Agent skill

Stitch Videos Ffmpeg

by gooseworks-ai in gooseworks-ai/goose-skills

Stitch video segments with ffmpeg concat, xfade, overlay, audio mux, and export settings, and trim a source into named clips at exact windows (trimclips.py).

MITAuto-check passedMedia & Creative

Install Stitch Videos Ffmpeg

skills CLI
$ npx skills add gooseworks-ai/goose-skills --skill stitch-videos-ffmpeg -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install gooseworks-ai/goose-skills stitch-videos-ffmpeg --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/gooseworks-ai/goose-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/ads/packs/video-ad-formats/stitch-videos-ffmpeg .claude/skills/stitch-videos-ffmpeg && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
stitch-videos-ffmpeg
GitHub stars
1.2k
Token cost
~3.4k tokens
SKILL.md length
1,676 words
Files
16 (incl. scripts)
Skills in repo
273
Repo updated
First seen
Licence
MIT

At a glance

Stitch video segments with ffmpeg concat, xfade, overlay, audio mux, and export settings, and trim a source into named clips at exact windows (trimclips.py).

  • Works in 5 steps: Read the brief and confirm all required… → Load any referenced files in this skill… → Run the provider, script, or planning… → …
  • Tasks that involve Video production
  • SKILL.md covers Purpose, Montage helper:…, Trim mode: scripts/trim_clips.py and FFmpeg notes, plus 5 more sections
  • Runs Python and Shell scripts from its folder; calls python3

What it does

Stitch Videos Ffmpeg is an agent skill from gooseworks-ai/goose-skills. Stitch video segments with ffmpeg concat, xfade, overlay, audio mux, and export settings, and trim a source into named clips at exact windows (trimclips.py). Ships montage.py, a free montage assembler (python3 + ffmpeg, no keys). It takes a JSON EDL of clips and stills, normalizes them and hard-cuts them in order, burns captions from an SRT, a cue list or word timings, and lays a VO over a music bed that ducks under it, mastered to -14 LUFS.

Its SKILL.md is about 3.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 18 other files, including scripts (for example `scripts/composite.py`, `scripts/composite_final.py` and `scripts/composite_final.sh`).

It sits in Media & Creative, covering Video production. It works with FFmpeg and Python. The repository describes itself as: Library of Growth & GTM skills + data APIs for Claude Code, Codex, Cursor to run ads, social, content, lead gen, seo and data scraping. The licence is MIT.

When your agent uses it

  • Tasks that involve Video production

Example prompts

  • “/stitch-videos-ffmpeg”

Requirements

  • Python 3
  • A Bash shell

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  1. Read the brief and confirm all required inputs are present.
  2. Load any referenced files in this skill folder only when they are needed.
  3. Run the provider, script, or planning workflow described by this skill.
  4. Save outputs under the requested output folder or skills/test-runs/// during tests.
  5. Write or update a manifest.json for executable runs with status, provider, outputs, warnings, and errors.

What it can do on your machine

Read from SKILL.md and the folder at commit c650c6d. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 7 files in scripts/ (Python and Shell), which the agent can run.

    Shell commands in SKILL.md call:

    • python3

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Stitch Videos Ffmpeg loads about 3.4k tokens when it runs. Until then it costs about 117 tokens; SKILL.md has 1,676 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~117
When it runs · the whole SKILL.md, loaded when a task matches
~3.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from gooseworks-ai/goose-skills at commit c650c6d, republished under its MIT licence (© gooseworks-ai). 1,676 words, ~3,410 tokens.

Download SKILL.mdSave it as .claude/skills/stitch-videos-ffmpeg/SKILL.md (or your agent's skills folder). This skill also uses 15 other files; get the full folder from GitHub.
name
stitch-videos-ffmpeg
description
Stitch video segments with ffmpeg concat, xfade, overlay, audio mux, and export settings, and trim a source into named clips at exact windows (trim_clips.py). Ships montage.py, a free montage assembler (python3 + ffmpeg, no keys). It takes a JSON EDL of clips and stills, normalizes them and hard-cuts them in order, burns captions from an SRT, a cue list or word timings, and lays a VO over a music bed that ducks under it, mastered to -14 LUFS.
version
1.3.0
updated
2026-10-06

stitch-videos-ffmpeg

Purpose

Stitch video segments with ffmpeg concat, xfade, overlay, audio mux, and export settings.

