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get_team_stats

Read-only

Use for one team's season: totals (passing, rushing, receiving, defense, kicking, penalties), EPA per play, yards per attempt/carry, the standings row, and every weekly stat line. Costs 5 credits.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
teamYesTeam code (e.g. KC, BUF, PHI)
seasonNoSeason year (e.g. 2025). Defaults to current.
season_typeNoRegular season (default) or postseason

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
teamYes
countYes
weeksYes
recordYes
seasonYes
totalsYes
season_typeYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, so safety is covered. The description adds concrete behavioral context: a credit cost ('Costs 5 credits') and the precise data scope (categories like passing, rushing, defense, EPA, standings row, weekly lines), which goes beyond what annotations provide.

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?

The description is front-loaded with the core purpose and packs substantial useful detail into two sentences. The enumeration of stat categories is long but earns its place by clarifying exact output scope; the cost line is appended at the end, which is acceptable though not perfectly structured.

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 present and read-only annotations, the description covers selection-relevant facts: scope, content, and cost. It does not need to describe return shape or safety because those are handled by schema and annotations. It is sufficiently complete for an agent to decide when to call it.

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 parameters are fully documented. The description adds no parameter-level meaning beyond reiterating that it is for one team's season; it does not explain team codes, season formatting, or season_type semantics beyond what the schema already states. Baseline 3 is appropriate.

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 tool returns a specific bundle of team-season statistics (totals for passing/rushing/etc., EPA, standings row, weekly lines) scoped to a single team. It does not explicitly distinguish from sibling tools like get_advanced_stats or get_standings, but the content list is specific enough to identify its role.

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 opening 'Use for one team's season' gives an explicit use case, but there are no exclusions or pointers to alternatives. The agent must infer that other tools like get_games or get_player_stats are for different resources; no when-not guidance is 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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