auto_complete

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 states the tool returns suggestions and mentions data usage with another endpoint, but fails to describe key traits: whether it's read-only, how it handles errors, rate limits, authentication needs, or the format of returned suggestions. For a query tool with zero annotation coverage, this is a significant gap in transparency.

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 with two sentences, front-loading the core purpose. However, the second sentence about endpoint usage is somewhat vague ('.../properties/list endpoint') and could be more specific. Overall, it's efficient with minimal waste, though not perfectly structured.

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 complexity (a query tool with no annotations and no output schema), the description is incomplete. It lacks details on return values, error handling, and behavioral traits. While it hints at a workflow with another endpoint, this is insufficient for the agent to fully understand tool behavior and integration. More context is needed for adequate completeness.

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 description does not add parameter semantics beyond the input schema. Schema description coverage is 100%, with the 'query' parameter well-documented in the schema (e.g., 'Any term or phrase...'). The description only mentions 'term or phrase' without providing additional context, syntax, or examples. Baseline score of 3 is appropriate as the schema does the heavy lifting.

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: 'Get suggestions by term or phrase.' This specifies the verb ('Get suggestions') and the resource ('term or phrase'), making it understandable. However, it doesn't explicitly differentiate from sibling tools like 'propertieslist' or 'propertiesv3lookup', which might also involve querying properties, so it misses full sibling distinction.

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 minimal usage guidance: it mentions that returned data is used with another endpoint ('.../properties/list endpoint'), implying a workflow context. However, it lacks explicit when-to-use instructions, alternatives (e.g., vs. 'propertieslist' or 'propertiesv3lookup'), or exclusions. This leaves the agent with little direction on tool selection.

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