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 commands/choxos/mathvizagent/create-scenegit clone --depth 1 https://github.com/choxos/MathVizAgentWhat 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 | $0.00012 | $0.00979 |
| Opus 5 | $0.00006 | $0.00490 |
| Sonnet 5 | $0.00002 | $0.00196 |
| Haiku 4.5 | $0.00001 | $0.00098 |
Grade A, and why
create-scene 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 yesterday.
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 — 158 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/create-scene - Single Scene Creation Workflow
Create a production-quality animated scene for a single mathematical concept.
Workflow Steps
Step 1: Requirements Gathering (@viz-architect)
Gather the following information from the user:
- Topic: What mathematical concept to visualize?
- Duration: Target scene duration (30s / 60s / 90s)
- Complexity: Simple / Moderate / Complex
- Features needed:
- Mathematical formulas? (y/n)
- Camera movements? (y/n)
- Data visualization? (y/n)
- Custom components? (y/n)
Step 2: Scene Design (@scene-designer)
Create a detailed scene plan:
## Scene: [Concept Name]
**Duration**: X seconds
**Concept**: One-sentence description
### Timeline
| Time | Element | Animation | Wait |
|------|---------|-----------|------|
| 0-5s | Title | GrowFromCenter | 0.5s |
| ... | ... | ... | ... |
### Key Moments
- [timestamp] Critical insight
- [timestamp] Transition point
### Technical Requirements
- Camera: [static / zoom / pan]
- Colors: [list semantic colors]
- Formulas: [list any MathTex needed]
- Components: [list any custom VGroups]
Step 3: Formula Preparation (@math-renderer)
If mathematical formulas are needed:
- Write MathTex code for each formula
- Identify parts for coloring/animation
- Create custom MathTex subclasses if complex
- Document index maps for animation
Step 4: Camera Planning (@camera-specialist)
If camera work is needed:
- Specify scene type (MovingCameraScene, ThreeDScene)
- Plan camera moments with timestamps
- Determine if line width management needed
- Set timing for camera movements
Step 5: Code Generation (@animation-specialist)
Generate the complete scene code:
from manim import *
# Configuration
COLORS = {
"PRIMARY": BLUE,
"SECONDARY": ORANGE,
"POSITIVE": GREEN,
"EMPHASIS": PURPLE,
"MUTED": GRAY,
}
TIMING = {
"FAST": 0.5,
"NORMAL": 1.0,
"SLOW": 2.0,
"COMPLEX": 4.0,
}
class [SceneName](Scene): # or MovingCameraScene
def construct(self):
# Section 1: Introduction
self.next_section("Introduction")
# ... code
# Section 2: Main Visualization
self.next_section("Main Content")
# ... code
# Section 3: Conclusion
self.next_section("Conclusion")
# ... code
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.
- yesterday First seen · 158 lines · 12 tokens per session scan A 8295d7f9ddb9
create-scene is a command published in the GitHub repository choxos/MathVizAgent (1 stars, last pushed 3mo ago), licensed MIT. It adds 12 tokens to every session and 979 once invoked, about $0.0001 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 2026-08-31.
Other commands, from other repositories
stt
Transcribe a local audio file or remote audio URL into text.
audition-voices
Generate voice audition samples for a character using Venice TTS.
status
Show 3d-design team status and recent activity.
music-suno-prompt
Grounded Suno prompt synthesis from local knowledge corpus + persona canon + label canon. No vibes-prompting.
develop-image-prompt.eval
Generates a detailed image generation prompt from a document or content description. Good output: a prompt that is specific, visual, non-abstract, includes style/composition/lighting guidance, and is calibrated to the specified dimensions and style options.
speckit.tasks
Generate an actionable, dependency-ordered tasks.md for the feature based on available design artifacts.