autocomplete

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 predictions but does not describe key behaviors like response format, pagination, rate limits, authentication needs, or error handling. For a tool with no annotation coverage, this is a significant gap, as the agent lacks essential operational context.

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, efficient sentence that front-loads the core functionality without unnecessary words. It directly states what the tool does, making it easy to parse and understand quickly. There is no wasted verbiage, and it effectively communicates the purpose in a compact form.

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 moderate complexity (4 parameters, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose but lacks details on behavior, usage guidelines, and output structure. Without annotations or an output schema, the agent must infer missing information, making the description incomplete for reliable tool invocation in more complex scenarios.

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%, meaning the input schema fully documents all parameters. The description does not add any semantic details beyond what the schema provides, such as explaining how parameters interact or providing usage examples. Since the schema handles the heavy lifting, a baseline score of 3 is appropriate, as the description neither compensates for gaps nor adds extra value.

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 'returns place/address, business and query predictions for text-based geographic queries,' which specifies the verb (returns), resources (place/address, business, query predictions), and scope (text-based geographic queries). However, it does not explicitly differentiate from sibling tools like 'search' or 'bulk_search,' which may also handle geographic queries, leaving some ambiguity about when to choose this tool over others.

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 no guidance on when to use this tool versus alternatives. It mentions the purpose but does not specify scenarios, prerequisites, or exclusions, such as comparing it to 'search' or 'bulk_search' for similar geographic queries. This lack of context makes it challenging for an AI agent to select the appropriate tool without additional inference.

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