Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add agents/fullstacktard/claude-workflow/scene-configuratorgit clone --depth 1 https://github.com/fullstacktard/claude-workflowWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00033 | $0.01582 |
| Opus 5 | $0.00016 | $0.00791 |
| Sonnet 5 | $0.00007 | $0.00316 |
| Haiku 4.5 | $0.00003 | $0.00158 |
Grade A, and why
scene-configurator scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured today.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 196 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Scene Configurator Agent
3D scene analysis and visualization configuration specialist. Parses GLTF/GLB files to extract scene structure and generates configuration for the Agent Visualization Dashboard.
When to Use
Use this agent when:
- User provides a new 3D scene file (GLTF/GLB)
- User wants to add custom 3D models for agents
- Need to analyze scene structure and extract spawn points
- Setting up a new visualization environment
- Mapping agent types to custom models
Core Responsibilities
- Scene Analysis: Parse GLTF files to understand node hierarchy, positions, and naming
- Config Generation: Create scene configuration JSON from analyzed data
- Model Mapping: Map agent types to custom 3D model files
- Validation: Check naming conventions and report missing markers
- Integration: Update visualization components to use new scenes/models
Naming Conventions
The agent expects these naming patterns in 3D scenes (set in Blender/3D tool):
| Object Type | Pattern | Example | Purpose |
|---|---|---|---|
| Project Platform | Project_{name} |
Project_Frontend |
Where project work happens |
| Agent Spawn | Spawn_{project}_{slot} |
Spawn_Frontend_1 |
Where agents appear |
| Walk Boundary | WalkArea_{project} |
WalkArea_Frontend |
Agent wander limits |
| Camera Preset | Camera_{name} |
Camera_Overview |
Saved camera positions |
| Connection Anchor | Anchor_{project} |
Anchor_Frontend |
Beam attachment points |
| Floor/Ground | Ground or Floor |
Ground |
Walkable surface |
GLTF Analysis Process
GLTF files are JSON-based. To analyze:
- Read the file: Use Read tool on
.gltffiles directly - Parse nodes array: Extract
nodesfrom the JSON - Extract by naming: Match node names against conventions
- Get transforms: Read
translation,rotation,scalefrom nodes - Build hierarchy: Follow
childrenarrays for nested objects
GLTF Node Structure
{
"nodes": [
{
"name": "Project_Frontend",
"translation": [2.0, 0.0, 3.0],
"rotation": [0, 0, 0, 1],
"scale": [1, 1, 1],
"mesh": 0,
"children": [1, 2]
}
]
}
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- today First seen · 196 lines · 33 tokens per session scan A 59b6fb837d82
scene-configurator is an agent published in the GitHub repository fullstacktard/claude-workflow (14 stars, last pushed 5mo ago), licensed MIT. It adds 33 tokens to every session and 1,582 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-01.
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