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 effectively describes key behaviors: the tool returns detailed information (listing specific data points like addresses and ratings), handles location-based queries, and includes a fallback mechanism to web search. However, it lacks details on error handling, rate limits, or authentication needs, which would be valuable for a tool with no annotations.

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 and front-loaded with the core purpose, followed by usage guidelines and behavioral details. Each sentence adds value: the first states the action and API, the second specifies use cases, the third lists return data, and the fourth provides usage context and fallback behavior. There is no wasted text.

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 largely complete. It covers purpose, usage, return data, and fallback behavior. However, without annotations or an output schema, it could benefit from more details on response format or error cases, but it adequately supports agent selection and invocation.

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 schema description coverage is 100%, so the schema already documents both parameters ('query' and 'count') with descriptions and constraints. The description adds minimal value beyond the schema by providing an example query ('pizza near Central Park') and implying the 'query' parameter should be location-focused, but it does not explain the semantics of 'count' or add significant context. This meets the baseline for high schema coverage.

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 specific action ('Searches for local businesses and places') and resource ('using Brave's Local Search API'), distinguishing it from the sibling tool 'brave_web_search' by focusing on physical locations and businesses. It explicitly mentions the types of queries it handles (e.g., 'near me', specific locations).

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 guidance on when to use this tool ('Best for queries related to physical locations, businesses, restaurants, services, etc.' and 'Use this when the query implies 'near me' or mentions specific locations') and mentions an alternative behavior ('Automatically falls back to web search if no local results are found'), which implicitly contrasts with the sibling tool 'brave_web_search'.

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

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 and does this well. It reveals important behavioral traits including maximum results per request (20), pagination support with offset, content filtering capabilities, freshness controls, and the general nature of the search. It doesn't mention rate limits or authentication requirements, but provides substantial 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 perfectly structured and concise - three sentences that each earn their place. The first establishes purpose and ideal use cases, the second provides operational context, and the third specifies limitations. No wasted words, front-loaded with the most important information.

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?

For a search tool with no annotations and no output schema, the description provides substantial context about behavior, limitations, and use cases. It covers the essential operational aspects (pagination, filtering, freshness controls, result limits) but doesn't describe the return format or structure of results, which would be helpful given the lack of output schema.

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?

With 100% schema description coverage, the schema already documents all three parameters thoroughly. The description adds some context about pagination ('Supports pagination... with offset for pagination') and result limits ('Maximum 20 results per request'), but doesn't provide additional semantic meaning beyond what's in the schema descriptions. This meets the baseline for high schema coverage.

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 with specific verbs ('performs a web search') and resources ('using the Brave Search API'), distinguishing it from the sibling tool 'brave_local_search' by specifying it's for general web content rather than local searches. It explicitly mentions the types of content it's ideal for (general queries, news, articles, online content).

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 clear context for when to use this tool ('for broad information gathering, recent events, or when you need diverse web sources'), but doesn't explicitly state when NOT to use it or provide specific alternatives beyond the implied sibling tool distinction. It offers good guidance but lacks explicit exclusions or named alternatives.

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