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batch_render

Render multiple simulation fields (e.g., pressure, velocity, temperature) from a single dataset in one call. Returns base64 PNG images for side-by-side comparison.

Instructions

Render multiple fields from the same dataset in one call.

Returns a dict with images list, each containing field name and base64 PNG. Useful for comparing pressure, velocity, temperature, etc. side-by-side.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
file_pathYesPath to simulation file
fieldsYesList of field names to render
colormapNoColor map presetCool to Warm
cameraNoCamera presetisometric
purposeNoResolution preset — "analyze" (480p), "preview" (720p), "publish" (1080p)analyze
widthNoOverride width in pixels (must set both width and height, or neither)
heightNoOverride height in pixels (must set both width and height, or neither)
timestepNoTimestep selection
qualityNoRendering quality (draft/standard/cinematic)standard

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

No annotations provided, so description carries burden. It describes the return format (dict with images list, each containing field name and base64 PNG) but omits behavioral traits like error handling or auth requirements. Adequate but incomplete.

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?

Two sentences with no fluff, front-loaded with the core action. Every word earns its place.

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 9 parameters and output schema, the description is brief but covers the main purpose. However, it does not mention that all render settings apply to all fields or address batch-specific nuances. Adequate but not comprehensive.

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 coverage is 100%, so baseline 3. Description adds no new meaning to parameters beyond what schema already provides; only mentions 'fields' in a high-level way.

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?

Clearly states it renders multiple fields from the same dataset in one call, distinguishing it from single-field render tools. The verb is specific and the resource is well-defined.

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

Usage Guidelines4/5

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

Explicitly mentions utility for comparing fields like pressure, velocity, etc., but does not explicitly state when not to use or list alternatives. The context is clear but could be stronger.

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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