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bosch_sync

Fetch and cache Bosch eBike data (bikes, batteries, components, service, updates) into SQLite. Run before using other tools to populate or refresh cached data.

Instructions

Sync Bosch eBike data to the local cache.

Fetches data from Bosch and stores it in SQLite. The source depends on your sign-in: a standard Bosch eBike Flow account uses the mobile app API; an EU Data Act (euda) client uses the Data Act API. Run this to populate the cache before using other bosch_get_* tools, or to refresh after a ride or charge cycle.

Bikes are identified automatically from your Bosch Flow account. Battery snapshots build a time series for health trend analysis.

Service records, software-update history and capacity-tester data are only available with a euda (EU Data Act) client; with a standard sign-in they report status "unavailable" rather than an empty result.

Args: data_types: What to sync. Options: "all", "bikes", "batteries", "components", "service", "software_updates", "capacity". Comma-separated for multiple, e.g. "bikes,batteries". Default: "all".

Returns a per-type summary: status (ok/empty/unavailable/error), record count, and a message explaining any non-ok result.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
data_typesNoall

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

No annotations provided, but description fully discloses behavior: fetches data from Bosch, stores in SQLite, sources depend on sign-in, and that some data types are only available with euda client. Also describes return format.

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?

Well-structured with paragraphs and clear sections, though the 'Args' section partly repeats some info. Still concise and front-loaded with purpose.

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

Completeness5/5

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

Given the complexity (sign-in types, data sources, availability differences), the description covers all essential context. Output schema exists but description still explains return format.

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?

Only parameter data_types has 0% schema coverage, but description adds full meaning: lists options (all, bikes, batteries, etc.), explains comma-separated, and notes default 'all'.

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 starts with 'Sync Bosch eBike data to the local cache,' which clearly states the verb and resource. It distinguishes from sibling tools (bosch_get_*) by explaining it populates the cache they read from.

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

Usage Guidelines5/5

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

Explicit guidance: 'Run this to populate the cache before using other bosch_get_* tools, or to refresh after a ride or charge cycle.' Also explains data availability differences based on sign-in type.

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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