Basal delivery state timeline

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

With no annotations, the description carries the full burden and does an excellent job: it explains the meaning of each state, that output is collapsed intervals rather than raw points, that times are device-local wall clock (not UTC), and that results are capped. It even details the conditional intervals array and the summary metrics returned.

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 fairly long but every clause earns its place: state definitions, use cases, the critical units distinction, time semantics, cap rationale, and return shape. The most important semantic warning — states not insulin amounts — 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?

There is no output schema, but the description compensates by stating exactly what the agent will receive: per-state minute/percentage summaries and an optional intervals array with start, end, and minutes. Combined with thorough parameter schema text and timezone clarification, an agent has enough to select and invoke the tool correctly.

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; the description adds a little extra by reiterating the wall-clock caveat and explaining why the time span is capped ('returns collapsed intervals, not raw points'). Most parameter-level detail already lives in the schema, so the added marginal value is moderate, not maximal.

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 exactly what the tool returns: a timeline of basal algorithm states (normal/suspend/max/limited), not insulin amounts. It explicitly differentiates from get_daily_insulin, making it easy for an agent to distinguish this from sibling tools.

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 gives concrete scenarios for using the tool — investigating lows, rebound patterns, system workload, and limited mode coinciding with excursions. It also tells agents when NOT to use it: when they need basal units, use get_daily_insulin instead.

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