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Cavalry MCP Bridge

Cavalry MCP Bridge

by matthewobanla
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
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cavalry_get_selected_layers

Retrieves the array of IDs for layers currently selected in the Cavalry viewport or scene tree to identify which elements to manipulate next.

Instructions

Returns an array of IDs of the currently selected layers in the Cavalry viewport / scene tree.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "cavalry_get_selected_layers"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.1/5.0
Behavior2/5

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

No annotations are available, so the description carries the full burden of behavioral disclosure. It states it returns an array of IDs, but does not indicate whether it is a read-only operation, what happens when nothing is selected, or any side effects. The simplicity suggests safety, but transparency is insufficient.

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 sentence that is front-loaded with the core action and resource. Every word is necessary; no fluff or repetition. It is optimally concise for the purpose.

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?

Given the lack of annotations and output schema, the description should provide more context about return values (empty vs. multi-selection), side effects, and operational context. It only covers the basic purpose, leaving gaps that could confuse an agent deciding when to invoke this tool.

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

Parameters4/5

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

There are no parameters, so the input schema already covers everything. The description does not need to add parameter meaning, and it does not miss any opportunity. According to guidelines, 0 parameters warrants a baseline of 4.

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 action ('returns an array of IDs') and the resource ('currently selected layers in the Cavalry viewport / scene tree'). It implicitly differentiates from sibling `cavalry_get_comp_layers` by specifying 'selected' layers, but does not explicitly contrast with other getters.

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 guidance is provided on when to use this tool versus alternatives like `cavalry_get_comp_layers` or when not to use it. The description only states what it does, leaving the agent to infer appropriate usage without exclusions or prerequisites.

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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