get_pricing

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

With no annotations provided, the description carries the full burden. It discloses key behavioral traits: it returns cost data in USD per unit (image/video/second), which is valuable context. However, it doesn't mention rate limits, authentication requirements, or error conditions, leaving gaps for a tool that likely queries external pricing data.

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 description is front-loaded and efficient: two sentences with zero waste. The first sentence states the purpose and return format, and the second provides usage guidance, making it easy to parse quickly.

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's moderate complexity (external pricing query), no annotations, and no output schema, the description is adequate but incomplete. It explains the return value (cost per unit in USD) but lacks details on response structure, error handling, or data freshness, which could hinder agent usage.

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?

Schema description coverage is 100%, so the schema already fully documents the 'models' parameter. The description adds no additional parameter semantics beyond what the schema provides, such as examples of valid model IDs or pricing granularity. Baseline 3 is appropriate when the schema does the heavy lifting.

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 clearly states the tool's purpose: 'Get pricing information for Fal.ai models' with specific resources (models) and verb (get). It distinguishes from siblings like 'get_usage' (usage statistics) and 'list_models' (model listing) by focusing on cost data.

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 clear context: 'Use this to check costs before generating content,' which implicitly suggests using it for cost estimation prior to using generation tools. However, it doesn't explicitly state when not to use it or name specific alternatives among siblings.

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