# Video Use

> Edita cualquier vídeo por conversación: transcribe, corta, hace color grading, genera animaciones de overlay y quema subtítulos, para talking heads, montajes, tutoriales, viajes o entrevistas. Sin presets ni menús.

Fuente: https://skillsagentes.com/skills/browser-use/video-use/video-use
Markdown: https://skillsagentes.com/skills/browser-use/video-use/video-use.md

Repositorio: https://github.com/browser-use/video-use
Autor: browser-use
Licencia: MIT
Actualizado: hace 4 meses
Coste de contexto: 82 tok instalada, 5.7k tok al activarse, 166.2k tok con todos los archivos del bundle
Bundle: 18 archivos, 649 KB
Permisos que pide: ninguno declarado

## Instalación

Un skill son archivos markdown: los mismos archivos valen para cualquier agente y lo único que cambia es el directorio de destino, es decir la bandera `--agent`. Añade `-g` para instalarlo en todos los proyectos de la máquina.

```bash
# Claude Code
npx -y skills add browser-use/video-use --agent claude-code
# Cursor
npx -y skills add browser-use/video-use --agent cursor
# Codex
npx -y skills add browser-use/video-use --agent codex
# Gemini CLI
npx -y skills add browser-use/video-use --agent gemini
# Windsurf
npx -y skills add browser-use/video-use --agent windsurf
# Cline
npx -y skills add browser-use/video-use --agent cline
```

## Qué hace

- Edita cualquier vídeo por conversación: transcribe, corta, hace color grading, genera animaciones de overlay y quema subtítulos, para talking heads, montajes, tutoriales, viajes o entrevistas.
- El LLM razona desde el transcript crudo más visuales a demanda; el único artefacto derivado es `takes_packed.md`, un transcript a nivel de frase.
- El audio es primario y los visuales siguen: los cortes candidatos salen de límites de palabra y silencios, y solo se mira el vídeo en los puntos de decisión.
- Flujo fijo: preguntar, confirmar el plan en lenguaje llano, ejecutar, iterar y persistir en `project.md`; nunca se toca el corte sin aprobación de la estrategia.
- Reglas duras de corrección de producción: subtítulos al final de la cadena de filtros, extracto por segmento más concat sin pérdida, fades de audio de 30ms en cada corte, y nunca cortar dentro de una palabra.

## Cuándo usarla

- Se quiere editar un vídeo hablando: transcribir, cortar, hacer color grading, añadir animaciones de overlay o quemar subtítulos.
- El material son talking heads, montajes, tutoriales, vídeos de viaje o entrevistas y se quiere un corte iterativo por conversación.

## Qué la activa

- "Edita este vídeo de entrevista y deja los mejores takes de cada beat"
- "Corta los silencios y las muletillas de este talking head"
- "Añade subtítulos estilo social y un color grade cálido"
- "Genera una animación de overlay sincronizada con la narración"

## Antes de instalar

- Necesita `ELEVENLABS_API_KEY` para la transcripción con Scribe, `ffmpeg` y `ffprobe` en el PATH, y dependencias de Python; yt-dlp, HyperFrames, Remotion o Manim solo se instalan al primer uso.

## Archivos

- .env.example — 20 B
- .gitignore — 790 B
- LICENSE — 1 KB
- README.md — 6 KB
- SKILL.md — 22 KB
- helpers/grade.py — 13 KB
- helpers/pack_transcripts.py — 7 KB
- helpers/render.py — 27 KB
- helpers/timeline_view.py — 13 KB
- helpers/transcribe.py — 8 KB
- helpers/transcribe_batch.py — 4 KB
- install.md — 8 KB
- poster.html — 20 KB
- pyproject.toml — 450 B
- static/timeline-view.svg — 12 KB
- static/video-use-banner.png — 500 KB
- tests/test_render_fps.py — 5 KB
- tests/test_render_orientation.py — 2 KB

## SKILL.md

Reproducido tal cual desde browser-use/video-use bajo MIT. Esta sección es el documento original y está en inglés.