Implementation status: refactored from existing repository skills. The workflow consolidates behavior that previously lived across larger skills.

Sources: ad-studio, voiceover-product-ad, ugc-product-video, voiceless-music-transformation-reel, product-stopmotion-ad.

Extraction notes: assembly and composite scripts.

Montage helper: scripts/montage.py

A free, deterministic way to cut a montage ad from finished clips. It needs python3 and ffmpeg/ffprobe only (Pillow is optional, see Captions). It makes no network or provider calls and needs no keys, so re-cuts cost nothing.

StepWhat it does
edlChecks a JSON spec and writes edl.json. Every file must exist and is probed with ffprobe; every cut must fit inside its clip. All problems are listed at once.
assembleScales each cut to one size (default 1080×1920, cover crops to fill, contain pads), one frame rate (default 30), square pixels and yuv420p. Then it hard-cuts them in order with the filter_complex concat filter, never the -f concat demuxer. Each cut gets an exact frame count, so the output length equals the EDL total.
captionsBurns an SRT, a JSON cue list, or word timings (one cue per --per words) into the video. The cue text is kept exactly as given (wrapping only turns spaces into line breaks).
mixLays the VO over the video and adds an optional music bed that ducks under the VO (sidechain compression, 20:1). Then it masters to -14 LUFS / -1 dBTP with two-pass loudnorm.
runRuns all four steps from one spec and writes manifest.json.

Each step prints a one-line JSON summary. Exit codes: 0 ok, 1 ffmpeg failed, 2 bad spec or arguments, 3 a tool is missing (ffmpeg, ffprobe, or a caption renderer).

Run it

After gooseworks fetch stitch-videos-ffmpeg (or as a dependency of a format package), the scripts are in /tmp/gooseworks-scripts/stitch-videos-ffmpeg/scripts/:

bash
S=/tmp/gooseworks-scripts/stitch-videos-ffmpeg/scripts   # or this folder's scripts/ in a checkout

python3 $S/montage.py run --spec montage.json --out edits/master.mp4 --workdir edits/work

# or one step at a time
python3 $S/montage.py edl      --spec montage.json --out edits/edl.json
python3 $S/montage.py assemble --edl edits/edl.json --out edits/body.mp4
python3 $S/montage.py captions --video edits/body.mp4 --words audio/vo.words.json \
    --respell '{"symbiotic": "synbiotic"}' --color "#FFE800" --out edits/captioned.mp4
python3 $S/montage.py mix      --video edits/captioned.mp4 --vo audio/vo.mp3 \
    --music audio/bed.mp3 --out edits/master.mp4
Spec format

Paths are relative to the spec file. Times are seconds or a timecode string ("SS", "MM:SS", "HH:MM:SS", optional .ms).

json
{
  "output": {"width": 1080, "height": 1920, "fps": 30, "fit": "cover"},
  "words": "audio/vo.words.json",
  "clips": [
    {"file": "clips/scene-01.mp4", "label": "hook", "word_range": [0, 4]},
    {"file": "clips/scene-02.mp4", "label": "feature", "in": 0.2, "out": 1.6},
    {"file": "clips/scene-03.mp4", "label": "reaction", "in": "00:00.5", "duration": 0.9},
    {"file": "clips/scene-04.mp4", "label": "b-roll", "t_in": 4.1, "t_out": 5.0},
    {"file": "clips/scene-05.mp4"},
    {"file": "overlays/landing-page.png", "label": "landing-page", "duration": 1.5,
     "pan": {"from": {"x": 0.5, "y": 0.2, "zoom": 1.0}, "to": {"x": 0.5, "y": 0.7, "zoom": 1.6}}},
    {"file": "brand/end-card.png", "label": "end-card", "duration": 2.0}
  ],
  "clip_audio": "drop",
  "captions": {"words": "audio/vo.words.json", "per": 1, "respell": {"symbiotic": "synbiotic"},
               "style": {"color": "#FFE800", "y": 0.5}},
  "audio": {"vo": "audio/vo.mp3", "music": "audio/bed.mp3", "music_start": 14.2}
}

