OpenGauss is a project-scoped Lean workflow orchestrator that gives coding agents a command-line interface for managing formal proof and formalization tasks. It is used with Lean projects to coordinate agents, tooling, backend sessions, and workflows supplied by lean4-skills. The catalogue add-ons operate these Gauss-native workflows.
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 math-inc/OpenGauss --skill ascii-videogit clone --depth 1 https://github.com/math-inc/OpenGaussWrote 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/math-inc/opengauss/ascii-video)<a href="https://agentmods.dev/skills/math-inc/opengauss/ascii-video"><img src="https://agentmods.dev/badge/skills/math-inc/opengauss/ascii-video/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/math-inc/opengauss/ascii-video"><img src="https://agentmods.dev/badge/skills/math-inc/opengauss/ascii-video.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00118 | $0.04057 |
| Opus 5 | $0.00059 | $0.02028 |
| Sonnet 5 | $0.00024 | $0.00811 |
| Haiku 4.5 | $0.00012 | $0.00406 |
Grade A, and why
ascii-video scanned grade A 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 11d 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.
Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
Never use `stderr=subprocess.PIPE` with long-running ffmpeg. Redirect to file: How it starts
The opening of the file, as written. The whole thing — 257 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ASCII Video Production Pipeline
Full production pipeline for rendering any content as colored ASCII character video.
Modes
| Mode | Input | Output | Read |
|---|---|---|---|
| Video-to-ASCII | Video file | ASCII recreation of source footage | references/inputs.md § Video Sampling |
| Audio-reactive | Audio file | Generative visuals driven by audio features | references/inputs.md § Audio Analysis |
| Generative | None (or seed params) | Procedural ASCII animation | references/effects.md |
| Hybrid | Video + audio | ASCII video with audio-reactive overlays | Both input refs |
| Lyrics/text | Audio + text/SRT | Timed text with visual effects | references/inputs.md § Text/Lyrics |
| TTS narration | Text quotes + TTS API | Narrated testimonial/quote video with typed text | references/inputs.md § TTS Integration |
Stack
Single self-contained Python script per project. No GPU.
| Layer | Tool | Purpose |
|---|---|---|
| Core | Python 3.10+, NumPy | Math, array ops, vectorized effects |
| Signal | SciPy | FFT, peak detection (audio modes only) |
| Imaging | Pillow (PIL) | Font rasterization, video frame decoding, image I/O |
| Video I/O | ffmpeg (CLI) | Decode input, encode output segments, mux audio, mix tracks |
| Parallel | concurrent.futures / multiprocessing | N workers for batch/clip rendering |
| TTS | ElevenLabs API (or similar) | Generate narration clips for quote/testimonial videos |
| Optional | OpenCV | Video frame sampling, edge detection, optical flow |
Pipeline Architecture (v2)
Every mode follows the same 6-stage pipeline. See references/architecture.md for implementation details, references/scenes.md for scene protocol, and references/composition.md for multi-grid composition and tonemap.
┌─────────┐ ┌──────────┐ ┌───────────┐ ┌──────────┐ ┌─────────┐ ┌────────┐
│ 1.INPUT │→│ 2.ANALYZE │→│ 3.SCENE_FN │→│ 4.TONEMAP │→│ 5.SHADE │→│ 6.ENCODE│
│ load src │ │ features │ │ → canvas │ │ normalize │ │ post-fx │ │ → video │
└─────────┘ └──────────┘ └───────────┘ └──────────┘ └─────────┘ └────────┘
What ships with it
11 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.
- README.md 16 KB
- references/architecture.md 33 KB
- references/composition.md 29 KB
- references/design-patterns.md 7.2 KB
- references/effects.md 74 KB
- references/examples.md 15 KB
- references/inputs.md 24 KB
- references/optimization.md 24 KB
- references/scenes.md 14 KB
- references/shaders.md 48 KB
- references/troubleshooting.md 11 KB
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.
- 11d ago First seen · 257 lines · 118 tokens per session scan A 835cddfa05de
ascii-video is a skill published in the GitHub repository math-inc/OpenGauss (1,261 stars, last pushed 5mo ago), licensed MIT. It adds 118 tokens to every session and 4,057 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 1 finding (runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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