get_recipe

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 performance characteristics (e.g., '5-10x faster than sequential requests', '70%+ cache hit rate'), error handling ('individual failures don't break entire batch'), and response format details. However, it doesn't explicitly mention whether this is a read-only operation or if it requires authentication, leaving some behavioral aspects implicit.

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 with clear sections (e.g., 'Batch Processing System', 'LLM Usage Patterns'), but it's quite lengthy with multiple subsections and performance examples. While all content is relevant, it could be more front-loaded; the core purpose appears in the first sentence, but detailed usage patterns come later. Some redundancy exists between the description and schema descriptions.

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 complexity (6 parameters, batch processing capabilities) and the presence of an output schema (implied by 'Has output schema: true'), the description is highly complete. It covers purpose, usage guidelines, behavioral traits, parameter interactions, performance characteristics, and response format details. The output schema likely handles return values, so the description appropriately focuses on other contextual aspects.

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 all six parameters thoroughly. The description adds value by organizing parameters into usage patterns ('Input Methods') and explaining how they interact (e.g., 'Mixed Batch' combining names and IDs), but doesn't provide significant semantic information 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: 'Advanced recipe retrieval with powerful batch processing for multiple cocktails.' It specifies the verb ('retrieval') and resource ('recipes'), and distinguishes from siblings like 'get_ingredient_info' and 'smart_search_cocktails' by focusing on recipe retrieval rather than ingredient information or search functionality.

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 through the 'LLM Usage Patterns' section, listing scenarios like single recipe requests, recipe comparison, menu planning, variation exploration, and research mode. It also offers detailed 'Input Methods' with specific use cases for each parameter combination, helping the agent choose appropriate inputs based on context.

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