How long each cut is (first match wins):

  • word_range: [i, j] cuts on the VO's word boundaries. It needs a top-level words file, used as the transcriber wrote it: a flat [{text|word, start, end}] list, {words: [...]} (OpenAI, ElevenLabs; spacing entries are skipped), Whisper's {segments: [{words: [...]}]} (goose-studio's transcribe-audio-fal), or fal's {chunks: [{text, timestamp: [s, e]}]}. Words with no time are skipped, and leading spaces are stripped. The cut runs from the start of word i to the start of word j + 1, or to the last word's end. The first cut starts at 0 so it covers the lead-in. Consecutive ranges tile the VO with no gaps.
  • t_in / t_out give a window on the timeline. The cut is t_out - t_in long. A window that does not start where the previous cut ended is reported as a gap or overlap warning; --strict turns warnings into errors.
  • in + out, or in + duration, trim the source clip.
  • With nothing set, the whole clip plays (from in, default 0).

Every cut starts at in in its source (default 0). A still image (.png, .jpg, .webp) needs a length; pan zooms and pans across it. The still is first cover-cropped to the output aspect (9:16 by default), and x/y are the window centre as a fraction of that cropped image (zoom ≥ 1). A video clip may be up to 0.1 s short of its cut, and then its last frame is held. Anything shorter is an error.

clip_audio (--clip-audio on assemble): drop (default) or keep. keep keeps each clip's own sound and fills silence under stills and silent clips.

Captions
  • Sources: srt, cues (a list or a JSON file of {start, end, text}), or words (any of the word-file shapes above) plus per and an optional respell map. respell swaps a misheard word for the locked spelling and keeps the punctuation around it. Overlapping cues: the later one wins.
  • Look: each cue is drawn whole, in one colour with an outline. With per: 1 that is one word at a time, each held until the next. There is no active-word (karaoke) highlight.
  • Timing: a cue shows from the first output frame at or after its start until the first frame at or after its end (a 1 ms caption grid; ffmpeg older than 5 falls back to 1/25 s and says so in the step's warnings).
  • Style: font, font_size (px, default 4.5% of the height), color, outline_color, outline (px), y (centre of the caption block as a fraction of the height, default 0.72) and max_width (default 0.86 of the width).
  • Renderers: auto uses Pillow when it is installed, so captions look the same on every machine. Otherwise it uses libass, which needs an ffmpeg with the ass filter. Some ffmpeg builds (Homebrew's default) have no libass and no drawtext, so Pillow is the dependable renderer. With neither, the step exits 3 and says so.
Mix defaults (all overridable)
SettingDefaultMeaning
vo_lufs-16VO level before mixing (static gain from a measured pass)
music_lufs-24Bed level between VO lines, before ducking
duck_threshold / duck_ratio0.02 / 20The bed ducks while the VO is above the threshold. ffmpeg caps the ratio at 20.
duck_attack / duck_release20 / 400 msHow fast the bed dips and comes back
vo_start, music_start0Where each track enters on the timeline. vo_start moves only the VO audio, not word_range cuts or word captions, so keep it 0 when those come from the same VO.
music_fade_in / music_fade_out0 / 1 sA bed shorter than the video loops (with a warning)
target_lufs / target_tp-14 / -1Master loudness. off skips it.
keep_video_audiofalseMix the video's own audio in too (not ducked)

A VO that runs past the end of the video is cut and reported as a warning, so lengthen the EDL (for example, the end card) instead.

Tests

tests/test_stitch_montage.py makes tiny synthetic clips, a still and two tones with ffmpeg, then checks: the output length equals the EDL total to the frame, size/fps/pixel shape are normalized, captions appear only on their cue frames with the exact text, the bed ducks under the VO (about 14 dB on the fixture), and the master is at -14 ±1 LUFS. It runs in CI (media-tests) and locally:

bash
python3 -m pytest -q skills/ads/packs/video-ad-formats/stitch-videos-ffmpeg/tests
Show full SKILL.md (654 more words)Show less
  • The older scripts here (composite.py, composite_final.py / .sh, normalize_clip.sh, voiceless/composite.py) are unchanged.
  • mix-master remains the multi-clip VO + SFX mix. A montage.py master is already at -14 LUFS, so a later -14 LUFS finishing pass barely changes it.
  • caption-burn remains the place for plate, seam and hook-card caption styles.

