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

Annotations already declare read-only, non-destructive, idempotent, and closed-world behavior. The description adds critical context beyond annotations: free tier returns counts/ranges/redacted samples while PRO returns full vendor, model, and exact prices; results are sorted cheapest first; and it explains unit semantics for token vs other modalities. It could mention rate limits or pagination behavior, but the tier distinction is a strong addition.

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 with the core purpose and uses clear examples. The first sentence is dense but informative, and the subsequent sentences about tiers and units earn their place. Overall efficient, though slightly long.

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?

With no output schema, the description carries the full burden of explaining return values. It does so by describing what free vs PRO tiers return and noting the sort order and units, which is sufficient for an agent to call the tool correctly. Pagination is covered by the input schema's limit/offset.

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 coverage is 100%, so the baseline is 3. The description significantly exceeds that by providing two concrete examples that map natural-language queries directly to parameter values (e.g., open_source="true", modality="Text", direction="Output", max_price=0.0005) and by clarifying that token prices are per 1,000 tokens while other modalities use their own units.

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 states a specific verb+resource: 'Search every priced SKU' and lists the filter dimensions. This distinguishes it from siblings like compare_prices or get_model_detail, which serve narrower purposes, even though no sibling is named explicitly.

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?

No explicit when-to-use guidance or alternatives are provided. The examples imply usage scenarios for translating natural-language queries into parameters, but they do not tell the agent when to select this tool over siblings such as compare_prices or get_price_history.

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