Semantic API

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions that the tool returns endpoint details, parameters, auth info, and code snippets, which adds some context about output. However, it lacks critical behavioral traits such as whether this is a read-only operation, potential rate limits, error handling, or any side effects. For a search tool with no annotations, this is a significant gap.

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 well-structured and front-loaded, starting with the core purpose, followed by return details, and then parameter explanations. Every sentence earns its place by adding value, with no redundant or unnecessary information. It's appropriately sized for a tool with two parameters.

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 tool's moderate complexity (2 parameters, no annotations, but with an output schema), the description is fairly complete. It covers the purpose, return values, and parameter semantics. Since an output schema exists, it doesn't need to detail return values further. However, it could improve by addressing behavioral aspects like error cases or performance expectations to be fully comprehensive.

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 schema description coverage is 0%, so the description must compensate. It provides clear semantics for both parameters: 'query' is described as a natural language description with an example, and 'auto_discover' is explained as controlling automatic discovery of new APIs. This adds meaningful context beyond the bare schema, though it could include more details like format constraints or implications of the boolean setting.

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: 'Search for an API capability using natural language.' It specifies the verb 'search' and resource 'API capability,' making it easy to understand what the tool does. However, it doesn't explicitly differentiate from its siblings (semantic_discover, semantic_discover_url), which keeps it from a perfect score.

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 by stating it searches for API capabilities using natural language, but it doesn't provide explicit guidance on when to use this tool versus its siblings. There's no mention of alternatives or specific contexts where this tool is preferred, leaving the agent to infer usage from the purpose alone.

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