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Agent skill · Audited from source

ascii-video

skill · nousresearch/hermes-agentMIT licenceAudited 31 Oct 2026 · source 15697f9e43dc

★ 258,923pushed todayversion 1.0.0
✓SAFEGrade B · 89/100 · 31 Oct 2026 · 15697f9
258,923repo stars · whole nousresearch/hermes-agent

Is it safe? Yes — SAFE, grade B (89/100). We read this skill's source at commit 15697f9e43dc and found no filesystem, network or shell access and no hard-coded secrets. What it does: ASCII video: convert video/audio to colored ASCII MP4/GIF.

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Cite this page

ModelsAtlas. “ascii-video (nousresearch/hermes-agent)”. Retrieved 31 Oct 2026. https://modelsatlas.com/skills/nousresearch/ascii-video

Trust audit

Audit 0.4.1 · source read 31 Oct 2026

Trust score89/100✓SAFE B
0 critical0 high0 medium0 low0 info

SAFE means nothing in the source contradicts what the skill says it does. Grade B is shared by 16,667 of 17,602 audited skills.

What the source does

  • FilesystemNone observedNo reads or writes in the source
  • NetworkNone observedNo outbound calls in the source
  • ShellNone observedNo commands run in the source
  • DependenciesPinnedNothing floats
  • SecretsNone foundNo keys in source

Five audit layers

LayerWhat we checkResultFindings
L0 ProvenanceRepo owner, licence, archive status, activityPASS0
L1 Static sourceSecrets, path traversal, supply chain, hidden codeNA0
L2 InstructionsPrompt injection, authority framing, hidden directivesPASS0
L3 InventoryThe files and declarations match the sourcePASS0
L4 SandboxRun in isolation and watch behaviourSKIPPED why0

Gates applied: no behavioural pass.

Findings (0)

No findings at any severity. We re-audit when the source changes.

Audit 0.4.1 · source sha 15697f9e43dc · 31 Oct 2026Report an issue or request a re-scan

Provenance

Who published it, and what the verdict is pinned to

  • Publishernousresearch GitHub organizationOwner of the repository this skill is read from
  • Source foldernousresearch/hermes-agent/skills/creative/ascii-videoThe exact folder we audited
  • LicenceMITAs the repository states it
  • Commit pinned for this verdict15697f9e43dcA new audit runs when the source changes
  • Repository statusNot archivedPushed today
  • Sandboxed runNot runSkills are read, not executed; layer L4 is skipped

What it tells the agent

Full source on GitHub ↗

Its description: ASCII video: convert video/audio to colored ASCII MP4/GIF.

---
name: ascii-video
description: "ASCII video: convert video/audio to colored ASCII MP4/GIF."
version: 1.0.0
author: SHL0MS, Hermes Agent
license: MIT
platforms: [linux, macos, windows]
metadata:
  hermes:
    tags: [ASCII, Video, FFmpeg, Terminal-Art]
    related_skills: []
---

# ASCII Video Production Pipeline

## When to use

Use when users request: ASCII video, text art video, terminal-style video, character art animation, retro text visualization, audio visualizer in ASCII, converting video to ASCII art, matrix-style effects, or any animated ASCII output.

## What's inside

Production pipeline for ASCII art video — any format. Converts video/audio/images/generative input into colored ASCII character video output (MP4, GIF, image sequence). Covers: video-to-ASCII conversion, audio-reactive music visualizers, generative ASCII art animations, hybrid video+audio reactive, text/lyrics overlays, real-time terminal rendering.

## Creative Standard

This is visual art. ASCII characters are the medium; cinema is the standard.

**Before writing a single line of code**, articulate the creative concept. What is the mood? What visual story does this tell? What makes THIS project different from every other ASCII video? The user's prompt is a starting point — interpret it with creative ambition, not literal transcription.

**First-render excellence is non-negotiable.** The output must be visually striking without requiring revision rounds. If something looks generic, flat, or like "AI-generated ASCII art," it is wrong — rethink the creative concept before shipping.

**Go beyond the reference vocabulary.** The effect catalogs, shader presets, and palette libraries in the references are a starting vocabulary. For every project, combine, modify, and invent new patterns. The catalog is a palette of paints — you write the painting.

**Be proactively creative.** Extend the skill's vocabulary when the project calls for it. If the references don't have what the vision demands, build it. Include at least one visual moment the user didn't ask for but will appreciate — a transition, an effect, a color choice that elevates the whole piece.

**Cohesive aesthetic over technical correctness.** All scenes in a video must feel connected by a unifying visual language — shared color temperature, related character palettes, consistent motion vocabulary. A technically correct video where every scene uses a random different effect is an aesthetic failure.

