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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the description doesn't need to restate safety. Instead, it adds behavioral context: returns null if slug doesn't resolve, indicates data fields returned (full description, launch date, revenue signals, for-sale status). Slightly unclear whether 'verified or self-reported' means revenue can be of different types, which could confuse but doesn't harm. Minor deduction for not saying anything about auth or rate limits, but those are likely covered by sibling docs.

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?

Two sentences, front-loaded with the primary action, and includes a concrete example. No wasted words, every clause serves a purpose.

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 tool is simple (1 param), has a rich schema, and an output schema exists. The description covers the main return fields, null handling, and relationship to sibling tools. A more explicit note on response example could push it to 5, but it's already quite complete for its complexity.

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% ('The tool's listing slug.'), so the parameter semantics are fully documented in the schema. The description adds an example slug format and ties it to the search_tools toolUrl, which is extra context. Per rubric, baseline of 3 applies when coverage is high, and this matches.

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 'Fetch the full public detail for one AI tool by its listing slug' – a specific verb+resource combination. It distinguishes this tool from siblings by explicitly referencing search_tools' output and by naming the exact use-case for retrieval.

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?

It provides explicit usage guidance: 'Call this after search_tools' and describes what data to retrieve. It also clarifies the null return case for a non-existent slug, covering an edge case that enriches the usage context.

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