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

With no annotations, the description carries the burden of behavioral disclosure. It reveals the hybrid semantic + keyword search mechanism, implies the result structure by referencing 'file_path', and gives guidance on deducing the development model. It does not describe pagination, rate limits, or exact response format, but it provides enough behavioral context for a read-only search operation.

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: a concise purpose statement followed by an explicit topic list, then actionable usage guidance. The topic list is long but directly relevant for helping an agent decide when to use the tool. No repetitive or filler content; front-loads the core purpose.

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 tool is moderately complex with 5 parameters and no output schema. The description compensates by explaining the search strategy, hinting at result fields (file_path), and providing integration with get_full_document for full context. It does not detail result ranking or snippet content, but it gives sufficient information for an agent to invoke the tool and interpret results in context.

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 description coverage is 100%, with each parameter already documented in the input schema. The description adds limited extra meaning by reinforcing the ui_language parameter's role ('use java for Java-based views, react for React-based views, or common for both'), but it does not explain max_tokens or max_results beyond the schema. Since the schema handles the semantics, the baseline score of 3 applies.

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 function: 'Search Vaadin documentation for relevant information about Vaadin development, components, and best practices.' It uses a specific verb ('Search') and resource ('Vaadin documentation'), enumerates topics, and distinguishes itself from sibling tools like get_component_java_api which target specific API details rather than broad search.

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 provides explicit when-to-use guidance with a detailed topic list ('USE THIS TOOL for questions about: Vaadin components... any Vaadin-specific topics') and instructs to use get_full_document when more context is needed. However, it does not explicitly state when to prefer sibling tools like get_component_java_api for focused API lookups, so it lacks a full when-not comparison.

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