sylvia-iot-mcp

data_network_dldata_count

Count network downlink data records, using optional filters for address, device, network, profile, and time range.

Instructions

Get the count of network downlink data records.

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": {
      "unit": "<unit>"
    },
    "name": "data_network_dldata_count"
  }
}

Input Schema

Name	Required	Description
`addr`	No	Filter by network address.
`tend`	No	End time in milliseconds since epoch.
`unit`	Yes	Unit ID (required for normal users).
`device`	No	Filter by device ID.
`tfield`	No	Time field for filtering: proc, pub, or resp. Required when using tstart/tend.
`tstart`	No	Start time in milliseconds since epoch.
`network`	No	Filter by network code.
`profile`	No	Filter by device profile.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 6, 2026

TDQS

B3.1/5.0

Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only says 'Get the count,' which implies a read operation returning a number, but it does not describe filtering semantics, default scope, time-window requirements, response shape, or any side-effect safety details.

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 a single sentence with no filler or redundancy. It is concise and front-loaded with the core action and resource, though it could have provided a bit more structure without much added length.

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

Completeness2/5

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

This is an 8-parameter filtering tool with no annotations and no output schema, yet the description only states the basic count operation. It omits how filters interact, whether time bounds require tfield, what the default count scope is, and what the response looks like, so an agent cannot fully infer correct invocation.

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 description coverage is 100%, so the baseline is 3 even though the description itself adds no parameter-level meaning. The description does not explain how filters combine or that tfield is required with tstart/tend, but the schema already documents these fields adequately.

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 states a specific verb ('Get') and resource ('count of network downlink data records'), making the operation immediately understandable. It also distinguishes this tool from sibling list and uplink variants such as data_network_dldata_list and data_network_uldata_count.

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?

No explicit guidance is given for when to use this tool instead of alternatives like data_network_dldata_list or data_application_dldata_count. The word 'count' implies a total rather than a list, but there is no direct comparison, prerequisite, or use-case context.

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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