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Create growth system

create_growth_system

Build a procedural vine/tree generator in TouchDesigner with L-system rewriting, 3D turtle drawing, and stochastic rule selection. Returns container path, preview, and adjustable parameters.

Instructions

Build an L-system / vine-growth generator: a Script SOP iterates a context-free rewriting grammar from axiom for generations steps, then walks the resulting string as a 3D turtle to draw a polyline tree. Recognised symbols: F (forward draw), f (forward no draw), + - (yaw ± branchAngle), & ^ (pitch), \ / (roll), [ ] (push/pop state). Other symbols are no-op constants (use X/A/B as grammar variables that expand but don't draw). Multiple rules sharing a from symbol trigger weighted-random stochastic selection (weight defaults to 1; seed controls the RNG). The polyline tree is thickened with a Tube SOP, recentred, and rendered. Complements create_particle_flock (boids) and create_gpu_particle_field (curl-noise) as the deterministic CPU-geometry idiom. Returns a summary plus a JSON block with the container path, output path, rules DAT path, exposed controls, errors, warnings, and an inline preview.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoContainer baseCOMP name.growth_system
seedNoRNG seed for stochastic rule selection.
axiomNoInitial string before rewriting.F
colorNoConstant MAT colour (RGB, 0..1).
rulesNoContext-free rewriting rules. Multiple rules sharing the same `from` symbol trigger weighted-random stochastic choice (weight defaults to 1).
parentNoParent network where the container is created./project1
thicknessNoTube SOP radius for the rendered branches.
branchAngleNoTurtle turn angle (degrees) for + / - / & / ^ / \ / / symbols.
generationsNoRewrite iterations. Capped at 7 because string length grows ~k^n and freezes the SOP cook.
step_lengthNoWorld units per F stroke.
expose_controlsNoExpose Generations / BranchAngle / StepLength / Thickness on the container.
Behavior5/5

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

Beyond the annotations (readOnlyHint=false, openWorldHint=true), the description discloses the full algorithmic behavior, the stochastic rule selection via seed, the rendering pipeline (Tube SOP, recentre), and the exact return JSON structure with paths and preview. No contradiction with annotations.

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 dense yet well-structured: first sentence states purpose, second explains the algorithm, third positions it among siblings, and fourth describes the return value. Every sentence earns its place with no fluff.

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

Completeness5/5

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

For a tool with 11 parameters and no output schema, the description is exceptionally complete: it covers the algorithm, grammar semantics, stochastic behavior, geometry pipeline, return format, and sibling differentiation. The schema handles per-parameter details, so the description focuses on integral context.

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?

Schema coverage is 100%, but the description adds meaningful context beyond the schema: it explains the turtle symbols (F, f, +, -, etc.), clarifies that X/A/B are non-drawing grammar variables, and notes that multiple rules with the same `from` trigger weighted-random selection. This enriches the parameter understanding.

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 explicitly states it builds an L-system / vine-growth generator, details the construction process (Script SOP, turtle interpretation, Tube SOP), and names sibling tools (create_particle_flock, create_gpu_particle_field) to distinguish it as the deterministic CPU-geometry idiom.

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

Usage Guidelines5/5

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

It explicitly names alternatives and provides a clear usage context: 'Complements create_particle_flock (boids) and create_gpu_particle_field (curl-noise) as the deterministic CPU-geometry idiom.' This tells the agent when to choose this tool over particle-based generators.

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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