log_hydration

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

No annotations are provided, so the description carries full burden for behavioral traits. It correctly hints at a write operation ('Add') and adds context about milliliters (e.g., '250 is a glass') and day defaults. However, it does not disclose what happens on success/failure, authentication needs (likely required for Garmin), rate limits, or side effects (e.g., overwriting existing entries on the same day). This is adequate but not rich.

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—two short sentences plus an Args block with two parameters. Every sentence adds value (purpose, measurement context, default behavior). No wasted words. The structure is front-loaded and easy to scan.

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 low complexity (2 params, no nested objects), the description is fairly complete. However, it lacks any info about the output schema (which exists), such as what the tool returns (confirmation, updated log, error). It also omits behavioral details like idempotency or whether the same day can be updated multiple times. An output schema exists, so return value details are partially excused, but the description could still mention what a successful response looks like.

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 0%, so the description must compensate fully. It explains 'milliliters' with a helpful real-world equivalence ('250 is a glass') and clarifies 'day' defaults to today. These add substantial meaning beyond the raw schema fields (which only provide types and a default string). Both parameters are well-explained.

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 action ('Add drunk water'), the resource ('hydration log'), and the platform ('Garmin Connect'). It is specific and distinct from siblings, which mostly deal with reading or logging other types of data (e.g., log_weight, get_daily_summary, create_workout).

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 gives clear use context (logging water to Garmin) but provides no explicit when-to-use or when-not-to-use guidance, nor does it compare with alternative tools (e.g., log_weight for weight or other logging tools). Some guidance can be inferred from sibling names but is not stated.

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