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 Mun1to/vidorq --skill skillgit clone --depth 1 https://github.com/Mun1to/vidorqWrote 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/mun1to/vidorq/skill)<a href="https://agentmods.dev/skills/mun1to/vidorq/skill"><img src="https://agentmods.dev/badge/skills/mun1to/vidorq/skill/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/mun1to/vidorq/skill"><img src="https://agentmods.dev/badge/skills/mun1to/vidorq/skill.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 | $0.00000 | $0.02074 |
| Opus 5.5 | $0.00000 | $0.00830 |
| Sonnet 5.5 | $0.00000 | $0.00415 |
| Haiku 4.5 | $0.00000 | $0.00207 |
Grade A, and why
skill scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 123 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Vidorq skill — edición por IA (v1)
Pipeline de edición que corre desde Claude Code. Hay dos salidas y las dos funcionan: el render directo (PyAV + NVENC), que no necesita Resolve para nada, y el timeline editable dentro de Resolve a través del puente. Auditadas las dos con el mismo encargo el 19-ago-2026. Documentación interna en español (regla D).
Flujo
video crudo ──► transcribe.py ──► transcript.json + takes_packed.md
│
(el LLM lee y razona el corte)
▼
edl.json ──► vidorq_render.py ──► final.mp4
(keep-segments + zoom) (cortes + punch zoom + captions)
Uso
# El intérprete con faster-whisper, PyAV, Pillow y onnxruntime dentro. En una
# instalación normal es el entorno de Vidorq; si usas otro, apúntalo aquí.
PY="$PWD/.venv/Scripts/python.exe"
# 1) Transcribir (word-level, local)
"$PY" skill/helpers/transcribe.py "<video>" "<out_dir>" es
# 2) Autorar edl.json a partir de takes_packed.md (paso de razonamiento del LLM)
# formato: {"strategy": "...", "segments": [{"start","end","zoom","note"}, ...]}
# 3) Renderizar
"$PY" skill/helpers/vidorq_render.py "<video>" "<out_dir>/edl.json" "<out_dir>/transcript.json" "<out_dir>/final.mp4"
#
# Los que casi siempre importan:
# --export <destino> a dónde va el archivo, y con eso el caudal, el audio
# y el volumen ya puestos. Uno de: youtube, youtube4k,
# shorts, instagram, x, mensajeria, master.
# Sin esto se usa `youtube`.
# --ratio <forma> source | vertical | portrait | square | wide
# --preset <estilo> el estilo de subtítulo (pop, punch, brasa...)
# --detras los subtítulos POR DETRÁS del sujeto. Cuesta unos
# 6 minutos por minuto de vídeo, así que se pide.
# Si el vídeo no tiene un sujeto que recortar lo dice
# por `MASCARA_NO:` y entrega el vídeo con los
# subtítulos delante, en vez de con manchas encima.
# --curva <nombre> CÓMO entran el texto y los rótulos: suave, rapida,
# muelle, atras, elastica, rebote o lineal. Sin esto,
# cada animación usa la suya, que ya es de calidad.
# --no-captions sin subtítulos
# --no-zoom sin punch zoom
#
# Escribe en stdout, una línea por cosa, para poder seguirlo desde fuera:
# PROGRESS <hechos> <total> avance; con --detras el total es el doble,
# porque cada fotograma se toca dos veces
# EXPORT: ... qué tamaño y qué caudal se van a usar
# VIDEO_OK / AUDIO_OK / MUX_OK / DONE
# SIN_AUDIO: el vídeo de origen es mudo y sale mudo
What ships with it
29 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.
- helpers/agente.py 15 KB runs code
- helpers/aprende.py 28 KB runs code
- helpers/autocolor.py 8.4 KB runs code
- helpers/build_resolve_timeline.py 3.2 KB runs code
- helpers/captions.py 56 KB runs code
- helpers/curvas.py 11 KB runs code
- helpers/descargar.py 6.4 KB runs code
- helpers/director.py 55 KB runs code
- helpers/efectos.py 12 KB runs code
- helpers/exportar.py 14 KB runs code
- helpers/faces.py 8.5 KB runs code
- helpers/fusion.py 15 KB runs code
- helpers/galeria.py 20 KB runs code
- helpers/leer.py 22 KB runs code
- helpers/looks.py 10 KB runs code
- helpers/mascara.py 19 KB runs code
- helpers/overlays.py 19 KB runs code
- helpers/previews.py 26 KB runs code
- helpers/providers.py 25 KB runs code
- helpers/segmentador.py 6.7 KB runs code
- helpers/speech.py 11 KB runs code
- helpers/transcribe.py 9.3 KB runs code
- helpers/translate.py 10 KB runs code
- helpers/vidorq_render.py 39 KB runs code
- helpers/vision.py 25 KB runs code
- models/face_detection_yunet_2023mar.onnx 227 KB
- models/LICENSE.u2net.txt 12 KB
- models/LICENSE.yunet.txt 1.1 KB
- models/u2netp.onnx 4468 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.
- 1mo ago Changed · +45 lines 05df042b9677
- 2mo ago First seen · 78 lines · 0 tokens per session scan A 342e81ebb508
skill is a skill published in the GitHub repository Mun1to/vidorq (5 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 2,074 tokens. 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 2026-08-31.
skill compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| skillMun1to/vidorq | Skill | 5 | 1mo ago | MIT | A | 0 | Claude Code, Codex |
| experiment-tracking-swanlabOrchestra-Research/AI-Research-SKILLs | Skill | 14k | 27d ago | MIT | A | 40 | Claude Code, Codex |
| ads-youtubeAgriciDaniel/claude-ads | Skill | 11k | 6d ago | MIT | A | 84 | Claude Code |
| ads-launchAgriciDaniel/claude-ads | Skill | 11k | 6d ago | MIT | A | 45 | Claude Code |
| notificationsvellum-ai/vellum-assistant | Skill | 1.5k | 3d ago | MIT | A | 9 | Claude Code, Codex |
| telegram-setupvellum-ai/vellum-assistant | Skill | 1.5k | 3d ago | MIT | A | 22 | Claude Code, Codex |
| docssamuelgursky/davinci-resolve-mcp | Skill | 4.0k | yesterday | MIT | B | 0 | Claude Code, Codex |