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by bubiji
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query_samples

Retrieve Apple HealthKit records by type and date range, with optional daily aggregation or raw output, to build reports and analyze health trends.

Instructions

读 HealthKit 样本。type 可写全名或简写(bodyMass/bodyFatPercentage/stepCount/heartRate…);agg=daily 按天聚合。

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "type": "<type>"
    },
    "name": "query_samples"
  }
}

Input Schema

NameRequiredDescriptionDefault
aggNo
endNo止(不含):YYYY-MM-DD(UTC 0 点)或带时区 ISO8601
typeYes
limitNo
startNo起(含):YYYY-MM-DD(UTC 0 点)或带时区 ISO8601

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.2

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden. '读' implies a read-only operation, but it omits HealthKit authorization requirements, pagination behavior implied by the limit parameter, and return format. Substantial gaps for a data-access tool.

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?

Compact two-clause structure with the core purpose front-loaded, followed by parameter hints. Both sentences earn their place, with only the trailing ellipsis example list slightly loose.

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

Completeness3/5

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

For a 5-parameter tool with no annotations and no output schema, the description covers type and agg but leaves limit and the shape of the returned samples unexplained. It is minimally adequate but not complete enough for an agent to call it with full confidence.

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

Parameters3/5

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

Schema coverage is only 40%, so the description must compensate: it usefully clarifies that type accepts full names or abbreviations with concrete examples (bodyMass, stepCount, heartRate) and explains that agg=daily aggregates by day, adding meaning beyond the bare enum. However, limit remains undocumented in both schema and description, so compensation is incomplete.

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

Purpose4/5

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

States a specific verb and resource ('读 HealthKit 样本' = read HealthKit samples), which is clearly distinct from the write-oriented siblings log_workout, log_meal, and sync_status. However, it never names an alternative or scoping condition to differentiate itself from other read tools like weekly_report.

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

Usage Guidelines2/5

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

There is no explicit when-to-use or when-not-to-use guidance. The note that agg=daily aggregates by day hints at a usage mode but stops short of telling the agent when to pick daily vs raw, or when to prefer this tool over siblings.

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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