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 skills add shubham0704/claude-skills --skill animating-computational-mechanicsgit clone --depth 1 https://github.com/shubham0704/claude-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/shubham0704/claude-skills/animating-computational-mechanics)<a href="https://agentmods.dev/skills/shubham0704/claude-skills/animating-computational-mechanics"><img src="https://agentmods.dev/badge/skills/shubham0704/claude-skills/animating-computational-mechanics/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/shubham0704/claude-skills/animating-computational-mechanics"><img src="https://agentmods.dev/badge/skills/shubham0704/claude-skills/animating-computational-mechanics.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What 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 5.1 | $0.00185 | $0.03379 |
| Opus 5 | $0.00093 | $0.01690 |
| Sonnet 5 | $0.00037 | $0.00676 |
| Haiku 4.5 | $0.00018 | $0.00338 |
Grade A, and why
animating-computational-mechanics 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 12d ago.
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 — 199 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Animating Computational Mechanics
You help the user produce pedagogical animations of computational mechanics — continuum kinematics, tensor calculus, and the finite element method — using one of three open-source toolchains: Matplotlib, Manim, or Blender. The recipes here are distilled from Flaschel, How to Visualize Computational Mechanics: Animating Finite Elements, Continuum Mechanics, and Tensor Calculus (Comp. Applic. in Engineering Education, 2026; open access; gallery at https://github.com/DrSimulate/gallery).
The skill is a decision tree (which tool?) plus a recipe book (concrete code for each canonical didactic pattern), not a generic "make me an animation" wand. Always pick the recipe that matches the mathematical object the user is trying to convey, not the visual style they ask for first.
1. When to use
Invoke when the user:
- Says "animate F", "show the deformation gradient acting on a unit circle", "rotate the stress tensor", "morph the reference into the deformed configuration".
- Wants to teach the weak form, mesh convergence, or discretization by moving test functions / shape functions / element counts.
- Has FEM results from ParaView and wants a photoreal Blender render (the Stop-motion-OBJ pipeline; see
PIPELINE.md). - References Flaschel 2026, the DrSimulate YouTube channel, or asks "how would Flaschel show this?".
- Has a static figure in a paper/lecture that visibly fails to convey time evolution or deformation.
Do not invoke for static figure cleanup (tikz-figure-review), for adding still visualizations to lecture notes (enhancing-latex-lectures), or for non-mechanics animations.
2. Tool selection
The three tools are not interchangeable. Pick the one whose primitive matches the mathematics:
| Tool | Native primitive | Use when | Cost |
|---|---|---|---|
Matplotlib (FuncAnimation) |
per-frame replot of a 2D/3D scene | Vector fields on a sphere or cube, line plots that evolve, simple 3D scenes with vectors, anything where the data is already in NumPy arrays. | Fastest to write. Renders to MP4/GIF. No surface shading. |
Manim (Scene + ValueTracker / Transform / apply_function) |
parameter-driven smooth tweening | Geometric morphing (reference → deformed config), continuous variation of a tensor's components, equation algebra animations, anything where smooth interpolation is the message. | Steeper. Renders MP4. Built for math exposition (LaTeX-native, smooth tweens). |
Blender (bpy Python API + Stop-motion-OBJ add-on) |
per-vertex mesh deformation with surface shading | Photoreal renders for the hero figure of a paper, importing real FEM simulation results, anything where surface texture / lighting carries pedagogical weight. | Highest setup cost. Best output. Requires Blender 4.5 + Stop-motion-OBJ. |
What ships with it
6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 12d ago First seen · 199 lines · 185 tokens per session scan A 9607e40a8d82
animating-computational-mechanics is a skill published in the GitHub repository shubham0704/claude-skills (1 stars, last pushed 7d ago), licensed MIT. It adds 185 tokens to every session and 3,379 once invoked, about $0.0009 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.
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