suggest

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the tool returns a 'JSON response containing a list of relevant autocomplete suggestions,' which is helpful, but lacks details on rate limits, authentication needs, error handling, or how suggestions are generated (e.g., based on popularity or 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 appropriately sized and front-loaded, with the first sentence clearly stating the purpose. However, the second sentence is slightly redundant ('You can send a request...') and could be more streamlined, though overall it avoids unnecessary verbosity.

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 (2 parameters, no output schema, no annotations), the description is adequate but incomplete. It covers the basic function and response format but lacks details on usage context, behavioral traits, or how to interpret the output, which would be helpful for an AI agent.

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%, so the schema already documents both parameters ('keyword' and 'lr'). The description adds some context by explaining that 'keyword' represents 'partial text entered by the user,' but doesn't provide additional meaning beyond what the schema offers, such as examples or constraints.

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 autocomplete suggestions or query predictions as a user types a search query.' It specifies the verb ('get') and resource ('autocomplete suggestions'), but doesn't explicitly differentiate it from sibling tools like 'search' or 'latest', which likely serve different functions.

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 tool's function but doesn't specify scenarios where it's preferred over sibling tools like 'search' or indicate any prerequisites or exclusions for usage.

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