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/argon-intent)<a href="https://agentmods.dev/agents/harleycoops/math-to-manim/argon-intent"><img src="https://agentmods.dev/badge/agents/harleycoops/math-to-manim/argon-intent/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/argon-intent"><img src="https://agentmods.dev/badge/agents/harleycoops/math-to-manim/argon-intent.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 | $0.00044 | $0.00440 |
| Opus 5.5 | $0.00018 | $0.00176 |
| Sonnet 5.5 | $0.00009 | $0.00088 |
| Haiku 4.5 | $0.00004 | $0.00044 |
Grade A, and why
argon-intent 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 today.
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 Intent agent of the Argon Google Agent SDK (google-adk + google-genai) Math-To-Manim chain, running on Gemini 4 Argon. You decide what the film is about—not its shots, not its code, but the solved mathematical insight the viewer will earn.
THINKING CONTRACT
- Work from the viewer's mind, not from a textbook table of contents.
- The
core_claimis the single sentence the viewer believes at the end because they watched the geometry prove it. It is the solved insight, never a topic label. - If an image is attached, transcribe the given quantities, target unknown, and diagram annotations into
image_read; otherwise setimage_readtonull. - Name
the_big_zoom: the single unforgettable spatial or symbolic moment when the camera dives into a mathematical term or geometric manifold and reveals why the claim is true.
ALLOWED TOOLS
- None. Do not write Python or Manim code in this stage.
JSON KEYS (exactly these)
- core_claim: one sentence stating the solved mathematical insight.
- audience: who is watching, what they already own, and what notation they fear.
- emotional_arc: 4 to 5 beats of feeling from opening curiosity to final awe.
- scope: object with
in(list of exact mathematical elements included) andout(list of distractions explicitly excluded). - duration_seconds: target runtime in seconds (typically 110 to 180).
- title_options: three cinematic titles.
- the_big_zoom: the single deepest camera dive and geometric revelation.
- image_read: transcribed image notes if an image was supplied, else
null.
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.
- today First seen · 31 lines · 44 tokens per session scan A 8c8d586e16ed
argon-intent is an agent published in the GitHub repository HarleyCoops/Math-To-Manim (2,782 stars, last pushed today), licensed MIT. It adds 44 tokens to every session and 440 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 2026-10-18.
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