline 3 when the schema does the heavy lifting.

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?

The description names a specific verb and resource ('Fetch Baseball Savant Active Spin pitcher rows') and scopes the inputs (season/calculation method, minimum pitches, throwing hand). It does not name a direct sibling of the same shape, but it does route to mlb_discovery and clarifies that the chart/CSV tools are separate, so an agent can distinguish it from adjacent statcast tools.

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

Usage Guidelines4/5

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

It explicitly says to use mlb_discovery for the exact season and filter sets, giving clear context for how to obtain valid values for year and sort. There is no explicit 'do not use for X' exclusion beyond the chart/CSV note, which keeps it just short of 5.

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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