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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds value by detailing what the output contains (parameter ranges, side preference, counts, vendor questions, match queries) and notes the 'catalogue data only' constraint. It does not contradict annotations, and the added context is meaningful beyond the annotations.

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 front-loaded with the core purpose ('How to choose a product of one category') and then lists the specific output components. It is a single, somewhat long sentence but each clause delivers necessary information. It could be broken into bullets for readability, but it is not verbose or redundant. This earns a 4.

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 no output schema, the description thoroughly explains what the agent will receive: decisive parameters with ranges, which side is better, counts per parameter, vendor questions, and ready match queries. It also covers the special 'cubesat' case. Nothing essential for calling the tool is missing; the description is complete for its purpose.

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 covers the single parameter fully (100% coverage), so the baseline is 3. The description enriches the parameter semantics by providing a concrete example (category = 'cubesat' returns a list of subsystems) and explaining that category is a component class with examples. This goes beyond the schema's generic description, warranting a 4.

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's purpose: choosing a product of a category from catalogue data. It specifies the resource (catalogue) and the action (guide selection), and the content is distinct from sibling tools like match_components or find_suppliers, which focus on different operations. The mention of 'decisive parameters', 'which side is better', and 'ready match queries' gives a precise scope.

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 implies usage for product selection guidance but does not explicitly name alternatives or conditions when not to use it. It provides clear context (from catalogue data only) but lacks exclusionary guidance or references to sibling tools. This is a 'clear context, no exclusions' scenario, matching a score of 4.

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