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smw355

NFL Data MCP Server

by smw355

get_player_stats

Retrieve season statistics for any NFL player by entering their name and position, covering seasons from 2015 to 2024.

Instructions

Get season statistics for a specific player by name and position

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearNoSeason year (2015-2024)
positionYesPlayer position (QB, RB, WR, TE, DB, LB, DL, K)
player_nameYesPlayer name to search for
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It does not state whether this is a read-only operation, what data is returned (which stat categories), whether year is optional and defaults to the latest season, or how name matching works (exact vs fuzzy). For a data-fetch tool with zero annotation coverage, this is a meaningful gap.

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

Conciseness3/5

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

The description is a single concise sentence with zero waste. However, it compresses 'by name and position' which duplicates what the schema already declares in the required parameters. It's efficient but under-specified relative to its brevity - it doesn't use the space to add behavioral value beyond the schema.

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

Completeness2/5

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

This is a data retrieval tool with no annotations and no output schema, so the description must carry substantial explanatory weight. It is incomplete: it doesn't specify what statistics are returned, whether year is optional, how name/position matching works, or how this differs from the sibling tools (search_players, compare_players). For a 3-parameter tool with sibling overlap, this level of detail is insufficient.

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

Parameters2/5

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

Schema description coverage is 100%, so the baseline is 3. However, the description adds minimal value beyond the schema: it bundles player_name and position together but doesn't clarify behavioral semantics like whether position filters the search or is required for disambiguation, whether year defaults to the most recent season when omitted, or how name matching behaves (exact match, case sensitivity). The description doesn't compensate for these ambiguities.

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 clear verb+resource+scope ('Get season statistics for a specific player by name and position'). It identifies the tool's purpose well, though it doesn't explicitly distinguish the single-player lookup nature from sibling tools like compare_players or search_players. The purpose is clear but lacks explicit sibling differentiation.

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

Usage Guidelines2/5

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

No guidance is given on when to use this tool versus alternatives. Siblings like search_players (for finding players) and compare_players (for comparing) have overlapping domains, and the description doesn't clarify that this tool fetches full season stats for exactly one known player. No exclusions or alternative tool references are provided.

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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