Skip to main content
Glama
Crawlora-org

Crawlora MCP

Official
by Crawlora-org
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Remote

mlb_statcast_park_factors

Get Baseball Savant Statcast Park Factors rows filtered by season, venue, condition, and batter side to analyze how parks affect wOBA, HR, and hit stats.

Instructions

Get Baseball Savant Statcast Park Factors rows. Returns season, venue, distance, distance-all, raw, or dimensions rows from Baseball Savant. Query filters are conditional on type and are live-echo validated; local sorting and pagination are applied to returned rows. The fence-stat and allDiffs controls only change display columns and do not change row data; CSV and linked venue detail pages are separate surfaces.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sortNoLocal row field present in the selected mode's data
statNoVenue mode metric
typeNoPark Factors table mode
yearNoMode-specific season; see endpoint markdown and mlb_discovery for exact values
limitNoRows per page (1-500)
parksNoPark population selector
offsetNoZero-based row offset
rollingNoRolling year count for year and venue modes
bat_sideNoOptional batter side for year, venue, or raw mode
sort_dirNoLocal sort direction
conditionNoPark condition for year and venue modes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.17.9

TDQS

A3.7/5.0
Behavior4/5

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

No annotations are provided, and the description carries useful behavioral load: it discloses local sorting/pagination on returned rows, that filters are live-echo validated, and that fence-stat/allDiffs only affect display columns, not row data. It also distinguishes CSV and linked venue detail pages as separate surfaces. It omits return format and pagination limits, but the mode-display caveat is genuinely non-obvious and valuable.

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?

Three sentences, front-loaded with purpose, each conveying a distinct fact (supported modes, validation/sorting behavior, display vs. data caveat). No filler, though the middle clause about CSV/linked pages is slightly tangential.

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 an 11-param, no-required, no-annotation, no-output-schema tool, the description does well to flag mode-conditional filters, local sorting/pagination, and display-vs-data distinctions. It lacks specifics on what returned rows contain and how modes map to filters, leaving modest gaps.

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 11 parameters and their enums. The description adds the conditional-on-type relationship between filters (and the display-only nature of some controls), but does not clarify the semantics of individual params like stat, rolling, or parks beyond the schema. Baseline 3 applies.

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 clearly states the verb and resource: retrieving Baseball Savant Statcast Park Factors rows, and enumerates the row kinds (season, venue, distance, distance-all, raw, dimensions). It concentrates on output shape rather than naming the sibling alternatives, so it is clear but not maximally differentiated from the large family of mlb_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 Guidelines3/5

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

The description notes that 'Query filters are conditional on type', which implies mode-dependent usage, and references 'endpoint markdown and mlb_discovery' for exact values. But it never states when to use this tool versus siblings like mlb_statcast or mlb_statcast_rolling, nor does it give explicit when-not guidance.

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

Deploy Server

Other Tools