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

Annotations already declare readOnly and idempotent, and the description adds useful behavioral details: it mentions the tool returns null for unresolvable slugs and lists the types of information (full description, launch date, revenue signals, for-sale status). This goes beyond the annotations without contradicting them.

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 core purpose, then the usage context and an edge case. 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?

With an output schema present, the description need not detail return structure. It covers purpose, usage guidance, parameter extraction, and error behavior (null return), making it fully self-sufficient for an agent to invoke correctly.

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% but the slug description is minimal. The description adds a precise example (e.g., '/tools/acme-writer' -> 'acme-writer'), clarifying exactly what format is expected, which is valuable beyond the schema's generic 'tool's listing slug'.

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 its slug, with a concrete example of slug extraction. It explicitly distinguishes from search_tools (which lists) and other siblings, making its purpose unambiguous.

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 instructs to call this after search_tools, establishing a clear workflow. It also notes the null return for invalid slugs, which helps the agent decide when to use it. However, it doesn't explicitly mention when not to use it or provide alternatives beyond the implied sequence.

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