search_entities

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

Despite no annotations, the description is transparent: it explains the search functionality, returns a JSON array, and uses Lucene syntax. It does not explicitly state read-only behavior, but the examples imply no side effects. The description adequately discloses the core behavior.

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 concise and well-structured: a one-line summary, then Args, Returns, and Examples. Every sentence is purposeful, no redundancy. The format is front-loaded and easy to 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?

The description covers the essential aspects: entity types, query syntax, limit, fields, and return format. With an output schema present, the return description is sufficient. Minor omissions (e.g., pagination) are acceptable for a search tool.

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?

With 0% schema coverage, the description fully compensates by detailing each parameter: entity types, Lucene query, limit range (1-500, default 20), and fields as comma-separated. Examples illustrate valid values, adding substantial meaning beyond the schema.

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 starts with 'Search any Bullhorn entity type using Lucene query syntax,' which clearly specifies the action (search) and the resource (any entity type). It distinguishes from sibling tools like get_candidate and list_candidates, which retrieve single entities or lists without search syntax.

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 when a Lucene query is needed, but it does not explicitly state when to use this tool versus alternatives like query_entities. No exclusions or when-not-to-use guidance is provided, leaving the agent to infer context from examples.

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