Trim mode: scripts/trim_clips.py

Cuts one source video into named clips at exact windows (this replaces the studio's trim-video-clips). Each clip is re-encoded with libx264, so cuts land on the requested frames and drop cleanly into an edit. Deciding which windows to cut is the caller's job.

bash
python3 scripts/trim_clips.py --source source.mp4 --clips clips.json --output-dir clips/ [--crf 18] [--overwrite]

clips.json is a list of {name, start, end} or {name, start, duration}; times are seconds or SS, MM:SS, HH:MM:SS with optional .ms:

json
[
  {"name": "hook-laptop-close", "start": 0, "end": 2.6},
  {"name": "mac-mini-glow", "start": "00:03", "duration": 5}
]
  • One <slug>.mp4 per clip, and manifest.json with each clip's window, real duration and status.
  • A bad spec (no end or duration, a window that ends before it starts) is skipped and listed in errors; the other clips still cut. A window that runs past the end of the source gives a shorter clip and a warning with both lengths.
  • Re-runs skip clips that already exist unless --overwrite. A source with no audio gives clips with no audio.

FFmpeg notes

Measured traps when joining and finishing. Each lives here once.

  • Joined generated clips drift in colour at every cut, even from one prompt. Apply one harmonising grade over the whole joined video; eq=contrast=1.05:saturation=0.95,colorbalance=bs=0.05:bm=-0.02 is a starting point.
  • A still PNG overlay with a fade does nothing unless the input is looped: -loop 1 -framerate 30 -t <length> before that -i. The build reports no error.
  • ffmpeg 9 removed -vsync. The old flag fails the whole command; use -fps_mode, or drop it (-update 1 alone overwrites frame by frame).
  • -ss before -i can land on a keyframe (always with stream copy). A re-encoded cut is exact; a measurement a decision depends on puts -ss after -i or decodes the range.
  • crop rounds offsets to whole pixels, so a gentle sine move becomes a still with one-pixel snaps. Scale up 4x, crop, scale back. Judge motion on the median, not the p90.
  • select then tile takes consecutive frames. Seek with -ss before the input, then fps=N, then tile.
  • A trailing comma in filter_complex fails the build silently behind a captured subprocess, and an older render on disk then passes the checks. Strip trailing commas and read the build's own exit status.
  • Generated video is already sharp. A finishing sharpen adds the artefact it means to hide; keep unsharp near 0.12 with no grain, and measure before assuming footage is soft.

Inputs

  • A clear user brief or source asset path.
  • Brand, product, audience, platform, and approval constraints when relevant.
  • Required credentials or provider access for any external service used by this skill.
  • Output directory or test-run directory where artifacts should be saved.

Workflow

  1. Read the brief and confirm all required inputs are present.
  2. Load any referenced files in this skill folder only when they are needed.
  3. Run the provider, script, or planning workflow described by this skill.
  4. Save outputs under the requested output folder or skills/test-runs/<timestamp>/<skill-name>/ during tests.
  5. Write or update a manifest.json for executable runs with status, provider, outputs, warnings, and errors.

Output

  • Primary artifact or written plan requested by the skill.
  • manifest.json for executable runs.
  • verification.md or a short verification summary that names the checks performed.
  • Any generated source assets, intermediate files, or final exports in the run folder.

Quality Checks

  • Required files exist and paths in the manifest are valid.
  • Output matches the requested format, platform, duration, dimensions, or text structure.
  • Brand claims, captions, on-screen text, and CTAs follow the provided brand rules.
  • Provider failures, skipped integrations, and human-review needs are explicit.

Failure Modes

  • Missing credentials, provider access, or source files.
  • Output does not match requested dimensions, duration, structure, or brand constraints.
  • Generated media contains artifacts, unreadable text, unsafe claims, or caption collisions.
  • Scaffolded skills cannot run production workflows until implementation details are added.

