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MLB pitcher splits

invoke_mlb_pitcher_splits
Read-onlyIdempotent

Pitcher performance against left handed and right handed hitters. window season is the full season (50+ batters faced), window l30 is the last 30 days (20+ batters faced). Returns ERA, FIP, xFIP, SIERA, strikeout and walk rates, swinging strike rate and ground ball rate.

Input Schema

NameRequiredDescriptionDefault
teamNoTeam abbreviation, for example NYY.
limitNoMaximum rows to return. The plan limit applies on top.
splitNoSplit filter: vs_LHH, vs_RHH, SP_overall, or RP_overall.
playerNoPlayer name, for example Aaron Judge.
windowNoTime window: season or l30.
sort_byNoSort field.
sort_dirNoSort direction: desc or asc.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive, so safety is covered. The description adds genuinely useful behavioral context beyond that: minimum sample thresholds (50+ batters faced for season, 20+ for l30), which tells the agent about data reliability and why rows may be missing for some pitchers.

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 tightly packed sentences with no filler: purpose first, then window semantics, then the return fields. Slightly list-like at the end, but every clause carries information an agent needs.

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 no output schema, the description takes on the burden of naming returned metrics (ERA, FIP, xFIP, SIERA, K/BB rates, SwStr, GB rate) and does so. All 7 parameters are documented in the schema, so the remaining gap is only defaults and how pitchers are identified, which is minor for a filterable list tool.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3. The description earns extra credit by explaining semantics the schema does not: the schema only says 'Time window: season or l30', while the description defines what each window actually means and its sample-size floor, and ties vs_LHH/vs_RHH to the LHH/RHH framing.

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?

Opening sentence states a specific resource and scope: pitcher performance split by handedness of opposing hitters. An agent can infer this differs from invoke_mlb_hitter_splits, but the description never explicitly names or contrasts with that sibling, leaving the differentiation implicit.

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?

Usage is implied through the split/window explanations rather than stated: the description never says when to pick this over invoke_mlb_matchup, invoke_mlb_starters, or invoke_mlb_team_splits. Context is present but the agent must infer the selection criteria.

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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