sylvia-iot-mcp

application_count

Count applications in a unit by providing its ID. Optionally filter by code substring to get a targeted count.

Instructions

Get the count of applications in a unit.

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": "application_count"
  }
}

Input Schema

Name	Required	Description	Default
`unit`	Yes	Unit ID (required for normal users).
`contains`	No	Filter by code substring (case insensitive).

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 6, 2026

TDQS

A3.6/5.0

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 communicates that this is a read-only counting operation, but it does not mention whether the count includes all applications in the unit, whether authorization affects results, how the contains filter interacts with the count, or what happens for unknown units. These details are left entirely to inference.

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 a single, focused sentence with no filler. It front-loads the core operation and resource, making the tool's purpose immediately clear.

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?

For a simple two-parameter count tool with 100% schema coverage, the description plus schema is mostly sufficient. The only notable gap is the absence of any mention of the return shape, but 'count' reasonably implies a numeric result, and no complex output schema exists.

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%, and the schema already documents that unit is the required unit ID and contains is a case-insensitive code substring filter. The description adds no extra parameter semantics beyond 'in a unit', but because the schema is fully self-explanatory, the baseline of 3 is appropriate.

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 the count'), a specific resource ('applications'), and a scoping context ('in a unit'). This clearly distinguishes it from sibling count tools like unit_count or network_count, which target different resources, and from application_list/application_get, which return records rather than counts.

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

Usage Guidelines3/5

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

The purpose of counting is reasonably implied by the tool name and description, so an agent can infer when to use it. However, there is no explicit guidance about when to prefer application_count over application_list or application_stats, nor any mention of when not to use it.

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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