ureweries

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 action ('Find breweries') but doesn't describe key traits like whether it's a read-only operation, potential rate limits, error handling, or the format of results. This leaves significant gaps in understanding how the tool behaves beyond its basic purpose.

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: 'Find breweries located in a specific city.' It is front-loaded with the core purpose, has zero wasted words, and is appropriately sized for the tool's complexity. Every part of the sentence earns its place by clearly conveying the tool's function.

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 incomplete. It lacks details on behavioral traits, usage context, and result handling. Without annotations or an output schema, the description should provide more context to help the agent invoke the tool correctly, but it falls short, leaving gaps in understanding.

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 input schema has 100% description coverage, with clear details for both parameters ('city' and 'limit'). The description adds no additional meaning beyond what the schema provides, such as explaining parameter interactions or edge cases. Since the schema does the heavy lifting, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.

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: 'Find breweries located in a specific city.' This includes a specific verb ('Find') and resource ('breweries'), and it specifies the scope ('in a specific city'). However, it does not explicitly differentiate from sibling tools like 'get_brewery' or 'search_breweries', which might have overlapping or distinct functionalities, so it doesn't reach the highest score.

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 lacks any mention of sibling tools, prerequisites, or exclusions. For example, it doesn't clarify if this is for exact city matches or broader searches, leaving the agent to infer usage without explicit direction.

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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states this is a read operation ('Get'), but doesn't mention any behavioral traits like error handling (e.g., what happens if the ID is invalid), rate limits, authentication needs, or response format. For a tool with no annotation coverage, this leaves significant gaps in understanding how it behaves.

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 purpose ('Get full details for a specific brewery') and specifies the key constraint ('by its Open Brewery DB ID'). There is no wasted verbiage, and every word earns its place in clarifying the tool's function.

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 low complexity (single parameter, no nested objects) and high schema coverage, the description is minimally adequate. However, with no annotations and no output schema, it lacks details on behavioral aspects like error handling or response structure. For a simple lookup tool, this is acceptable but leaves room for improvement in transparency.

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%, with the single parameter 'id' fully documented in the schema as the Open Brewery DB brewery ID with an example. The description adds no additional parameter semantics beyond what the schema provides, such as format constraints or usage notes. Baseline 3 is appropriate when 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 verb ('Get full details') and resource ('for a specific brewery'), making the purpose unambiguous. It specifies the lookup mechanism ('by its Open Brewery DB ID'), which distinguishes it from siblings that filter by city or search broadly. However, it doesn't explicitly contrast with sibling tools like 'breweries_by_city' or 'search_breweries' in the description text itself.

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 implies usage when you have a specific brewery ID and need full details, which is clear from context. However, it doesn't explicitly state when to use this tool versus alternatives like 'search_breweries' for broader queries or 'breweries_by_city' for location-based filtering. No exclusion criteria or prerequisites are mentioned.

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 full burden for behavioral disclosure. It mentions the return format ('list of matching breweries with location and contact details') which is helpful, but doesn't cover important aspects like pagination behavior, rate limits, authentication requirements, error conditions, or whether this is a read-only operation. For a search tool with zero annotation coverage, this represents significant gaps.

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 concise with two sentences that efficiently convey the core functionality and return format. It's front-loaded with the main purpose. While slightly more detail about behavioral aspects could improve it, every sentence earns its place, warranting a score of 4.

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 2 parameters (100% schema coverage) and no output schema, the description provides adequate but incomplete context. It covers the basic purpose and return format but lacks behavioral details that would be important for an AI agent. Without annotations or output schema, the description should do more to explain how results are structured and what limitations exist.

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 thoroughly. The description adds minimal value beyond the schema - it mentions searching 'by name' which aligns with the 'query' parameter description, but doesn't provide additional context about parameter interactions or search semantics. This meets the baseline of 3 when 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: 'Search for breweries by name' specifies the verb (search) and resource (breweries). It distinguishes from 'breweries_by_city' by focusing on name-based search rather than location, but doesn't explicitly differentiate from 'get_brewery' which might retrieve a single brewery by ID. This earns a 4 for clear purpose without full sibling differentiation.

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 like 'breweries_by_city' or 'get_brewery'. It doesn't mention prerequisites, exclusions, or contextual factors. This lack of comparative usage information results in a score of 2.

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