local_descriptions

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

With no annotations, the description carries the full burden of behavioral disclosure. It mentions fetching via an external API, which implies network usage and potential rate limits, but doesn't specify authentication needs, error handling, or what 'AI-generated' entails. It lacks details on response format, pagination, or data freshness.

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 with zero waste. It's front-loaded with the core purpose and includes the API source, making it easy to parse quickly without unnecessary elaboration.

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 no annotations, 0% schema coverage, and no output schema, the description is incomplete. It doesn't cover parameter semantics, behavioral traits like rate limits or errors, or return values. For a tool with external API dependencies and one required parameter, this leaves significant gaps for the 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 0%, so the description must compensate for undocumented parameters. It doesn't explain the 'ids' parameter—what these IDs represent, their format, or how to obtain them. The description adds no meaning beyond the bare schema, leaving the agent guessing about input requirements.

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 action ('Fetch AI-generated descriptions') and resource ('for locations'), specifying it uses the Brave Local Search API. It distinguishes from 'local_pois' (likely points of interest) and 'web_search' (general search) by focusing on location descriptions, but doesn't explicitly differentiate from 'rich_fetch' (which might be similar).

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?

No guidance is provided on when to use this tool versus alternatives like 'local_pois' or 'rich_fetch'. The description implies it's for location descriptions, but doesn't specify use cases, prerequisites, or exclusions, leaving the agent to infer context from tool names alone.

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