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JavaScript
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mlb_league_leaders

Retrieve ranked MLB league leaders by category, season, group, league, and game type. Use mlb-discovery to find valid category names before submitting requests.

Instructions

Get MLB league leaders. Returns ranked MLB leader entries for one or more validated categories. Use mlb-discovery for all accepted categories, groups, and game type codes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
groupNoStat group
limitNoLeaders per category (1-100)
seasonNoFour-digit season; defaults to current year
game_typeNoMLB game type
league_idNoMLB league id
categoriesYesComma-separated MLB leader category names; values are listed in mlb-discovery

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.17.7

TDQS

A3.5/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full behavioral burden. It does disclose that results are ranked entries and that categories are validated, but it is silent on pagination, how many defaults apply, ordering guarantees, or failure behavior for invalid categories.

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?

Three short sentences, front-loaded with the core action, then the return semantics, then the dependency pointer. Nothing is redundant and no sentence fails to earn its place.

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

Completeness3/5

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

With six parameters, no output schema, and no annotations, the description should compensate more than it does. It covers purpose and category validation but leaves return format, empty/invalid-category handling, and pagination unaddressed, which matters for a mutation-free but unannotated query tool.

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 all six parameters (group, limit, season, game_type, league_id, categories) are already documented in the schema, making 3 the baseline. The description adds only the pointer to mlb-discovery for category/group/game-type values, a marginal gain over structured fields.

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 states a specific verb and resource ('Get MLB league leaders') and clarifies the return shape ('ranked MLB leader entries for one or more validated categories'). It does not, however, distinguish itself from close siblings such as mlb_league_stats or mlb_team_stats, so an agent must still infer the boundary.

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 routes agents to mlb-discovery for accepted categories, groups, and game-type codes, which is genuinely useful for parameter discovery. But it gives no guidance on when to use this tool versus statistical siblings like mlb_league_stats, so usage context is only implied.

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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