smartSearch

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description adds that the tool both executes the query and returns the generated SearchQuery, which is useful, but it discloses no LLM-nondeterminism, schema-fetching, or failure-mode context for a tool that generates queries from free text.

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?

Three sentences, front-loaded with the core action, then illustrative examples, then the routing rule. Each sentence earns its place and there is no filler.

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?

An output schema exists, so return-value detail is not required in the description, and the description still summarizes the return shape. Combined with 100% parameter coverage and full annotations, an agent has everything needed to call this correctly.

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 100% and both parameters are documented in the schema, so baseline 3 applies. The description mentions reliance on 'the project schema' but adds no syntax, format, or intent detail for prompt or currentQuery beyond what the schema already says.

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 chain (convert, execute, return) over a specific resource (natural-language question → RushDB SearchQuery) and names what it returns. It is clearly distinguishable from the semanticSearch and vectorSearch siblings without opening any schema.

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?

Gives an explicit when-to-use trigger ('user-facing questions such as "Who are piloting Falcon?"') and an explicit alternative with the condition that selects it ('For direct vector similarity over an embedding index, use vectorSearch instead'). Nothing is left to inference.

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