sephora_product

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

With no annotations provided, the description carries the transparency burden and handles it well. It reveals that the data comes from Sephora's credential-free public JSON-LD, that only the full page slug resolves (not an arbitrary or partial slug), and that the product detail includes only a sample of recent reviews. These are behaviors beyond what the schema alone can convey.

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 has no wasted words. The main resource/issue action is in the first sentence, followed by a compact list of what the full detail includes, then a practical example that disambiguates the parameter. All this in four sentences, and each sentence carries unique, necessary information.

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?

For a tool with a single parameter and no output schema, the description is nearly complete. A full list of distinct output fields (variants, price, availability, rating, review count, sample reviews) and the slug-resolution warning tell the agent enough to invoke it successfully. A clear error-handling note for invalid slugs would be the last minor missing piece.

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 description of the product_id parameter ('Full Sephora product-page slug') is high-confidence, but the tool description adds substantial value with a concrete example, a copy-it-from-the-URL instruction segment, and a caveat about partial slugs. That transforms a generic parameter name into an unambiguous, operational instruction.

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 explicitly states a specific verb—'Returns'—and a specific resource: one Sephora product's full detail. It enumerates the exact content fields (every color/shade variant with price, availability, rating, review count, and a sample of recent reviews), making it unmistakably distinct from search, reviews, and other Sephora siblings.

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 gives clear context on when to invoke the tool: whenever an agent needs a single product's complete detail by its full product-page slug. It also explains which identifier format works and warns against partial slugs. It does not explicitly list alternative tools or exclusions, but the scope is precise enough for an agent to choose it correctly.

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