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Cavalry MCP Bridge

Cavalry MCP Bridge

by matthewobanla
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cavalry_get_comp_layers

Retrieve an array of layer and node IDs from the active composition, with an option to return only root-level layers.

Instructions

Returns an array of layer and node IDs present in the active composition.

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_comp_layers"
  }
}

Input Schema

NameRequiredDescriptionDefault
topLevelOnlyNoIf true, only returns root-level layers. Defaults to false.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.2/5.0
Behavior2/5

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

The description only states the return type without disclosing behavioral traits. Since no annotations are provided, the description carries full burden. It does not mention that the operation is read-only, any dependencies on composition state, or potential side effects. The agent lacks information about performance or error conditions.

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 wasted words. It is front-loaded with the key action and result, achieving maximum conciseness.

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 absence of an output schema, the description should explain the structure of the returned array (e.g., string IDs or objects). It also lacks context about the 'active composition' concept and error handling. For a simple tool with one parameter, the description is insufficient for an agent to fully understand the tool's behavior.

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?

The input schema has 100% description coverage, with a clear explanation for the single parameter 'topLevelOnly'. The tool description adds no additional meaning beyond the schema, so the baseline score 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 clearly states the verb 'Returns' and the resource 'array of layer and node IDs present in the active composition'. It distinguishes this tool from siblings like 'cavalry_get_selected_layers' (selected layers) and 'cavalry_get_scene_info' (scene info), providing a specific scope.

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 such as 'cavalry_get_selected_layers' or 'cavalry_get_scene_info'. There is no mention of filter conditions, prerequisites, or when the 'topLevelOnly' parameter is appropriate.

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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