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

Annotations already declare readOnly/idempotent/non-destructive, so the safety profile is covered. The description goes beyond that by disclosing the return payload: each robot's reference for other tools plus the count of specs held, which is genuinely useful for deciding whether to chain into get_robot.

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?

Two tightly packed sentences, front-loaded with what it does before what it returns. No filler, though the second sentence crams two return facts together.

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?

There is no output schema, and the description partly compensates by describing the return shape. However, for a search tool sharing a name-space with find_robots, the missing differentiation and undocumented limit parameter leave an agent under-informed despite the low overall complexity.

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 50%: query is documented with an example but limit is not. The description adds meaningful semantics for query (name, maker, or kind of robot) beyond the schema's example strings, but says nothing about the limit parameter. This sits at the baseline for partial coverage.

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?

States a specific verb (find) plus resource (robots) and enumerates the searchable facets: name, maker, kind. That is clear on its own, but the definition never distinguishes itself from the sibling find_robots, which appears to do the same thing, so it falls short of a 5.

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?

There is no guidance on when to use search_robots versus the near-identical find_robots, nor versus get_robot for direct lookup. The agent is left to guess between two similarly named siblings with no disambiguating condition.

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