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alexbrogan10

nfl-stats-mcp

by alexbrogan10

leaderboard

Read-only

Rank NFL players by any stat across one or more seasons, with filters for position, per-game averages, and season type.

Instructions

Rank players by a stat over one or more seasons (totals are summed across seasons).

Input Schema

NameRequiredDescriptionDefault
statYesA counting stat (e.g. 'passing_yards', 'receiving_tds') or rate stat (e.g. 'yards_per_carry'). See list_stats.
limitNo
seasonsNoSeasons to include, e.g. [2024, 2025]. 1999 or later. Defaults to the current season.
per_gameNoDivide counting stats by games played.
positionNoFilter by position or group, e.g. QB, RB, WR, TE, K.
ascendingNoTrue to list the lowest values first.
min_gamesNo
min_volumeNoOverride the qualifier for rate stats (e.g. minimum attempts). Defaults to the NFL's per-team-game minimums.
season_typeNoREG = regular season, POST = playoffs, ALL = both.REG

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds useful behavioral context by saying totals are summed across seasons, but it omits other relevant behavior such as qualifier handling for rate stats and per-game interactions.

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?

The description is a single well-formed sentence with no filler. The core action and aggregation rule are front-loaded.

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 and 78% schema description coverage, the definition does not need to explain return values or most parameters. The description supplies the key aggregation rule, though it leaves the sibling-routing context to other tools or schema hints.

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 high at 78%, so parameter semantics are mostly handled by the schema. The description only adds meaning around multi-season aggregation, without explaining other parameters such as limit, ascending, or min_volume beyond what the schema already says.

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 and resource: ranking players by a stat across seasons. It does not name or distinguish itself from sibling tools such as player_stats or situational_stats, so sibling differentiation is missing.

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 implies the tool is for leaderboard rankings, but gives no explicit when-to-use or when-not-to-use guidance versus alternatives. The schema mentions list_stats for stat names, but the description itself does not route the agent among siblings.

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