get_food_log

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

With no annotations, the description carries full burden. It mentions the return content (entries with macros and micros) but does not disclose behaviors like pagination, error handling, or performance implications. The transparency is adequate but not detailed.

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 concise: two short paragraphs with front-loaded purpose, a usage hint, and well-structured parameter descriptions. Every sentence adds value without 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?

The tool has a simple interface with two optional parameters and has an output schema. The description covers the return content, usage context, and parameter details. Minor omission: no mention of behavior when no entries exist for the date range.

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 0%, so the description must compensate. It explains the date format (YYYY-MM-DD) and default behavior (defaults to today) for both parameters. This adds value beyond the schema's type and title.

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) and resource (food log with individual entries and full nutrition). It distinguishes from sibling tools like get_daily_nutrition or get_micronutrients by emphasizing detailed entries and micronutrients.

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 a use case ('great for analyzing what was eaten and spotting nutrient gaps') and implies when to use it for detailed analysis. However, it does not explicitly contrast with siblings or state when not to use.

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