calculate_fueling_plan

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description must carry the burden. It discloses the computational nature (calculates targets) and the output (returns a product list). However, it does not explicitly state that the tool has no side effects or what the output format looks like, leaving some ambiguity.

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?

Two concise sentences: the first states the core action, the second provides usage examples. No wasted words; every sentence adds value.

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?

The description covers the core purpose and usage but lacks details about the output format (e.g., how targets are returned) and does not explain how parameters influence the calculation beyond what is in the schema. For a tool with 9 parameters and no output schema, more completeness would be beneficial.

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 coverage is 100%, with all 9 parameters having descriptions in the schema. The description adds no additional parameter-specific information beyond the schema. Baseline score for high coverage is 3.

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 calculates personalized race nutrition targets and returns matching Lecka products. It distinguishes itself from sibling tools like get_nutrition_data and get_products by focusing on race-specific planning with product recommendations.

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 explicitly says 'Use this when an athlete asks what to eat during a race, how many gels they need, or what their carb target should be.' This provides clear when-to-use guidance, though it does not explicitly state when not to use or contrast with siblings.

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