# Video Use

## Principle

1. **LLM reasons from raw transcript + on-demand visuals.** The only derived artifact that earns its keep is a packed phrase-level transcript (`takes_packed.md`). Everything else — filler tagging, retake detection, shot classification, emphasis scoring — you derive at decision time.
2. **Audio is primary, visuals follow.** Cut candidates come from speech boundaries and silence gaps. Drill into visuals only at decision points.
3. **Ask → confirm → execute → iterate → persist.** Never touch the cut until the user has confirmed the strategy in plain English.
4. **Generalize.** Do not assume what kind of video this is. Look at the material, ask the user, then edit.
5. **Artistic freedom is the default.** Every specific value, preset, font, color, duration, pitch structure, and technique in this document is a *worked example* from one proven video — not a mandate. Read them to understand what's possible and why each worked. Then make your own taste calls based on what the material actually is and what the user actually wants. **The only things you MUST do are in the Hard Rules section below.** Everything else is yours.
6. **Invent freely.** If the material calls for a technique not described here — split-screen, picture-in-picture, lower-third identity cards, reaction cuts, speed ramps, freeze frames, crossfades, match cuts, L-cuts, J-cuts, speed ramps over breath, whatever — build it. The helpers are ffmpeg and PIL. They can do anything the format supports. Do not wait for permission.
7. **Verify your own output before showing it to the user.** If you wouldn't ship it, don't present it.

## Hard Rules (production correctness — non-negotiable)

These are the things where deviation produces silent failures or broken output. They are not taste, they are correctness. Memorize them.

1. **Subtitles are applied LAST in the filter chain**, after every overlay. Otherwise overlays hide captions. Silent failure.
2. **Per-segment extract → lossless `-c copy` concat**, not single-pass filtergraph. Otherwise you double-encode every segment when overlays are added.
3. **30ms audio fades at every segment boundary** (`afade=t=in:st=0:d=0.03,afade=t=out:st={dur-0.03}:d=0.03`). Otherwise audible pops at every cut.
4. **Overlays use `setpts=PTS-STARTPTS+T/TB`** to shift the overlay's frame 0 to its window start. Otherwise you see the middle of the animation during the overlay window.
5. **Master SRT uses output-timeline offsets**: `output_time = word.start - segment_start + segment_offset`. Otherwise captions misalign after segment concat.
6. **Never cut inside a word.** Snap every cut edge to a word boundary from the Scribe transcript.
7. **Pad every cut edge.** Working window: 30–200ms. Scribe timestamps drift 50–100ms — padding absorbs the drift. Tighter for fast-paced, looser for cinematic.
8. **Word-level verbatim ASR only.** Never SRT/phrase mode (loses sub-second gap data). Never normalized fillers (loses editorial signal).
9. **Cache transcripts per source.** Never re-transcribe unless the source file itself changed.
10. **Parallel sub-agents for multiple animations.** Never sequential. Spawn N at once via the `Agent` tool; total wall time ≈ slowest one.
11. **Strategy confirmation before execution.** Never touch the cut until the user has approved the plain-English plan.
12. **All session outputs in `<videos_dir>/edit/`.** Never write inside the `video-use/` project directory.

Everything else in this document is a worked example. Deviate whenever the material calls for it.

## Directory layout

The skill lives in `video-use/`. User footage lives wherever they put it. All session outputs go into `<videos_dir>/edit/`.

```
<videos_dir>/
├── <source files, untouched>
└── edit/
    ├── project.md               ← memory; appended every session
    ├── takes_packed.md          ← phrase-level transcripts, the LLM's primary reading view
    ├── edl.json                 ← cut decisions
    ├── transcripts/<name>.json  ← cached raw Scribe JSON
    ├── animations/slot_<id>/    ← per-animation source + render + reasoning
    ├── clips_graded/            ← per-segment extracts with grade + fades
    ├── master.srt               ← output-timeline subtitles
    ├── downloads/               ← yt-dlp outputs
    ├── verify/                  ← debug frames / timeline PNGs
    ├── preview.mp4
    └── final.mp4
```

