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matthewobanla

Cavalry MCP Bridge

cavalry_eval_expression

Evaluate a JavaScript expression within Cavalry to retrieve scene data or trigger internal functions, enabling direct inspection of compositions and properties.

Instructions

Evaluates a single JavaScript expression inside Cavalry and returns its value.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
expressionYesJavaScript expression to evaluate (e.g. `api.getCompLayers(false)` or `api.get('basicShape#1', 'position.x')`).
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states that it evaluates an expression and returns its value, but it does not disclose potential side effects, whether the evaluation is read-only, or if the expression can modify state. Given that evaluating arbitrary JavaScript could have side effects, this lack of transparency is a significant gap.

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, front-loaded sentence that efficiently conveys the core purpose. There is no unnecessary verbosity or repetition. Every word contributes to clarity, making it optimally concise.

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

Completeness3/5

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

Given the simplicity of the tool (one param, no output schema) and lack of annotations, the description is adequate but not thorough. It mentions that it returns a value but does not specify the nature of that value (e.g., types, serialization) or note that evaluation occurs within a specific Cavalry context. It could be more explicit about side effects or limitations, but for a basic evaluation tool, it is reasonably complete.

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 fully describes the single parameter 'expression' with a clear description and examples. The tool description adds no extra detail about the parameter beyond what the schema already provides. Since schema coverage is 100%, the baseline of 3 applies, and the description does not meaningfully enhance the parameter semantics.

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 tool's function: evaluating a single JavaScript expression inside Cavalry and returning its value. The verb 'Evaluates' is specific, the resource is well-defined, and it distinguishes from siblings like cavalry_run_script which runs scripts or cavalry_get_comp_layers which retrieves layers.

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 gives no explicit guidance on when to use this tool versus alternatives. It doesn't mention scenarios where running a full script via cavalry_run_script would be more appropriate, nor does it provide any exclusions or prerequisites. The usage context is only implied by the word 'single' versus a script.

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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