find_alternatives

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

No annotations are provided, so the description carries the full disclosure burden. It discloses the core behavior: sharing at least one active ingredient, in-stock filtering, and returning 'other' products. However, it does not explicitly state whether the operation is read-only, how results are ordered or paginated, or whether the given product is excluded beyond the word 'other.'

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 entire description is one efficient sentence that front-loads the operation and matching rule, then adds a relevant use case. There is no filler or repetition of the schema.

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 2-parameter tool with no annotations and minimal schema, the description covers the main purpose and use case but omits the in_stock_only parameter behavior. It also does not explicitly distinguish itself from recommend_products, leaving some ambiguity in edge cases. An output schema exists, but the description still needs to explain how to control the stock filter.

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 0%, so the description must compensate. It clarifies product_id via 'the given product,' but it never mentions the in_stock_only parameter, its default value, or how setting it to false changes the result. This is a significant gap because that parameter controls the core stock filter.

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 states a specific verb and resource: 'Find other in-stock products sharing at least one active ingredient with the given product.' It clearly differentiates this from generic search_products and recommend_products by naming the exact matching rule and the out-of-stock/different-brand use case.

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 a concrete when-to-use signal: 'useful when it's out of stock or the client wants a different brand with the same effect.' It does not explicitly name alternatives or exclusions, but the use case is clear enough to guide tool selection among the siblings.

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