## Setup

First-time install lives in `install.md` (clone, deps, ffmpeg, skill registration, API key). Don't re-run it every session; on cold start just verify:

- `ELEVENLABS_API_KEY` resolves — either in the environment or in `.env` at the video-use repo root. If missing, ask the user to paste one and write it to `.env` (never to the user's `<videos_dir>`).
- `ffmpeg` + `ffprobe` on PATH.
- Python deps installed (`uv sync` or `pip install -e .` inside the repo).
- Node.js + npm available if the session needs HyperFrames or Remotion slots. HyperFrames currently requires Node.js 22+.
- `yt-dlp`, HyperFrames, Remotion, Manim installed only on first use.
- First-use animation setup happens inside the slot directory, never at the video-use repo root. HyperFrames can be invoked with `npx --yes hyperframes ...`; Remotion can be scaffolded with `npx create-video@latest` or installed as a project-local dependency before using its `remotion render` command.
- This skill vendors `skills/manim-video/`. Read its SKILL.md when building a Manim slot.

Helpers (`helpers/transcribe.py`, `helpers/render.py`, etc.) live alongside this SKILL.md. Resolve their paths relative to the directory containing this file — the skill is typically symlinked at `~/.claude/skills/video-use/` or `~/.codex/skills/video-use/`.

## Helpers

- **`transcribe.py <video>`** — single-file Scribe call. `--num-speakers N` optional. Cached.
- **`transcribe_batch.py <videos_dir>`** — 4-worker parallel transcription. Use for multi-take.
- **`pack_transcripts.py --edit-dir <dir>`** — `transcripts/*.json` → `takes_packed.md` (phrase-level, break on silence ≥ 0.5s).
- **`timeline_view.py <video> <start> <end>`** — filmstrip + waveform PNG. On-demand visual drill-down. **Not a scan tool** — use it at decision points, not constantly.
- **`render.py <edl.json> -o <out>`** — per-segment extract → concat → overlays (PTS-shifted) → subtitles LAST. `--preview` for 720p fast. `--build-subtitles` to generate master.srt inline.
- **`grade.py <in> -o <out>`** — ffmpeg filter chain grade. Presets + `--filter '<raw>'` for custom.

For animations, create `<edit>/animations/slot_<id>/` with `Bash` and spawn a sub-agent via the `Agent` tool.

## The process

1. **Inventory.** `ffprobe` every source. `transcribe_batch.py` on the directory. `pack_transcripts.py` to produce `takes_packed.md`. Sample one or two `timeline_view`s for a visual first impression.
2. **Pre-scan for problems.** One pass over `takes_packed.md` to note verbal slips, obvious mis-speaks, or phrasings to avoid. Plain list, feed into the editor brief.
3. **Converse.** Describe what you see in plain English. Ask questions *shaped by the material*. Collect: content type, target length/aspect, aesthetic/brand direction, pacing feel, must-preserve moments, must-cut moments, animation and grade preferences, subtitle needs. Do not use a fixed checklist — the right questions are different every time.
4. **Propose strategy.** 4–8 sentences: shape, take choices, cut direction, animation plan, grade direction, subtitle style, length estimate. **Wait for confirmation.**
5. **Execute.** Produce `edl.json` via the editor sub-agent brief. Drill into `timeline_view` at ambiguous moments. Build animations in parallel sub-agents. Apply grade per-segment. Compose via `render.py`.
6. **Preview.** `render.py --preview`.
7. **Self-eval (before showing the user).** Run `timeline_view` on the **rendered output** (not the sources) at every cut boundary (±1.5s window). Check each image for:
   - Visual discontinuity / flash / jump at the cut
   - Waveform spike at the boundary (audio pop that slipped past the 30ms fade)
   - Subtitle hidden behind an overlay (Rule 1 violation)
   - Overlay misaligned or showing wrong frames (Rule 4 violation)

   Also sample: first 2s, last 2s, and 2–3 mid-points — check grade consistency, subtitle readability, overall coherence. Run `ffprobe` on the output to verify duration matches the EDL expectation.

