concept-to-video

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Turn any concept into an animated explainer video using Manim (Python). Use whenever the user wants animated visualizations, motion graphics, or video output (MP4/GIF) for technical concepts. Covers: architecture animations, data flow visualizations, algorithm step-throughs, pipeline explainers, math proofs, comparisons, agent interactions, training loops, or any "animate X" / "make a video of X" request. Also trigger for existing Manim scene edits or re-renders. Trigger on: "create a video", "animate this", "make an explainer", "concept to video", "manim animation", "show this as a video", "motion graphic", "visualize this process", or any concept + video/animation output request. Use this skill even for casual "animate" requests about technical ideas.

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Sourcemathews-tom/praxis-skills

Added on2026-02-24

NPX Install

npx skill4agent add mathews-tom/praxis-skills concept-to-video

SKILL.md Content

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Concept to Video

Creates animated explainer videos from concepts using Manim (Python) as a programmatic animation engine.

Reference Files

File	Purpose
`references/scene-patterns.md`	Common scene patterns for different concept types with reusable templates
`scripts/render_video.py`	Wrapper around Manim CLI — handles quality, format, output path cleanup

Why Manim as the engine

Manim is the "SVG of video" — you write Python code that describes animations declaratively, and it renders to MP4/GIF at any resolution. The Python scene file IS the editable intermediate: the user can see the code, request changes ("make the arrows red", "add a third step", "slow down the transition"), and only do a final high-quality render once satisfied. This makes the workflow iterative and controllable, exactly like concept-to-image uses HTML as an intermediate.

Workflow

Concept → Manim scene (.py) → Preview (low-quality) → Iterate → Final render (MP4/GIF)

Interpret the user's concept — determine the best animation approach
Design a self-contained Manim scene file — one file, one Scene class
Preview by rendering at low quality (
```
-ql
```
) for fast iteration
Iterate on the scene based on user feedback
Export final video at high quality using
```
scripts/render_video.py
```

Step 0: Ensure dependencies

Before writing any scene, ensure Manim is installed:

bash

# System deps (usually pre-installed)
apt-get install -y libpango1.0-dev libcairo2-dev ffmpeg 2>/dev/null

# Python package
pip install manim --break-system-packages -q

Verify with:

python3 -c "import manim; print(manim.__version__)"

Step 1: Interpret the concept

Determine the best animation pattern. Read

references/scene-patterns.md

for detailed templates.

User intent	Animation pattern	Key Manim primitives
Explain a pipeline/flow	Sequential flow animation	Arrow, Rectangle, Text, AnimationGroup
Show architecture layers	Layer build-up	VGroup, Arrange, FadeIn with shift
Algorithm step-through	State machine transitions	Transform, ReplacementTransform, Indicate
Compare approaches	Side-by-side morph	Split screen VGroups, simultaneous animations
Data transformation	Object metamorphosis	Transform chains, color transitions
Mathematical concept	Equation + geometric proof	MathTex, geometric shapes, Rotate, Scale
Agent/multi-system interaction	Message passing animation	Arrows between entities, Create/FadeOut
Training/optimization loop	Iterative cycle animation	Loop with Transform, ValueTracker, plots
Timeline/history	Left-to-right progression	NumberLine, sequential Indicate

Step 2: Design the Manim scene

Core rules:

Single file, single Scene class: Everything in one
```
.py
```
file with one
```
class XxxScene(Scene)
```
.
Self-contained: No external assets unless absolutely necessary. Use Manim primitives for everything.
Readable code: The scene file IS the user's artifact. Use clear variable names, comments for each animation beat.
Color with intention: Use Manim's color constants (BLUE, RED, GREEN, YELLOW, etc.) or hex colors. Max 4-5 colors. Every color should encode meaning.
Pacing: Include
```
self.wait()
```
calls between logical sections. 0.5s for breathing room, 1-2s for major transitions.
Text legibility: Use
```
font_size=36
```
minimum for body text,
```
font_size=48+
```
for titles. Test at target resolution.
Scene dimensions: Default Manim canvas is 14.2 × 8 units (16:9). Keep content within ±6 horizontal, ±3.5 vertical.

