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

Annotations declare readOnlyHint, openWorldHint, and idempotentHint, but the description adds behavioral details: it returns null for non-resolving slugs, indicating error handling, and clarifies the data source and scope (public detail). This goes beyond the annotations by describing the return value in edge cases and the nature of the data (revenue signals, for-sale status).

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 two sentences, front-loaded with the main purpose, and includes a concrete example. Every phrase adds value: the behavior on invalid slugs, the source of the slug, and what the returned details include. No fluff or redundancy.

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?

The description is complete for a tool with a single parameter, high schema coverage, and an output schema present. It covers input derivation, usage context, return value, and edge-case behavior. The output schema likely documents return structure, so not describing it is acceptable. Complexity is low, and no additional guidance seems necessary.

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 parameter is fully documented. The description adds important semantic context by explaining how to derive the slug from toolUrl (e.g., '/tools/acme-writer' -> 'acme-writer'), which is not in the schema. This elevates the score above baseline, though the schema already covers the parameter.

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 fetches full public details for one AI tool by slug, specifying the source (listing slug from search_tools) and what is returned (description, launch date, revenue signals, for-sale status). It also mentions returning null for invalid slugs, which distinguishes it from sibling tools like search_tools.

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 explicitly instructs to call this after search_tools, providing clear sequential usage. It also differentiates from search_tools by explaining that this retrieves full details for a single tool, while implying search_tools is for listing. No alternative tools are mentioned, but the context of sibling tools (list_alternatives, list_offers) suggests this is for basic tool detail retrieval.

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