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grade_tcg_card

Analyze trading cards from Pokémon, Magic, and more for PSA or Beckett grading using local Vision AI. Provide card images to receive an estimated grade.

Instructions

Analyze a Trading Card (Pokémon, Magic, etc) for PSA/Beckett grading using a local Vision AI.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
card_image_pathsYesA JSON string array of absolute paths to the dropped card images (e.g. '["/path/1.png", "/path/2.png"]').
card_nameNoName of the card being graded (e.g. 'Base Set Charizard')Unknown Card

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, and the description only mentions using a local Vision AI. It fails to disclose behavioral traits such as error handling, image requirements, or whether the tool can grade all card types or has limitations.

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, front-loaded sentence that concisely states the tool's purpose without extraneous information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has an output schema and the description provides a high-level purpose, but it omits context like the grading criteria, supported card sets, or what happens with incomplete parameters. More detail would improve completeness.

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?

The input schema covers 100% of parameters with meaningful descriptions. The tool description does not add extra semantic value beyond specifying that it uses a local Vision AI, so it meets the baseline for parameter clarity.

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 tool analyzes trading cards for PSA/Beckett grading using a specific verb and resource. It distinguishes itself from all sibling tools which focus on unrelated tasks like creating banners, emotion detection, etc.

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?

The description provides no explicit guidance on when to use this tool versus alternatives. There are no sibling tools for card grading, but usage context (e.g., prerequisites, when not to use) is missing.

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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