**Dense, layered, considered.** Every frame should reward viewing. Never flat black backgrounds. Always multi-grid composition. Always per-scene variation. Always intentional color.

## Modes

| Mode | Input | Output | Reference |
|------|-------|--------|-----------|
| **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 required.

| Layer | Tool | Purpose |
|-------|------|---------|
| Core | Python 3.10+, NumPy | Math, array ops, vectorized effects |
| Signal | SciPy | FFT, peak detection (audio modes) |
| Imaging | Pillow (PIL) | Font rasterization, frame decoding, image I/O |
| Video I/O | ffmpeg (CLI) | Decode input, encode output, mux audio |
| Parallel | concurrent.futures | N workers for batch/clip rendering |
| TTS | ElevenLabs API (optional) | Generate narration clips |
| Optional | OpenCV | Video frame sampling, edge detection |

## Pipeline Architecture

Every mode follows the same 6-stage pipeline:

```
INPUT → ANALYZE → SCENE_FN → TONEMAP → SHADE → ENCODE
```

1. **INPUT** — Load/decode source material (video frames, audio samples, images, or nothing)
2. **ANALYZE** — Extract per-frame features (audio bands, video luminance/edges, motion vectors)
3. **SCENE_FN** — Scene function renders to pixel canvas (`uint8 H,W,3`). Composes multiple character grids via `_render_vf()` + pixel blend modes. See `references/composition.md`
4. **TONEMAP** — Percentile-based adaptive brightness normalization. See `references/composition.md` § Adaptive Tonemap
5. **SHADE** — Post-processing via `ShaderChain` + `FeedbackBuffer`. See `references/shaders.md`
6. **ENCODE** — Pipe raw RGB frames to ffmpeg for H.264/GIF encoding

## Creative Direction

### Aesthetic Dimensions

| Dimension | Options | Reference |
|-----------|---------|-----------|
| **Character palette** | Density ramps, block elements, symbols, scripts (katakana, Greek, runes, braille), project-specific | `architecture.md` § Palettes |
| **Color strategy** | HSV, OKLAB/OKLCH, discrete RGB palettes, auto-generated harmony, monochrome, temperature | `architecture.md` § Color System |
| **Background texture** | Sine fields, fBM noise, domain warp, voronoi, reaction-diffusion, cellular automata, video | `effects.md` |
| **Primary effects** | Rings, spirals, tunnel, vortex, waves, interference, aurora, fire, SDFs, strange attractors | `effects.md` |
| **Particles** | Sparks, snow, rain, bubbles, runes, orbits, flocking boids, flow-field followers, trails | `effects.md` § Particles |
| **Shader mood** | Retro CRT, clean modern, glitch art, cinematic, dreamy, industrial, psychedelic | `shaders.md` |
| **Grid density** | xs(8px) through xxl(40px), mixed per layer | `architecture.md` § Grid System |
| **Coordinate space** | Cartesian, polar, tiled, rotated, fisheye, Möbius, domain-warped | `effects.md` § Transforms |
| **Feedback** | Zo

Excerpt, first 6,000 characters of SKILL.md, verbatim from the audited commit. It is text from someone else’s repository, quoted so you can judge it before your agent reads it.

Install

Pinned to the audited commit 15697f9

Download folder ↗
git clone https://github.com/nousresearch/hermes-agent
git -C hermes-agent checkout 15697f9e43dc

The author documents no install command, so this uses the repository directly. Our verdict covers commit 15697f9e43dc only.

Works in which agents?

What its own text says, not a test

AgentStatusMore
CursorMentioned in its text, not testedSkills for Cursor · About Cursor
“Mentioned” means the skill’s text names the agent. We have not run it there.

Audit history

Every audit, every source change

  1. ✓SAFE B 89 / 100

    first audit · source 15697f9e43dc

README badge

For maintainers · shows the latest audit

ModelsAtlas: SAFE BMODELSATLASSAFE · B
[![ModelsAtlas: SAFE B](https://modelsatlas.com/skills/nousresearch/ascii-video/badge.svg)](https://modelsatlas.com/skills/nousresearch/ascii-video/)

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Questions about ascii-video

What does the ascii-video skill do?
The agent that grows with you
Is ascii-video safe to install?
The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.
What can ascii-video access on my machine?
The audit observed no filesystem, network or shell use at all in its source.
Which assistants does ascii-video work with?
Its documentation mentions cursor. That is what the text claims, not a compatibility test we ran.
How current is this page?
The grade is for one exact copy of the source (15697f9e43dc), read on 2026-10-31. The repository is watched, and a new audit runs when it changes — this is the first audit.

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