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rjexile

Sports Trading Card Agent

by rjexile

nfl_stats_lookup

Retrieve NFL player statistics and card market insights for informed trading decisions. Enter a player name and season to access performance data and market analysis.

Instructions

Look up NFL player stats and get card market insights. Covers passing, rushing, receiving, and defensive stats.

Args: player_name: NFL player name, e.g. "Patrick Mahomes", "Josh Allen", "Justin Jefferson", "Micah Parsons". Partial names work. season: NFL season year (e.g. 2025). Default: 2025

Returns: Player bio, season stats (passing/rushing/receiving/defense), and card market insight based on performance.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
player_nameYes
seasonNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations provided, description carries full burden. It discloses important behavioral context that 'Partial names work' for fuzzy matching and lists covered stat categories (passing/rushing/etc.). However, lacks disclosure on error handling, rate limits, or authentication requirements.

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?

Well-structured with clear Args and Returns sections. Front-loaded purpose statement. Returns section is slightly redundant given output schema exists, but every sentence adds value. No excessive verbosity.

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?

For a 2-parameter lookup tool with output schema present, description adequately covers purpose, parameter semantics, and partial matching behavior. Missing error state documentation (e.g., ambiguous partial matches), but reasonable completeness given tool simplicity.

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 coverage is 0%, requiring description to fully compensate. Args section provides excellent semantics: player_name includes multiple examples and notes partial matching behavior; season includes example and default value note. Fully documents both parameters beyond what schema provides.

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?

States specific verb 'Look up' and resources 'NFL player stats' and 'card market insights'. Distinguishes from mlb_stats_lookup via 'NFL' specificity, but does not explicitly differentiate from generic player_stats_lookup sibling.

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 explicit guidance on when to use this tool versus alternatives like player_stats_lookup or card_market_analysis. While the NFL domain is clear, there is no 'when-not-to-use' or alternative recommendations.

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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