Brewers almanack

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 specific recipe components, but doesn't describe whether this is a read-only operation, if it requires authentication, rate limits, or how recipe suggestions are generated (e.g., based on databases, AI, user preferences). For a tool with zero annotation coverage, this leaves significant behavioral 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 extremely concise and front-loaded: a single sentence that states the action ('Suggest a beer recipe'), the target ('for a target style'), and enumerates the return values. Every word earns its place with zero waste or redundancy.

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 complexity of recipe generation, no annotations, and no output schema, the description is incomplete. It doesn't explain what constitutes a valid 'style', how recipe suggestions are derived, error conditions, or the structure of returned data. For a tool with 2 parameters and significant domain complexity, this leaves too many unanswered questions for effective agent use.

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 fully documents both parameters ('style' and 'batch_size_litres'). The description adds no additional parameter semantics beyond what's in the schema—it doesn't explain format expectations for 'style' (e.g., specific style names) or practical implications of 'batch_size_litres'. Baseline 3 is appropriate when the schema does all the work.

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: 'Suggest a beer recipe for a target style' with specific outputs listed (grain bill, hop schedule, yeast selection, process parameters). It distinguishes from siblings like 'search_styles' or 'search_ingredients' by focusing on recipe generation rather than information lookup. However, it doesn't explicitly contrast with 'diagnose_off_flavour' or 'pairing_guide', which are also recipe-related but serve different purposes.

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 doesn't mention when to choose 'suggest_recipe' over 'search_ingredients' for ingredient selection, or how it differs from 'match_water_profile' in recipe development. There's no context about prerequisites, such as needing a valid beer style, or limitations like batch size constraints.

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