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. It discloses the tool's behavior by stating it returns multiple data points (compound, causes, prevention, etc.), but doesn't mention limitations like accuracy, data sources, or error handling. It adds some context but leaves gaps in behavioral traits.

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, well-structured sentence that efficiently conveys the tool's function and output without unnecessary words. It's front-loaded with the core purpose and includes all essential details, making it highly concise and effective.

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 (diagnostic analysis), no annotations, and no output schema, the description does a good job by specifying the input purpose and detailed output structure. However, it could be more complete by addressing potential limitations or data sources, which would help an agent use it more effectively.

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, so the baseline is 3. The description adds value by clarifying that the parameter is for 'taste or aroma description of the off-flavour', providing semantic context beyond the schema's generic 'description' field, but doesn't detail format or examples.

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 ('diagnose', 'returns') and resources ('beer off-flavours', 'taste or aroma descriptions'), distinguishing it from sibling tools like 'search_styles' or 'suggest_recipe' by focusing on problem identification rather than recipe creation or ingredient lookup.

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 a user has a taste/aroma description of an off-flavour, but it doesn't explicitly state when to use this tool versus alternatives (e.g., 'search_ingredients' for ingredient-related issues) or provide exclusions. The context is clear but lacks explicit guidance on tool selection.

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