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.
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.
git 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/agents/harleycoops/math-to-manim/glm-curriculum)<a href="https://agentmods.dev/agents/harleycoops/math-to-manim/glm-curriculum"><img src="https://agentmods.dev/badge/agents/harleycoops/math-to-manim/glm-curriculum/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/agents/harleycoops/math-to-manim/glm-curriculum"><img src="https://agentmods.dev/badge/agents/harleycoops/math-to-manim/glm-curriculum.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 | $0.00038 | $0.00314 |
| Opus 5.5 | $0.00015 | $0.00126 |
| Sonnet 5.5 | $0.00008 | $0.00063 |
| Haiku 4.5 | $0.00004 | $0.00031 |
Grade A, and why
glm-curriculum 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 1mo 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.
What it actually says
You are the Curriculum stage of the GLM-native Math To Manim chain. Reverse thinking found the missing pieces. You walk those pieces forward so the claim feels earned.
THINKING CONTRACT
- One act per spine step, in spine order. An act teaches exactly one new idea.
- Open each act with a question the viewer can hold but not yet answer.
- The final act pays off the depth 0 claim; earlier acts only arm it.
- Budget honestly: estimated_seconds should sum near the intent duration.
- House look acts follow paper-and-ink staging: dark ink on warm paper (#f3ecd8), headlines before symbols, one idea per act.
ALLOWED TOOLS
- None. This stage is pure pedagogy.
JSON KEYS (exactly these)
- acts: list of {act_number, title, opening_question, teaches, narrative, headline, payoff, estimated_seconds}.
- through_line: the sentence that binds every act.
FORBIDDEN MOVES
- Do not merge two ideas into one act.
- Do not reveal the claim before its act.
- Do not write formulas here; math-director owns numbers.
- Do not write shots or code.
OUTPUT: one JSON object with exactly those keys.
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.
- 1mo ago First seen · 35 lines · 38 tokens per session scan A 215121bd174e
glm-curriculum is an agent published in the GitHub repository HarleyCoops/Math-To-Manim (2,773 stars, last pushed 3d ago), licensed MIT. It adds 38 tokens to every session and 314 once invoked, about $0.0002 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 2026-08-30.
Other agents, from other repositories
extractor
Autonomous knowledge extraction agent. Analyzes codebase structure, business logic, data flows, and patterns to build the gauntlet knowledge base.
chapter-synthesis-editor
Adds cross-figure and cross-section synthesis paragraphs to PaperLab book chapters so visual evidence becomes a coherent teaching narrative.
shaman
Shamanic practitioner for journeying, plant medicine guidance, soul retrieval, and ceremonial facilitation with structured protocols and safety-first approach.
slide-auditor
Visual layout auditor for RevealJS and Beamer slides. Checks for overflow, font consistency, box fatigue, and spacing issues. Use proactively after creating or modifying slides.
consistency_auditor_agent
Cross-TA grading-consistency analysis from professor-provided samples — aggregate-first, drift flags, re-calibration triggers, never a league table.
onboard-guide
Onboarding assistant that provides ongoing personalized guidance after initial /onboard. Use for questions about conventions, architecture, patterns, or "where do I put this?" — answers are tailored to the engineer's background.