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query_metric_series

Retrieve steps, distance, calories, and weight time series from local Xiaomi Mi Fitness data. Specify date range, aggregation, and granularity to analyze personal health trends.

Instructions

Query metric series

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
metricYes
end_dateYes
start_dateYes
aggregationNo
granularityNo
Behavior1/5

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

No annotations are provided, and the description contains no behavioral details. There is no mention of read-only behavior, side effects, pagination, response format, or any constraints. The description carries the full burden for transparency and completely fails to disclose any behavioral traits beyond the act of querying.

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

Conciseness2/5

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

The description is only three words, which is extremely concise, but the brevity is a symptom of under-specification rather than efficiency. It does not earn its place since it merely parrots the tool name without contributing semantic value. A concise description should still convey purpose and context.

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

Completeness1/5

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

This tool has 5 parameters, 3 enums, no output schema, and no annotations. The description only says 'Query metric series', which is far from sufficient. It does not explain what a metric series is, how to specify it, what the returned data looks like, or any constraints. Essential context for successful invocation is entirely missing.

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

Parameters1/5

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

Schema description coverage is 0%, meaning the schema itself provides no explanations for parameters. The description adds zero information about metric, date ranges, aggregation, or granularity. It does not help the agent understand parameter purposes or relationships, such as how start_date and end_date define the series interval.

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

Purpose2/5

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

The description 'Query metric series' directly restates the tool name (query_metric_series) without adding specificity. It identifies the verb and general resource but fails to indicate which metrics are involved, how the series is defined, or how it differs from sibling query tools like query_heart_rate or query_sleep. This is tautological and uninformative.

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

Usage Guidelines1/5

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

There is no guidance on when to use this tool versus alternatives. The sibling tools include many query_* variants, yet the description provides no context, use cases, or exclusions. An agent is left to guess which tool fits a given metric query.

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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