   If anything fails: fix → re-render → re-eval. **Cap at 3 self-eval passes** — if issues remain after 3, flag them to the user rather than looping forever. Only present the preview once the self-eval passes.
8. **Iterate + persist.** Natural-language feedback, re-plan, re-render. Never re-transcribe. Final render on confirmation. Append to `project.md`.

## Cut craft (techniques)

- **Audio-first.** Candidate cuts from word boundaries and silence gaps.
- **Preserve peaks.** Laughs, punchlines, emphasis beats. Extend past punchlines to include reactions — the laugh IS the beat.
- **Speaker handoffs** benefit from air between utterances. Common values: 400–600ms. Less for fast-paced, more for cinematic. Taste call.
- **Audio events as signals.** `(laughs)`, `(sighs)`, `(applause)` mark beats. Extend past them.
- **Silence gaps are cut candidates.** Silences ≥400ms are usually the cleanest. 150–400ms phrase boundaries are usable with a visual check. <150ms is unsafe (mid-phrase).
- **Example cut padding** (the launch video shipped with this): 50ms before the first kept word, 80ms after the last. Tighter for montage energy, looser for documentary. Stay in the 30–200ms working window (Hard Rule 7).
- **Never reason audio and video independently.** Every cut must work on both tracks.

## The packed transcript (primary reading view)

`pack_transcripts.py` reads all `transcripts/*.json` and produces one markdown file where each take is a list of phrase-level lines, each prefixed with its `[start-end]` time range. Phrases break on any silence ≥ 0.5s OR speaker change. This is the artifact the editor sub-agent reads to pick cuts — it gives word-boundary precision from text alone at 1/10 the tokens of raw JSON.

Example line:
```
## C0103  (duration: 43.0s, 8 phrases)
  [002.52-005.36] S0 Ninety percent of what a web agent does is completely wasted.
  [006.08-006.74] S0 We fixed this.
```

## Editor sub-agent brief (for multi-take selection)

When the task is "pick the best take of each beat across many clips," spawn a dedicated sub-agent with a brief shaped like this. The structure is load-bearing; the pitch-shape example is not.

```
You are editing a <type> video. Pick the best take of each beat and 
assemble them chronologically by beat, not by source clip order.

INPUTS:
  - takes_packed.md (time-annotated phrase-level transcripts of all takes)
  - Product/narrative context: <2 sentences from the user>
  - Speaker(s): <name, role, delivery style note>
  - Expected structure: <pick an archetype or invent one>
  - Verbal slips to avoid: <list from the pre-scan pass>
  - Target runtime: <seconds>

Common structural archetypes (pick, adapt, or invent):
  - Tech launch / demo:   HOOK → PROBLEM → SOLUTION → BENEFIT → EXAMPLE → CTA
  - Tutorial:             INTRO → SETUP → STEPS → GOTCHAS → RECAP
  - Interview:            (QUESTION → ANSWER → FOLLOWUP) repeat
  - Travel / event:       ARRIVAL → HIGHLIGHTS → QUIET MOMENTS → DEPARTURE
  - Documentary:          THESIS → EVIDENCE → COUNTERPOINT → CONCLUSION
  - Music / performance:  INTRO → VERSE → CHORUS → BRIDGE → OUTRO
  - Or invent your own.

RULES:
  - Start/end times must fall on word boundaries from the transcript.
  - Pad cut boundaries (working window 30–200ms).
  - Prefer silences ≥ 400ms as cut targets.
  - Unavoidable slips are kept if no better take exists. Note them in "reason".
  - If over budget, revise: drop a beat or trim tails. Report total and self-correct.

OUTPUT (JSON array, no prose):
  [{"source": "C0103", "start": 2.42, "end": 6.85, "beat": "HOOK",
    "quote": "...", "reason": "..."}, ...]

Return the final EDL and a one-line total runtime check.
```

## Color grade (when requested)

Your job is to **reason about the image**, not apply a preset. Look at a frame (via `timeline_view`), decide what's wrong, adjust one thing, look again.

