search_products

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

With no annotations, the description fully carries the behavioral burden. It discloses that results are grouped by chain, includes normalized price and promotion info, and reports data freshness via a sources map with timestamps. It does not explicitly state it is read-only, indicate rate limits, or mention authentication requirements, but the provided details are sufficient for safe usage.

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?

Four sentences efficiently cover purpose, filters, output format, and usage examples. No extraneous words, and key information is front-loaded. Ideal structure for an AI agent to quickly parse.

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 6 parameters (including nested objects) and no output schema, the description adequately explains the return structure, filter logic, and data freshness. It lacks error handling or edge-case guidance, but the usage examples and parameter details cover typical scenarios. Minor gap in describing limit/offset pagination behavior, but overall 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 coverage is 100%, so parameters are individually described. The description adds value by explaining how filters combine (e.g., 'All tags must match') and contextualizes the output. However, it does not provide deeper semantic nuance beyond what the schema already conveys. Score reflects the baseline for full schema coverage with modest additive value.

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?

Description specifies the core action 'Search for products' and the exact resource scope: 'across configured Swiss grocery chains (Migros, Coop, Aldi, Denner, Lidl)'. It provides concrete example queries like 'find organic milk under 2 CHF', which help distinguish this tool from siblings like get_product (single product lookup) and find_stock (inventory check).

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 lists explicit use cases ('Use for ...') and demonstrates how to combine filters. It implies the tool is for cross-chain price comparisons and attribute searches. However, it does not explicitly state when not to use it or differentiate from get_product (single item) and find_stock (availability). The guidance is clear but lacks exclusionary context.

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