search_products

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

No annotations exist, so the description must carry the full burden. It states results are 'grouped by chain with normalised price, unit price, size, and promotion info', which is useful. However, it does not disclose pagination behavior, error handling, or consequences of missing data. The description adds value but is not exhaustive.

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 is two sentences plus a list of example uses, all front-loaded with essential information. Every sentence serves a purpose—scope, filters, returns, and examples—without unnecessary verbiage. It is concise and well-structured.

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 the complexity (6 parameters, nested objects, no output schema), the description covers the main aspects: chains, filters, returned fields, and example uses. It omits explicit pagination info but the schema has limit/offset. With no output schema, mentioning the returned structure ('grouped...normalised price...') is helpful. It is fairly complete.

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%, so the schema already documents all parameters. The description does not add new parameter-level details beyond giving example tags and chains. It reinforces the schema but does not enhance semantic understanding further, meeting the baseline of 3.

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 searches for products across specific Swiss grocery chains by keyword, with optional filters. It provides concrete example queries like 'find organic milk under 2 CHF', making the purpose unmistakable. The sibling tools (e.g., get_product, find_stock) have different scopes, so this tool is well-distinguished.

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 explicitly gives use cases such as 'compare pasta prices' or 'search for gluten-free bread', telling the agent when to use it. However, it does not provide explicit when-not-to-use guidance or compare with alternative tools (e.g., get_product for specific products), leaving room for ambiguity.

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