Sports Trading Card Agent

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively explains the return structure (average, median, low, high, individual listings) and clarifies the semantic difference between sold and active listings. However, it omits operational details like rate limits, data freshness, or error behavior when cards are not found.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The Args/Returns docstring structure is appropriate for the complexity. The query examples are necessary domain guidance (trading card searches require specific formats) and the listing_type explanation prevents ambiguity. No sentences are gratuitous, though the Returns section slightly overlaps with the existing output schema.

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

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

Given the tool has 3 simple parameters and an output schema (per context signals), the description is adequately complete. It documents all parameters and summarizes return values without needing to replicate the full output schema. No critical gaps exist for a lookup operation of this scope.

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

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

With 0% schema description coverage (only titles provided), the description provides essential compensation by detailing query syntax with concrete examples, explaining the enum-like behavior of listing_type, and documenting the limit range (1-50). This rich semantic context prevents parameter misuse despite the bare schema.

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

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

The description 'Look up current market prices for a sports trading card' provides a specific verb and resource. While it doesn't explicitly namedrop siblings, the functional focus on price retrieval clearly distinguishes it from siblings like card_investment_advisor (advice/recommendations) and card_market_analysis (analytical insights) by focusing on raw data lookup.

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

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

The description provides excellent implicit usage guidance through the listing_type parameter explanation ('sold' for true market value vs 'active' for asking prices), helping users select the right price dataset. However, it lacks explicit guidance on when to use this tool versus alternatives like card_market_analysis or card_investment_advisor.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.