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evanatpizzarobot

DraftCall-MCP

Search NFL players

search_players

Find NFL players by partial name, team abbreviation, or position to resolve ambiguous queries before comparing stats.

Instructions

Find players by partial name, team abbreviation, or position. Use this when a name is ambiguous or only partly known before calling the other tools.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryYesPartial name, team abbreviation (e.g. "KC"), or position.
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It does not state what the tool returns (list of players? IDs? full details?), whether it's read-only, any limitations on result counts (other than the limit param), or pagination. The description is too sparse to fully inform an agent about execution behavior.

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?

A single, efficient sentence that front-loads the main action and includes a usage condition. No filler or redundant information. The structure is ideal for quick scanning.

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?

The tool has no output schema and only a single description sentence. It fails to explain what the search results contain or how they should be used (e.g., to feed into get_player). Given the sibling tools, an agent needs to know if search_players returns enough data to proceed directly or if it should be followed by another call.

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 50%, and the description does not compensate for the undocumented 'limit' parameter. It repeats the query semantics from the schema without adding new meaning (e.g., case sensitivity, format of team abbreviations). The 50% coverage means the description needs to explain the missing parameter but does not.

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 'finds players' with specific search criteria (partial name, team abbreviation, position). This is a specific verb + resource combination that distinguishes it from a retrieval tool like get_player. However, it does not explicitly name a sibling or contrast itself beyond implying it's a preliminary step.

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

Usage Guidelines4/5

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

Explicitly says 'Use this when a name is ambiguous or only partly known before calling the other tools.' This gives clear guidance on when to use it and positions it as a pre-step. It lacks explicit exclusions (e.g., when you have a player ID), but the context is clear enough for an agent.

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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