log_daily_metric

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

With no annotations provided, the description carries the full behavioral burden and succeeds: it discloses row creation, partial-write semantics, and the fact that nulls are untouched. This is exactly the kind of behavioral context an agent needs before calling a mutating tool.

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?

Three sentences with no filler. The core purpose is front-loaded, and every sentence contributes either behavioral semantics or usage guidance. The description is compact yet rich.

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 an output schema (per context), so return-value prose is unnecessary. The description covers creation, partial updates, null behavior, and the correct sibling for undo. Nothing an agent needs to call this correctly is missing.

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%, giving the baseline 3, but the description adds meaningful parameter behavior beyond the schema: only passed metrics are written, nulls are not touched, and at least one metric is implied. This improves the agent's understanding of how the nullable parameters actually behave.

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 opens with a specific verb and resource: 'Record one or more health metrics for a single day.' It also distinguishes itself from siblings by explicitly naming clear_metric for undo operations, so an agent can tell logging from reading or clearing without ambiguity.

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?

It clearly states when to use the tool (logging metrics for a day) and when not to ('To undo a value logged by mistake, use clear_metric'). It also explains the partial-update behavior, which prevents agents from thinking they must re-send all values.

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