© gooseworks-ai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 15 other files (scripts) in skills/ads/packs/video-ad-formats/stitch-videos-ffmpeg of gooseworks-ai/goose-skills.

  • SKILL.md
  • scripts/composite.py
  • scripts/composite_final.py
  • scripts/composite_final.sh
  • scripts/montage.py
  • scripts/normalize_clip.sh
  • scripts/trim_clips.py
  • scripts/voiceless/composite.py
  • skill.meta.json
  • tests/expected-output.md
  • tests/human-test.md
  • tests/sample-input.md
  • tests/smoke-test.md
  • tests/test_stitch_montage.py
  • tests/test_trim_clips.py
  • tests/verifier.md

Open the folder on GitHubat commit c650c6d

Compare with similar skills

Stitch Videos Ffmpeg next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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Ffmpeg Skillkajisho5/ffmpeg-skill1.9k—~7.4kAutomated safety check: PassMIT
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Whiteboard Videognipbao/codex-whiteboard-video-skill327—~7.2kAutomated safety check: NotesMIT

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Works with

Questions about Stitch Videos Ffmpeg

What does Stitch Videos Ffmpeg do?

Stitch video segments with ffmpeg concat, xfade, overlay, audio mux, and export settings, and trim a source into named clips at exact windows (trimclips.py). Stitch Videos Ffmpeg is an agent skill from gooseworks-ai/goose-skills.py).

When should I use Stitch Videos Ffmpeg?

Stitch Videos Ffmpeg fits situations like: tasks that involve Video production.

How do I install Stitch Videos Ffmpeg in Claude Code?

Run `npx skills add gooseworks-ai/goose-skills --skill stitch-videos-ffmpeg -a claude-code`. Or copy the skill folder (skills/ads/packs/video-ad-formats/stitch-videos-ffmpeg in gooseworks-ai/goose-skills) into .claude/skills/stitch-videos-ffmpeg in your project. Claude Code loads it when a task matches its description.

How do I install Stitch Videos Ffmpeg in Codex?

Run `npx skills add gooseworks-ai/goose-skills --skill stitch-videos-ffmpeg -a codex`. Or copy the skill folder (skills/ads/packs/video-ad-formats/stitch-videos-ffmpeg in gooseworks-ai/goose-skills) into .agents/skills/stitch-videos-ffmpeg in your project. Codex loads it when a task matches its description.

Can I use Stitch Videos Ffmpeg in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add gooseworks-ai/goose-skills --skill stitch-videos-ffmpeg -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/stitch-videos-ffmpeg, .gemini/skills/stitch-videos-ffmpeg, .github/skills/stitch-videos-ffmpeg and .opencode/skills/stitch-videos-ffmpeg in your project.

What does Stitch Videos Ffmpeg need to run?

Going by SKILL.md and its folder, Stitch Videos Ffmpeg needs Python and a shell for the scripts in its folder and the command-line tools its instructions call (python3). Our summary lists: Python 3; A Bash shell.

Does Stitch Videos Ffmpeg access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Stitch Videos Ffmpeg safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Stitch Videos Ffmpeg use?

Stitch Videos Ffmpeg is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Stitch Videos Ffmpeg use?

About 3.4k tokens (SKILL.md is roughly 14k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Stitch Videos Ffmpeg?

Skills that share tags, products or a category with Stitch Videos Ffmpeg: Vox Director (Alisa0808/vox-director, 2.2k stars), Ffmpeg Skill (kajisho5/ffmpeg-skill, 1.9k stars), OpenStoryline Install Helper (FireRedTeam/FireRed-OpenStoryline, 3.5k stars) and Cassette Video Edit (Cassette-Editor/oh-my-cassette, 119 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Stitch Videos Ffmpeg?

gooseworks-ai (a GitHub organization) maintains it in gooseworks-ai/goose-skills, which has 1,240 GitHub stars. The repository holds 273 skills in this directory. The repository was last updated on October 8, 2026.

Source: gooseworks-ai/goose-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.