Mental model is ASC CDL. Per channel: `out = (in * slope + offset) ** power`, then global saturation. `slope` → highlights, `offset` → shadows, `power` → midtones.

**Example filter chains** (`grade.py` has `--list-presets`; use them as starting points or mix your own):

- **`warm_cinematic`** — retro/technical, subtle teal/orange split, desaturated. Shipped in a real launch video. Safe for talking heads.
- **`neutral_punch`** — minimal corrective: contrast bump + gentle S-curve. No hue shifts.
- **`none`** — straight copy. Default when the user hasn't asked.

For anything else — portraiture, nature, product, music video, documentary — invent your own chain. `grade.py --filter '<raw ffmpeg>'` accepts any filter string.

Hard rules: apply **per-segment during extraction** (not post-concat, which re-encodes twice). Never go aggressive without testing skin tones.

## Subtitles (when requested)

Subtitles have three dimensions worth reasoning about: **chunking** (1/2/3/sentence per line), **case** (UPPER/Title/Natural), and **placement** (margin from bottom). The right combo depends on content.

**Worked styles** — pick, adapt, or invent:

**`bold-overlay`** — short-form tech launch, fast-paced social. 2-word chunks, UPPERCASE, break on punctuation, Helvetica 18 Bold, white-on-outline, `MarginV=35`. `render.py` ships with this as `SUB_FORCE_STYLE`.

```
FontName=Helvetica,FontSize=18,Bold=1,
PrimaryColour=&H00FFFFFF,OutlineColour=&H00000000,BackColour=&H00000000,
BorderStyle=1,Outline=2,Shadow=0,
Alignment=2,MarginV=35
```

**`natural-sentence`** (if you invent this mode) — narrative, documentary, education. 4–7 word chunks, sentence case, break on natural pauses, `MarginV=60–80`, larger font for readability, slightly wider max-width. No shipped force_style — design one if you need it.

Invent a third style if neither fits. Hard rules: subtitles LAST (Rule 1), output-timeline offsets (Rule 5).

## Animations (when requested)

Animations match the content and the brand. **Get the palette, font, and visual language from the conversation** — never assume a default. If the user hasn't told you, propose a palette in the strategy phase and wait for confirmation before building anything.

**Tool options:**

Pick the engine per animation slot. Do not default to Remotion just because the animation is web-adjacent.

- **HyperFrames** — Browser-native HTML/CSS/GSAP video compositions: product UI motion, website-to-video or mockup-to-video captures, kinetic typography, landing-page/storyboard promos, data-driven UI states, transparent WebM overlays, and clips that need deterministic frame capture plus HyperFrames lint/validate/render checks. Best when the animation should be authored and verified like a web composition instead of a React component tree.
- **Remotion** — React/CSS compositions with component state, reusable React primitives, or an existing Remotion brand system. Best when the user specifically asks for React/Remotion or when React composition is the simpler authoring model.
- **Manim** — formal diagrams, state machines, equation derivations, graph morphs. Read `skills/manim-video/SKILL.md` and its references for depth.
- **PIL + PNG sequence + ffmpeg** — simple overlay cards: counters, typewriter text, single bar reveals, progressive draws. Fast to iterate, any aesthetic you want. The launch video used this.

For HyperFrames slots, scaffold the slot inside `edit/animations/slot_<id>/` with `npx --yes hyperframes init . --example blank --non-interactive --skip-skills`, build the HTML composition there, run the HyperFrames checks that fit the slot (`lint`, `validate`, and a draft render when practical), then produce the final overlay video with `npx --yes hyperframes render . -o render.mp4` or `--format webm -o render.webm` when alpha is required. Point the EDL overlay `file` at the actual rendered path.

For Remotion slots, keep the Remotion project isolated inside the same slot directory, scaffold with `npx create-video@latest` or install Remotion locally there, render the composition to `render.mp4` with the project-local `remotion render` command, and verify duration and dimensions with `ffprobe`.

