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fitbit_get_weight

Get weight, BMI, and body fat percentage from Fitbit weight log. Choose date range and whether to use cached or live data.

Instructions

Get weight log entries (weight, BMI, body fat percentage).

Returns data from the local cache by default. Use live=True to fetch from Fitbit API. Run fitbit_sync first to populate the cache.

Weight data is sparse: only days with weigh-in entries are present.

Args: start_date: Start date as "YYYY-MM-DD", "YYYY-MM", or "30d". Default: last 30 days. end_date: End date as "YYYY-MM-DD". Default: today. live: If true, fetch directly from Fitbit API instead of cache.

Returns one entry per weigh-in with weight_kg, bmi, fat_pct.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
start_dateNo
end_dateNo
liveNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses caching behavior, sparsity ('only days with weigh-in entries are present'), and parameter defaults. Some additional behavioral details (e.g., error handling) could be added, but the core is well-covered.

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

Conciseness5/5

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

The description is concise, uses clear bullet points for args and returns, and every sentence adds value. It is front-loaded with the purpose and caveats.

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 tool's simplicity, the description covers purpose, usage, parameters, behavioral nuances, and return format completely. It leaves no important gaps.

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

Parameters4/5

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

Schema description coverage is 0%, but the description compensates by explaining all three parameters: start_date format and default, end_date format, and the live boolean meaning. This adds significant value beyond the bare 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 clearly states 'Get weight log entries (weight, BMI, body fat percentage).' This provides a specific verb and resource, distinguishing it from sibling tools like fitbit_get_activity and fitbit_get_sleep.

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

Usage Guidelines4/5

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

The description explains default cache usage and the option to fetch live data, and mentions the prerequisite 'Run fitbit_sync first.' It lacks explicit when-not-to-use guidance, but the context of sibling tools makes the purpose clear.

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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