dashboard_data

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so safety and external-fetch behavior are covered by structured data. The description adds genuinely new behavioral context: the payload is compact and series values are null where Garmin has no data, which prevents misreading gaps as zeros. It stops short of describing cost/latency for what is clearly an aggregate over many upstream calls.

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?

Purpose is front-loaded in the first clause, followed by a contents list and a short usage directive. The long enumeration of sections is load-bearing since there is no output schema, though it could be tightened into grouped phrasing rather than a comma chain.

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?

With no output schema, the description carries the burden of explaining return values and does list the major sections, which is adequate. But the one parameter is undocumented, the '30 days' versus 'default 90' tension is unresolved, and there is no hint about payload size or upstream call cost for an aggregate tool pulling many endpoints.

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 description coverage is 0% and the single 'days' parameter (default 90) is never mentioned in the description. Worse, the description says the bundle includes 'the last 30 days of activities,' which reads as a fixed window and creates ambiguity about whether 'days' controls that section or only the series. The agent has no guidance on what changing 'days' actually affects.

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 names a specific artifact ('compact JSON bundle for building a dashboard') and enumerates its contents: snapshot, daily series, weekly rollups, load focus, activities and power profile. That is far more concrete than a tautology and implicitly separates it from single-metric siblings like timeseries or chart. It does not explicitly name a sibling for differentiation, so it falls short of a 5.

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 sentence 'Embed it as data in the page rather than re-deriving numbers' gives one clear usage directive and implicitly steers away from calling chart or timeseries repeatedly. However, there is no statement of when NOT to use it, no prerequisites (does it require a configured athlete or prior sync?), and no comparison to daily/weekly_report which likely overlap in content.

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