semantic-search

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It explains the technique (vector embeddings) and a prerequisite, but does not disclose behaviors like result ranking, performance characteristics, or error handling beyond what is implied by the schema.

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 a single sentence that efficiently conveys the tool's purpose, technique, and requirement without any redundant or vague language.

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 search tool with 10 parameters and no output schema or annotations, the description is adequate but incomplete. It covers the core purpose and a prerequisite, but lacks information about output format, result interpretation, or guidance on when to use this over other search tools.

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 has 100% description coverage with clear examples for each parameter. The tool description does not add additional parameter-level details beyond what the schema provides, so the baseline score of 3 is appropriate.

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 identifies the tool as a natural-language semantic search over OpenMetadata entities using vector embeddings, distinguishing it from sibling search tools like 'search-metadata' and 'suggest-metadata' which are likely keyword-based. The specific verb and resource are well-defined.

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 mentions a requirement (OM 1.12+ with semantic search enabled), which provides usage context, but does not explicitly state when to use this tool versus alternatives such as standard search or suggest. The usage is implied but lacks exclusions or comparisons.

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