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Get Experimental Techniques

get_experimental_techniques

Browse TouchDesigner experimental techniques by category to get code snippets, operator chains, and setup notes for GLSL, GPU compute, machine learning, generative systems, audio-visual, networking, and Python advanced.

Instructions

Browse TouchDesigner experimental techniques by category. Categories: glsl, gpu-compute, machine-learning, generative-systems, audio-visual, networking, python-advanced. Returns technique descriptions, code snippets, operator chains, and setup notes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
categoryYesTechnique category to browse. Options: glsl, gpu-compute, machine-learning, generative-systems, audio-visual, networking, python-advanced. Aliases: shader/raymarching/sdf=glsl, gpu/cuda=gpu-compute, ml/ai=machine-learning, generative/lsystem=generative-systems, audio/fft=audio-visual, network/osc/ndi=networking, python/numpy/opencv=python-advanced
show_codeNoInclude GLSL/Python code snippets in output (default: true)
show_setupNoInclude operator setup details (default: true)
technique_idNoOptional specific technique ID to fetch (e.g. 'raymarching_basic', 'reaction_diffusion_gs'). If omitted, returns all techniques in the category.
Behavior3/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It implies a read-only operation ('browse') and describes the output, but does not explicitly state whether it is side-effect-free, idempotent, or what permissions are needed. This is adequate but not thorough.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise at two sentences, front-loading the purpose. However, it could be slightly more structured (e.g., listing parameters or expected behavior), but it remains efficient and clear.

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

Completeness4/5

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

For a browsing tool with no output schema, the description adequately explains what is returned (descriptions, code snippets, operator chains, setup notes) and lists all categories. It covers the essential information needed for an agent to use the tool effectively.

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 description coverage is 100%, so baseline is 3. The description does not add significant meaning beyond the schema; the schema already lists categories and aliases in the parameter description. The tool description merely repeats a subset, so no extra value.

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 'browse' and the resource 'experimental techniques', with a defined scope of 'by category'. It lists the specific categories and the types of data returned (descriptions, code snippets, operator chains, setup notes). This distinguishes it from sibling tools like get_glsl_pattern or get_experimental_build, which target different resources.

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

Usage Guidelines3/5

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

The description implies usage context by naming categories and return types, but lacks explicit guidance on when to use this tool versus alternatives (e.g., get_experimental_build for builds, get_glsl_pattern for patterns). No when-not-to-use or exclusion criteria are provided.

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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