Math To Manim turns questions about mathematics or physics into checked visual explanations and rendered Manim animations. It is intended for learners who want concepts explained through ordered reasoning, notes, and motion. Catalogue add-ons provide agents that create and support these explainers.
Borrowing it
Nothing to install: this file belongs to HarleyCoops/Math-To-Manim. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/HarleyCoops/Math-To-Manim/main/CLAUDE.mdgit clone --depth 1 https://github.com/HarleyCoops/Math-To-ManimWrote 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/instructions/harleycoops/math-to-manim/claude-md)<a href="https://agentmods.dev/instructions/harleycoops/math-to-manim/claude-md"><img src="https://agentmods.dev/badge/instructions/harleycoops/math-to-manim/claude-md/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/instructions/harleycoops/math-to-manim/claude-md"><img src="https://agentmods.dev/badge/instructions/harleycoops/math-to-manim/claude-md.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 | $0.00643 | $0.00643 |
| Opus 5.5 | $0.00257 | $0.00257 |
| Sonnet 5.5 | $0.00129 | $0.00129 |
| Haiku 4.5 | $0.00064 | $0.00064 |
Grade B, and why
Math-To-Manim CLAUDE.md scanned grade B with 1 finding 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 7d 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.
Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
- Mechanics: gpt-5.5 is only reachable through the Codex CLI — `codex exec` / `codex review` (my ~/.codex/config.toml defaults to gpt-5.5). Use the codex-implementation, codex-review, and codex-computer-use skills; for w How it starts
The opening of the file, as written. The whole thing — 38 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Picking the right models for workflows and subagents
Rankings, higher = better. Cost reflects what I actually pay (OpenAI has really generous limits), not list price. Intelligence is how hard a problem you can hand the model unsupervised. Taste covers UI/UX, code quality, API design, and copy.
| model | cost | intelligence | taste |
|---|---|---|---|
| gpt-5.5 | 9 | 8 | 5 |
| sonnet-5 | 5 | 5 | 7 |
| opus-4.8 | 4 | 7 | 8 |
| fable-5 | 2 | 9 | 9 |
How to apply:
- These are defaults, not limits. You have standing permission to override them: if a cheaper model's output doesn't meet the bar, rerun or redo the work with a smarter model without asking. Judge the output, not the price tag. Escalating costs less than shipping mediocre work.
- Cost is a tie-breaker only; when axes conflict for anything that ships, intelligence > taste > cost.
- Bulk/mechanical work (clear-spec implementation, data analysis, migrations): gpt-5.5 — it's effectively free.
- Anything user-facing (UI, copy, API design) needs taste ≥ 7.
- Reviews of plans/implementations: fable-5 or opus-4.8, optionally gpt-5.5 as an extra independent perspective.
- Never use Haiku.
- Mechanics: gpt-5.5 is only reachable through the Codex CLI —
codex exec/codex review(my ~/.codex/config.toml defaults to gpt-5.5). Use the codex-implementation, codex-review, and codex-computer-use skills; for work they don't cover (investigation, data analysis), runcodex exec -s read-onlydirectly with a self-contained prompt. - Claude models (sonnet-5, opus-4.8, fable-5) run via the Agent/Workflow model parameter.
Using gpt-5.5 inside workflows and subagents (the model parameter only takes Claude models, so use a wrapper):
- Spawn a thin Claude wrapper agent with
model: 'sonnet', effort: 'low'whose prompt instructs it to write a self-contained codex prompt, runcodex execvia Bash, and return the result.
Agent skills
Issue tracker
Issues live in Linear: team WAR (Warreandvavasour), project Math-To-Manim Upgrade, through the Linear connector. See docs/agents/issue-tracker.md.
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.
- 7d ago Changed · +14 lines · +130 tokens per session 4bdae9aa8d2a
- 1mo ago First seen · 24 lines · 513 tokens per session scan B 07cc03fe87b1
Math-To-Manim CLAUDE.md is an instructions file published in the GitHub repository HarleyCoops/Math-To-Manim (2,804 stars, last pushed 2d ago), licensed MIT. It adds 643 tokens to every session, about $0.0026 per session on Opus 5.5. A static security scan graded it B with 1 finding (reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other instructions, from other repositories
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, cache eligibility and rollout and applying the notice (cutover).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
vscode copilot-instructions.md
Copilot instructions for microsoft/vscode, covering vs code copilot instructions, project overview, root folders, core architecture (src/ folder) and built-in extensions (extensions/ folder).
deepseek-harness AGENTS.md
AGENTS.md instructions for deepseek-ai/deepseek-harness, covering agents.md, pre-stable apis and released session data, repository layout, commands and host sandbox failures.