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

Annotations already declare the operation read-only and idempotent, and the description adds valuable behavioral details: it returns null if the slug doesn't resolve, and it references how the slug is obtained (from search_tools' toolUrl). This clarifies expected outcomes without repeating annotation data, and there is no contradiction.

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?

Three sentences, front-loaded with the main action, each sentence serving a purpose: what it does, when to use it, and edge-case behavior. 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?

Given a single parameter and an output schema (not shown but present), the description covers the tool's purpose, usage context, return contents, and null case. It is fully self-contained for an agent to invoke correctly within the sibling tool set.

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 input schema only lists 'slug' with a minimal description. The description enriches this by explaining the exact format ('/tools/acme-writer' -> 'acme-writer') and source of the slug (from search_tools' toolUrl), adding semantic meaning beyond the schema's basic type enforcement.

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[es] the full public detail for one AI tool' by slug, with a concrete example ('/tools/acme-writer' -> 'acme-writer'). It distinguishes itself from sibling search_tools by mentioning the workflow 'Call this after search_tools', making the purpose specific and 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 explicitly instructs when to use this tool ('Call this after search_tools') and lists the type of information returned (full description, launch date, etc.). However, it does not explicitly mention when not to use it or compare with alternatives like list_alternatives or list_offers, so it misses the full 'when-not/alternatives' spectrum.

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