Break a metric down by source

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

Annotations already declare readOnly, idempotent, non-destructive behavior, and the description adds meaningful context beyond that: it explains the data becomes part of the conversation and may be sent to a cloud model. This is a real behavioral disclosure about data flow and privacy that an agent could not infer from the schema or annotations.

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: purpose leads, a do-not-use block clearly distinguishes the sibling tool, and the privacy note is placed at the end. It is longer than strictly necessary because of the privacy explanation, but each paragraph earns its place and the key information is front-loaded.

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 simple two-parameter input, full schema coverage, output schema presence, and complete annotations, the description covers what an agent needs to call this tool correctly. The only minor gap is that it does not spell out the exact return shape or whether source values are normalized, but the output schema covers that burden.

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?

The schema covers 100% of the two parameters, including formats and examples for `date` and `metric`. The description does not add much beyond the schema, but the terms 'one day' and 'metric' reinforce the single-day, single-metric scope. The schema does the heavy lifting, so a baseline 3 is appropriate.

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 states a concrete action and resource: 'Show one metric's raw measurements for one day, broken down by which source reported them.' It directly distinguishes the tool from the sibling `get_metric_history` by emphasizing the per-source breakdown and the 'which one is correct?' use case. The verb and scope are specific enough that an agent can tell what it is for.

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 names the alternative: 'Do not use this tool when... use `get_metric_history` instead.' It also gives a concrete triggering scenario (e.g., Apple Watch and Garmin disagreeing on resting heart rate), making both when-to-use and when-not-to-use clear.

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