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

The annotations already declare readOnlyHint=true and idempotentHint=true, indicating a safe read operation. The description adds useful behavioral context beyond annotations: it discloses that the tool returns null for invalid slugs, indicating no error throw, and specifies the type of data returned (description, launch date, revenue signals, for-sale status). This is more than the annotations alone provide, hence a 4.

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, tightly written, and front-loaded with the core action and input. Every phrase adds value: the slug format example, the recommended call sequence, and the null return behavior. There is no verbose or redundant text.

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 single parameter, high schema coverage, the presence of an output schema (automatically defining return structure), and read-only annotations, the description covers all necessary context: what to call, when to call, what to expect in return, and the null edge case. There is no gap that would hinder correct invocation.

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?

The schema has 100% coverage of the parameter 'slug' with its description 'The tool's listing slug.' The description reinforces this by explaining how the slug is derived (from search_tools' toolUrl) and gives an example. This matches the baseline of 3 for high schema coverage, and the added example provides slight extra value without overstepping.

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 detail for one AI tool by slug, distinguishing it from siblings. It specifies the verb ('fetch'), the resource ('one AI tool'), and the precise input (slug from search_tools' toolUrl). It also provides an example of slug format, eliminating ambiguity.

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 says to call this after search_tools to obtain full description, launch date, revenue signals, and for-sale status. It clarifies that the slug comes from search_tools' toolUrl, and notes that it returns null for unresolvable slugs, which guides the agent on when and how to use it.

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