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SORACOM Data Reader MCP

by leaveanest

get_harvest_data_by_resource

Retrieve Harvest sensor data for specific IoT resources by type and ID within defined time ranges using the SORACOM Data Reader MCP server.

Instructions

リソースタイプとIDでHarvest Dataを取得します

Args: resource_type: リソースタイプ(subscriber, device など) resource_id: リソースID from_time: 取得開始時刻(UNIXタイムスタンプ・ミリ秒) to_time: 取得終了時刻(UNIXタイムスタンプ・ミリ秒) sort: ソート順(asc: 古い順, desc: 新しい順) limit: 取得件数(最大1000) last_evaluated_key: ページング用キー

Returns: Harvest Dataのリストと次ページのキー

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
resource_typeYes
resource_idYes
from_timeNo
to_timeNo
sortNodesc
limitNo
last_evaluated_keyNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

With no annotations provided, the description carries the full burden. It mentions pagination behavior ('ページング用キー') and a maximum limit constraint ('最大1000'), which are useful behavioral details. However, it doesn't cover important aspects like authentication requirements, rate limits, error conditions, or whether this is a read-only operation.

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 with clear sections (Args, Returns) and front-loaded the core purpose. Every sentence adds value, though the Japanese-only presentation might be less accessible in multilingual contexts. The structure is efficient with no wasted text.

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?

Given the complexity (7 parameters, pagination, time-based filtering) and the presence of an output schema (which handles return values), the description is quite complete. It explains all parameters thoroughly and mentions the pagination behavior. The main gap is lack of sibling tool differentiation and some behavioral context like authentication.

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?

With 0% schema description coverage and 7 parameters, the description provides excellent parameter semantics. It clearly explains each parameter's purpose, format constraints (UNIX timestamp in milliseconds), enum values for 'sort', maximum limit, and the pagination mechanism. This fully compensates for the lack of schema descriptions.

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?

The description clearly states the tool's purpose: 'リソースタイプとIDでHarvest Dataを取得します' (Get Harvest Data by resource type and ID). It specifies the verb '取得します' (get/retrieve) and the resource 'Harvest Data', but doesn't explicitly differentiate from sibling tools like 'get_harvest_data' which likely has a different filtering approach.

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?

The description provides no guidance on when to use this tool versus alternatives. With sibling tools like 'get_harvest_data', 'get_harvest_file_download_url', 'get_harvest_file_info', and 'list_harvest_files', there's no indication of when this resource-based retrieval is preferred over other methods.

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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