None is mandatory. Invent hybrids if useful (e.g., PIL background with a HyperFrames or Remotion layer on top).

**Duration rules of thumb, context-dependent:**

- **Sync-to-narration explanations.** A viewer needs to parse the content at 1×. Rough floor 3s, typical 5–7s for simple cards, 8–14s for complex diagrams. The launch video shipped at 5–7s per simple card.
- **Beat-synced accents** (music video, fast montage). 0.5–2s is fine — they're visual accents, not information. The "readable at 1×" rule becomes *"recognizable at 1×"*, not *"fully parseable."*
- **Hold the final frame ≥ 1s** before the cut (universal).
- **Over voiceover:** total duration ≥ `narration_length + 1s` (universal).
- **Never parallel-reveal independent elements** — the eye can't track two new things at once. One thing, pause, next thing.

**Animation payoff timing (rule for sync-to-narration):** get the payoff word's timestamp. Start the overlay `reveal_duration` seconds earlier so the landing frame coincides with the spoken payoff word. Without this sync the animation feels disconnected.

**Easing** (universal — never `linear`, it looks robotic):

```python
def ease_out_cubic(t):    return 1 - (1 - t) ** 3
def ease_in_out_cubic(t):
    if t < 0.5: return 4 * t ** 3
    return 1 - (-2 * t + 2) ** 3 / 2
```

`ease_out_cubic` for single reveals (slow landing). `ease_in_out_cubic` for continuous draws.

**Typing text anchor trick:** center on the FULL string's width, not the partial-string width — otherwise text slides left during reveal.

**Example palette** (the launch video — one aesthetic among infinite):
- Background `(10, 10, 10)` near-black
- Accent `#FF5A00` / `(255, 90, 0)` orange
- Labels `(110, 110, 110)` dim gray
- Font: Menlo Bold at `/System/Library/Fonts/Menlo.ttc` (index 1)
- ≤ 2 accent colors, ~40% empty space, minimal chrome
- Result: terminal / retro tech feel

This is one style. If the brand is warm and serif, use that. If it's colorful and playful, use that. If the user handed you a style guide, follow it. If they didn't, propose one and confirm.

**Parallel sub-agent brief** — each animation is one sub-agent spawned via the `Agent` tool. Each prompt is self-contained (sub-agents have no parent context). Include:

1. One-sentence goal: *"Build ONE animation: [spec]. Nothing else."*
2. Absolute output path (`<edit>/animations/slot_<id>/render.mp4`)
3. Exact technical spec: resolution, fps, codec, pix_fmt, CRF, duration
4. Style palette as concrete values (RGB tuples, hex, or reference to a design system)
5. Font path with index
6. Frame-by-frame timeline (what happens when, with easing)
7. Anti-list ("no chrome, no extras, no titles unless specified")
8. Code pattern reference (copy helpers inline, don't import across slots)
9. Deliverable checklist (script, render, verify duration via ffprobe, report)
10. **"Do not ask questions. If anything is ambiguous, pick the most obvious interpretation and proceed."**

One sub-agent = one file (unique filenames, parallel agents don't overwrite each other).

## Output spec

Match the source unless the user asked for something specific. Common targets: `1920×1080@24` cinematic, `1920×1080@30` screen content, `1080×1920@30` vertical social, `3840×2160@24` 4K cinema, `1080×1080@30` square. `render.py` defaults the scale to 1080p from any source; pass `--filter` or edit the extract command for other targets. Worth asking the user which delivery format matters.

## EDL format

```json
{
  "version": 1,
  "sources": {"C0103": "/abs/path/C0103.MP4", "C0108": "/abs/path/C0108.MP4"},
  "ranges": [
    {"source": "C0103", "start": 2.42, "end": 6.85,
     "beat": "HOOK", "quote": "...", "reason": "Cleanest delivery, stops before slip at 38.46."},
    {"source": "C0108", "start": 14.30, "end": 28.90,
     "beat": "SOLUTION", "quote": "...", "reason": "Only take without the false start."}
  ],
  "grade": "warm_cinematic",
  "overlays": [
    {"file": "edit/animations/slot_1/render.mp4", "start_in_output": 0.0, "duration": 5.0}
  ],
  "subtitles": "edit/master.srt",
  "total_duration_s": 87.4
}
```

`grade` is a preset name or raw ffmpeg filter. `overlays` are rendered animation clips. `subtitles` is optional and applied LAST.

