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bosch_get_activities

Retrieve e-bike ride summaries with per-ride metrics including distance, elevation, speed, cadence, power, calories, assist modes, CO2, and brake events, filterable by date and bike.

Instructions

List e-bike rides with per-ride summary metrics.

Live read from the Bosch rider-activity API (no cache). Each ride includes distance, elevation gain/loss, avg/max speed, cadence, measured rider power, calories, rider-vs-motor energy share, assist-mode distance split (metres per mode), CO2 (emissions / car-equivalent / saved), and ABS/brake events. Heart rate is not recorded by the bike (it has no HR sensor) - pair with a wrist device for HR.

Args: start_date: Window start (YYYY-MM-DD, YYYY-MM, or "30d"). Default 30 days ago. end_date: Window end. Default today. bike_id: Optional bike UUID filter. limit: Optional cap on rides returned (most recent first).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
bike_idNo
end_dateNo
start_dateNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations, the description carries full transparency burden. It discloses live read/no-cache behavior, lists all included metrics, and explicitly notes that heart rate is not recorded (with guidance to pair a wrist device). This goes beyond a minimal read-only description, though it omits potential rate limits or auth requirements.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured: purpose first, then behavioral context, metric list, a limitation note, and an Args section. The metric list is somewhat long but informative. No filler words; each sentence adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return structure is covered elsewhere. The description addresses parameters, live data behavior, metric scope, and a key limitation (no HR sensor). It could mention pagination behavior beyond the limit parameter, but overall it is sufficiently complete for a read-only list tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, but the Args section fully compensates. It explains each parameter's format (e.g., YYYY-MM-DD, YYYY-MM, or '30d'), default behavior, and filtering semantics. This is essential meaning completely absent from the input schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb+resource: 'List e-bike rides with per-ride summary metrics.' This clearly distinguishes from sibling tools like bosch_get_activity_detail by focusing on listing multiple rides with summary metrics rather than detailed individual-ride information.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for listing e-bike rides and gives parameter context, but it never explicitly states when to use this tool versus alternatives. It mentions 'Live read... (no cache)' and HR limitations, but does not name alternative tools or provide when-not-to-use conditions.

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

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