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dburge86

kenpom-mcp

by dburge86

get_conference_defense

Get defensive stats for all teams in a conference: efficiency, eFG%, TO%, OR%, FTR, 2P%, 3P%, Blk%, Stl%. Provide conference code and optional season.

Instructions

Get conference defensive stats for all teams in a conference.

Returns defensive efficiency, eFG%, TO%, OR%, FTR, 2P%, 3P%, Blk%, and Stl%.

Args: conference: Conference code (required). Examples: 'B12', 'SEC', 'B10', 'ACC'. season: Optional season year (e.g., "2024"). Defaults to current season.

Returns: JSON array of conference defensive stats.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
seasonNo
conferenceYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses the exact statistics returned, the return format (JSON array), and the default season behavior. It implies a read-only operation via 'Get' and adds context beyond a simple call, though it does not explicitly state side effects or prerequisites.

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 well-structured with Args and Returns sections, front-loaded with the main purpose. The list of statistics is necessary and not wasteful. It is slightly longer than minimal but each sentence adds value.

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?

Given the simplicity of the tool (2 params, 1 required) and the descriptive output, the description covers purpose, parameters, return format, and the specific metrics. It lacks details about error conditions or data source caveats, but these are not critical for a straightforward read endpoint.

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

Parameters5/5

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

Schema description coverage is 0%, but the description fully compensates. It provides conference code examples ('B12', 'SEC'), marks conference as required, and explains that season defaults to the current season. This is far richer than the bare schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb (Get), resource (conference defensive stats), and scope (all teams in a conference). It naturally distinguishes itself from the sibling tool get_conference_offense by explicitly mentioning 'defensive' stats.

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 provides clear context for when to use the tool (for conference-level defensive stats), but it does not explicitly mention alternatives or exclusions. An agent could infer that offensive stats belong to get_conference_offense, but the description does not state this, leaving some ambiguity.

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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