Animation best practices

python

# DO: Use animation groups for simultaneous effects
self.play(FadeIn(box), Write(label), run_time=1)

# DO: Use .animate syntax for property changes
self.play(box.animate.shift(RIGHT * 2).set_color(GREEN))

# DO: Stagger related elements
self.play(LaggedStart(*[FadeIn(item) for item in items], lag_ratio=0.2))

# DON'T: Add/remove without animation (jarring)
self.add(box)  # Only for setup before first frame

# DON'T: Make animations too fast
self.play(Transform(a, b), run_time=0.3)  # Too fast to read

Structure template

python

from manim import *

class ConceptScene(Scene):
    def construct(self):
        # === Section 1: Title / Setup ===
        title = Text("Concept Name", font_size=56, weight=BOLD)
        self.play(Write(title))
        self.wait(1)
        self.play(FadeOut(title))

        # === Section 2: Core animation ===
        # ... main content here ...

        # === Section 3: Summary / Conclusion ===
        # ... wrap-up animation ...
        self.wait(2)

Step 3: Preview render

Use low quality for fast iteration:

bash

python3 scripts/render_video.py scene.py ConceptScene --quality low --format mp4

This renders at 480p/15fps — fast enough for previewing timing and layout. Present the video to the user.

Step 4: Iterate

Common refinement requests and how to handle them:

Request	Action
"Slower/faster"	Adjust `run_time=` params and `self.wait()` durations
"Change colors"	Update color constants
"Add a step"	Insert new animation block between sections
"Reorder"	Move code blocks around
"Different layout"	Adjust `.shift()` , `.next_to()` , `.arrange()` calls
"Add labels/annotations"	Add `Text` or `MathTex` objects with `.next_to()`
"Make it loop"	Add matching intro/outro states

Step 5: Final export

Once the user is satisfied:

bash

python3 scripts/render_video.py scene.py ConceptScene --quality high --format mp4

Quality presets

Preset	Resolution	FPS	Flag	Use case
`low`	480p	15	`-ql`	Fast preview
`medium`	720p	30	`-qm`	Draft review
`high`	1080p	60	`-qh`	Final delivery
`4k`	2160p	60	`-qk`	Presentation quality

Format options

Format	Flag	Use case
`mp4`	`--format mp4`	Standard video delivery
`gif`	`--format gif`	Embeddable in docs, social
`webm`	`--format webm`	Web-optimized

Delivering the output

Present both:

The
```
.py
```
scene file (for future editing)
The rendered video file (final output)

Copy the final video to

/mnt/user-data/outputs/

and present it.

Error Handling

Error	Cause	Resolution
`ModuleNotFoundError: manim`	Manim not installed	Run Step 0 setup commands
`pangocairo` build error	Missing system dev headers	`apt-get install -y libpango1.0-dev`
`FileNotFoundError: ffmpeg`	ffmpeg not installed	`apt-get install -y ffmpeg`
Scene class not found	Class name mismatch	Verify class name matches CLI argument
Overlapping objects	Positions not calculated	Use `.next_to()` , `.arrange()` , explicit `.shift()` calls
Text cut off	Text too large or positioned near edge	Reduce `font_size` or adjust position within ±6,±3.5
Slow render	Too many objects or complex transformations	Reduce object count, simplify paths, use lower quality
`LaTeX Error`	LaTeX not installed (for MathTex)	Use `Text` instead, or install `texlive-latex-base`

LaTeX fallback

If LaTeX is not available, avoid

MathTex

and

Tex

. Use

Text

with Unicode math symbols instead:

python

# Instead of: MathTex(r"\frac{1}{n} \sum_{i=1}^{n} x_i")
# Use:        Text("(1/n) Σ xᵢ", font_size=36)

Limitations

Manim + ffmpeg required — cannot render without these dependencies.
No audio support in this workflow — Manim supports audio but adds complexity. Keep videos silent or add audio post-export.
LaTeX optional — MathTex requires a LaTeX installation. Fall back to Text with Unicode for math.
Render time scales with complexity — a 30-second 1080p scene with many objects can take 1-2 minutes to render.
3D scenes require OpenGL — ThreeDScene may not work in headless containers. Stick to 2D Scene class.
No interactivity — output is a static video file, not an interactive widget.

Design anti-patterns to avoid

Walls of text on screen — keep to 3-5 words per label, max 2 lines
Everything appearing at once — use staged animations with LaggedStart
Uniform timing — vary run_time to create rhythm (fast for simple, slow for important)
No visual hierarchy — use size, color, and position to guide attention
Rainbow colors — 3-4 intentional colors max
Ignoring the grid — align objects to consistent positions using arrange/align

concept-to-video

NPX Install

Tags

SKILL.md Content

Concept to Video

Reference Files

Why Manim as the engine

Workflow

Step 0: Ensure dependencies

Step 1: Interpret the concept

Step 2: Design the Manim scene

Animation best practices

Structure template

Step 3: Preview render

Step 4: Iterate

Step 5: Final export

Quality presets

Format options

Delivering the output

Error Handling

LaTeX fallback

Limitations

Design anti-patterns to avoid