query_workout_series

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

Annotations already declare readOnlyHint/idempotent/non-destructive, but the description adds substantial context beyond them: local SQLite only, no cloud request or automatic sync, requires a configured local account/cache, error status for unknown workout IDs, and the important caveat that empty lists mean no cached matches rather than zero measurements. The downsampling/clamping behavior and the 500-point hard cap are also disclosed.

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-loads the core purpose in the first sentence, then layers contract, semantics, and caveats. It is dense and long, but nearly every clause carries operational information; a few items (contract string, source=cache) are borderline overhead.

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, yet the description enumerates the returned fields (t offsets, bpm, downsampled/source_points/returned_points/method, summary statistics) and the envelope (status, source, generated_at, data). For a read tool with five parameters and no output schema, nothing material is missing.

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 the schema does not: the resolution/max_points interaction ('resolution defaults to 60 seconds and increases to respect max_points') and the cross-activity comparability rationale for reference_max_hr. These go beyond the per-field schema text.

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?

States a specific verb+resource ('Read an auto-downsampled heart-rate curve for one workout_id') and scopes it to a single workout rather than a date range, which distinguishes it from query_heart_rate and query_metric_series. It also names the contract identifier, so an agent can identify the exact operation.

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?

Explicitly routes the agent: 'For raw date-range samples use query_heart_rate', 'Use get_data_coverage to inspect availability or sync_data to refresh with user consent'. It also gives the conditional rule for reference_max_hr (pass the same value for comparable time_in_zone, omit otherwise), which is real when-to-use guidance.

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