get_activity_timeseries

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

Without annotations, the description carries full responsibility for behavioral disclosure. It does disclose two useful behaviors: the data is second-by-second and downsampled to max_points. However, it does not address potential edge behaviors such as variable series availability by activity type, empty series handling, or any auth/rate-limit considerations that would matter to an agent deciding whether this call is safe or appropriate.

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 tight and front-loaded: one sentence captures the core behavior and scope, followed by a compact, well-labeled argument list. Every sentence earns its place, and the Args block is justified because the schema provides no descriptions.

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 an output schema present, the description does not need to explain return structureBasic correctness is fully covered: required parameter, optional parameter with default, and the data's granularity and downsampling behavior. It could add one detail: that series availability may depend on activity type (e.g., power for cycling, pace for running), but this is a minor gap given the supported series list.

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%, yet the description fully compensates for both parameters. It explains that activity_id is the Garmin activity ID from get_recent_activities, and that max_points caps samples per series with its default value. This goes well beyond the bare schema, adding provenance and semantics that an agent needs to call the tool correctly.

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 what the tool returns: second-by-second chart data of an activity as named series, and it enumerates the series types (heart rate, pace, altitude, cadence, power, temperature...). This specificity distinguishes it from activity-level summaries like get_activity_details and single-series timelines like get_heart_rate_timeline. The only minor weakness is that it omits an explicit verb like 'retrieve', but the meaning is unambiguous.

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 description conveys when to use the tool (when you need multi-series intra-activity chart data) and provides the prerequisite that activity_id comes from get_recent_activities. However, it does not explicitly mention alternatives or exclusions, such as 'if you only need heart rate, use get_heart_rate_timeline'. The usage context is clear but not fully explicit about routing among the many sibling timeline endpoints.

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