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manim-dsa-explainer

manim-dsa-explainer is a skill for Claude Code, Codex from dbillion/manim-storytelling-skills. It costs 135 tokens per session (2,749 once invoked), scanned A, original, MIT.

Instructions for making Manim videos that explain data-structures and algorithms. Manim is a programming tool for creating animated mathematical and technical scenes.

In plain words
What is it for?
Use it to create narrated visual explanations of sorting, searching, traversals, dynamic programming, data structures, and similar algorithm topics.
Why use it?
It provides a defined story structure for showing how an algorithm works, including when to compare a slow method with a faster one and how to end with a test check.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

not rated 3repo 3mo ago A scan 135 tokens original MIT

Good fit Use it to create narrated visual explanations of sorting, searching, traversals, dynamic programming, data structures, and similar algorithm topics.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/dbillion/manim-storytelling-skills/manim-dsa-explainer
View source ↗ dbillion/manim-storytelling-skills
Install

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.

Any agent
npx skills add dbillion/manim-storytelling-skills --skill manim-dsa-explainer
Clone the repo
git clone --depth 1 https://github.com/dbillion/manim-storytelling-skills

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for manim-dsa-explainer

README.md
[![agentmods](https://agentmods.dev/badge/skills/dbillion/manim-storytelling-skills/manim-dsa-explainer/github.svg)](https://agentmods.dev/skills/dbillion/manim-storytelling-skills/manim-dsa-explainer)
Your own site
<a href="https://agentmods.dev/skills/dbillion/manim-storytelling-skills/manim-dsa-explainer"><img src="https://agentmods.dev/badge/skills/dbillion/manim-storytelling-skills/manim-dsa-explainer/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.

agentmods 80×15 button for manim-dsa-explainer

Your own site · 80×15
<a href="https://agentmods.dev/skills/dbillion/manim-storytelling-skills/manim-dsa-explainer"><img src="https://agentmods.dev/badge/skills/dbillion/manim-storytelling-skills/manim-dsa-explainer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 135 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,749 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00135 $0.02749
Opus 5.5 $0.00054 $0.01100
Sonnet 5.5 $0.00027 $0.00550
Haiku 4.5 $0.00014 $0.00275

Measured 2mo ago against content hash 73087a77f459, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

manim-dsa-explainer 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 2mo ago.

The scan reads SKILL.md. This mod also ships 5 executable files (examples/brute_vs_optimized_kadane.py, examples/single_path_merge_sort_with_test_panel.py, style/dsa_style.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

manim-dsa-explainer/SKILL.md · 208 lines

How it starts

The opening of the file, as written. The whole thing — 208 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Manim DSA Explainer (single-path + comparison, unified)

Relationship to the other skill

Read manim-explainer-animations/SKILL.md and its references/ first -- it owns the mobject/animation API surface (mobjects, animations, camera, plotting, text, advanced techniques). This skill owns the narrative shape for DSA content specifically: which of the two formats to use, the 3D-solid vocabulary, the technique-selection grammar, camera/angle presets, and the mandatory verified-by-test closing beat.

Step 0 -- pick the format

  • Comparison (5 acts): use when a genuine brute-force baseline exists AND the complexity gap is real and instructive (e.g. two-sum brute O(n^2) vs hash-set O(n), LIS O(n^2) vs O(n log n)).
  • Single-path (4 acts): use for everything else -- sorts, traversals, searches, tree/graph operations, single-pass or single-table DP, data structure mechanics, bit tricks. This is the default; most of a DSA catalog has no real brute/optimized pair, so don't force one.

Both formats close with the same Act 6: verified by test (below) -- that part is not optional and does not vary by format.

Comparison format -- 5 acts (~45-90s)

  1. Cold open -- state the problem as a shape in 3D space, no numbers yet.
  2. Brute force -- animate an exhaustive particle sweep (nested loops felt as many particle-trips, not a caption saying "O(n^2)").
  3. The insight -- one beat naming the single fact the optimized version exploits. Give it a full breath.
  4. Optimized -- same 3D space, same camera/axes as act 1, short direct path.
  5. Payoff -- 2D complexity graph, both curves plotted from the true Big-O (Axes.plot, not eyeballed shapes), optimized curve visibly separating.

Single-path format -- 4 acts (~30-50s)

  1. Cold open -- build the data structure/space with the matching solid before any code appears.
  2. The walkthrough -- real source in a Code mobject with a synced SurroundingRectangle highlight tracking the active line, while a particle/marker performs the algorithm in the 3D structure. Largest act.
  3. The key property -- why this approach works (loop invariant, structural guarantee, base case). Real breath (Write + wait), not skipped just because there's no brute-force to contrast against.
  4. Payoff -- final state held (sorted array, traced path, returned value). Optional fixed-in-frame complexity caption.

Read the full file on GitHub · 208 lines

Files

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.

Changes

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.

  1. 2mo ago First seen · 208 lines · 135 tokens per session scan A 73087a77f459

Subscribe to this mod's changes

manim-dsa-explainer is a skill published in the GitHub repository dbillion/manim-storytelling-skills (3 stars, last pushed 3mo ago), licensed MIT. It adds 135 tokens to every session and 2,749 once invoked, about $0.0005 per session on Opus 5.5. 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.

Creative and mediaLearning and teaching
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