## Memory — `project.md`

Append one section per session at `<edit>/project.md`:

```markdown
## Session N — YYYY-MM-DD

**Strategy:** one paragraph describing the approach
**Decisions:** take choices, cuts, grades, animations + why
**Reasoning log:** one-line rationale for non-obvious decisions
**Outstanding:** deferred items
```

On startup, read `project.md` if it exists and summarize the last session in one sentence before asking whether to continue.

## Anti-patterns

Things that consistently fail regardless of style:

- **Hierarchical pre-computed codec formats** with USABILITY / tone tags / shot layers. Over-engineering. Derive from the transcript at decision time.
- **Hand-tuned moment-scoring functions.** The LLM picks better than any heuristic you'll write.
- **Whisper SRT / phrase-level output.** Loses sub-second gap data. Always word-level verbatim.
- **Running Whisper locally on CPU.** Slow and it normalizes fillers. Use hosted Scribe.
- **Burning subtitles into base before compositing overlays.** Overlays hide them. (Hard Rule 1.)
- **Single-pass filtergraph when you have overlays.** Double re-encodes. Use per-segment extract → concat.
- **Linear animation easing.** Looks robotic. Always cubic.
- **Hard audio cuts at segment boundaries.** Audible pops. (Hard Rule 3.)
- **Typing text centered on the partial string.** Text slides left as it grows.
- **Sequential sub-agents for multiple animations.** Always parallel.
- **Editing before confirming the strategy.** Never.
- **Re-transcribing cached sources.** Immutable outputs of immutable inputs.
- **Assuming what kind of video it is.** Look first, ask second, edit last.

## Dónde encaja

- Categoría: [Productividad](https://skillsagentes.com/categorias/productividad.md) — Planificación, toma de notas y automatización de flujos personales.
- Creador: [browser-use](https://skillsagentes.com/creators/browser-use.md) — 6 skills en el directorio
- [Todas las skills](https://skillsagentes.com/skills.md)
- [Ranking de instalaciones](https://skillsagentes.com/ranking.md)

## Otras skills del mismo repositorio

- [Manim Video](https://skillsagentes.com/skills/browser-use/video-use/manim-video.md): Pipeline de producción de animaciones matemáticas y técnicas con Manim Community Edition: vídeos explicativos estilo 3Blue1Brown, visualizaciones de algoritmos, derivaciones de ecuaciones, diagramas de arquitectura e historias de datos.

## Skills relacionadas

- [Brainstorming](https://skillsagentes.com/skills/obra/superpowers/brainstorming.md): Debes usarlo antes de cualquier trabajo creativo: crear features, construir componentes, añadir funcionalidad o modificar comportamiento. Explora la intención, requisitos y diseño antes de implementar.
- [Executing Plans](https://skillsagentes.com/skills/obra/superpowers/executing-plans.md): Úsalo cuando tengas un plan de implementación escrito para ejecutar en una sesión separada con puntos de revisión.
- [Writing Plans](https://skillsagentes.com/skills/obra/superpowers/writing-plans.md): Úsala cuando tengas un spec o requisitos para una tarea de múltiples pasos, antes de tocar código.
- [Using Superpowers](https://skillsagentes.com/skills/obra/superpowers/using-superpowers.md): Úsala al iniciar cualquier conversación: establece cómo encontrar y usar skills, exigiendo su invocación antes de CUALQUIER respuesta, incluso preguntas aclaratorias.
- [Ask Matt](https://skillsagentes.com/skills/mattpocock/skills/ask-matt.md): Pregunta qué skill o qué flujo encaja con tu situación. Un router sobre los skills de este repo.

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