get_glucose_stats

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

With no annotations, the description carries the full burden and does real work: it discloses the default lookback window and the Share maximum on span, that target thresholds come from DEXCOM_TARGET_LOW/HIGH with 70-180 mg/dL fallbacks, and that percentages are weighted by reading count rather than time. It stops short of stating read-only semantics or behavior on empty/insufficient data, which is reasonable for an obviously read-only aggregation.

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?

Front-loaded with what the tool returns, then short parameter notes in descending order of importance; almost no filler. The line-broken style is terse to the point of being slightly fragmented, but nothing repeats the schema verbatim.

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?

No output schema and no annotations, so the description must enumerate results — and it does list the full return payload plus defaults and units. Missing pieces are the `units` parameter's effect and edge-case behavior (no data, window exceeding 24h), which keep it from being fully self-contained.

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 0% with five parameters, so the description has to compensate and mostly does: start/end are pinned to ISO 8601 with a stated default and maximum span, and target_low_mg_dl/target_high_mg_dl get units, defaults, and an environment-variable source. The `units` parameter is left completely unexplained, a notable gap given the description insists thresholds are in mg/dL.

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?

It names a specific resource (glucose) and enumerates exactly what is computed: mean, SD, CV, GMI, min/max, and time-in/below/above range. That is far more than a restatement of the name, though it never explicitly distinguishes itself from the siblings get_glucose and get_current_glucose (aggregate vs. raw/instantaneous readings is only implied).

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 only implied: the 'last 24 hours, the Share maximum' default and the target-range defaults tell the agent what typical calls look like, but there is no explicit statement of when to choose this over get_glucose or get_current_glucose, and no exclusions or prerequisites.

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