trend

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

The description adds substantial behavioral context beyond the annotations: it explains the output structure (series, change per 30 days, direction), notes that daily grouping adds a 7-day rolling average, clarifies that missing data is marked 'not recorded' and must never be treated as zero, and adds a medical disclaimer. These details materially help an agent interpret results correctly.

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 four sentences with no wasted content, front-loading the core purpose and then adding only useful behavioral caveats. The 'I4.' prefix is minor noise but does not undermine clarity or structure.

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 presence of an output schema and full parameter schema coverage, the description is complete enough to call and interpret the tool correctly. It covers scope, grouping behavior, missing data semantics, and the informational-only caveat.

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%, so the baseline is 3, but the description adds meaning about the group_by parameter by explaining that daily grouping adds a 7-day rolling average. It also reinforces the 366-day maximum window, though metric enum semantics remain entirely in the schema.

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 a specific operation: computing the trend of one metric over up to 366 days, with series, 30-day change, and direction. It implicitly distinguishes itself from point-in-time sibling tools like get_hrv or get_sleep by emphasizing multi-day trend analysis, though it does not name any sibling explicitly.

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?

Usage is implied through the scope ('up to 366 days', 'by day, week or month') and output description, but there is no explicit guidance on when to choose this tool versus compare_periods or weekly_review. It also does not state exclusions or prerequisites.

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