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ugc-fixloop

the UGC fix-loop toolkit — surgically re-render a bad window/beat of a single-take UGC master (stitch_replacement.py, pure FFmpeg) and GPT cross-model review a Seedance prompt before render (vet_seedance_prompt.py, routed through the openai-proxy).

Install / Use

npx skills add gooseworks-ai/goose-skills --skill ugc-fixloop

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

85/100

Supported Platforms

Universal

Our assessment of ugc-fixloop

ugc-fixloop scores 85/100 on our quality scale, 592nd of 952 AI & Machine Learning skills we index.

Its SKILL.md is 3.4 KB long, split into 6 sections with 2 code examples: a solid amount of guidance for an agent.

With 1,222 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
26/30
Structure
16/20
Description
15/15
Adoption
13/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 33 days ago, so ugc-fixloop is actively maintained.
  • Our last check on 2026-10-12 found the source still online.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

ugc-fixloop compared with similar skills

All 4 of these similar skills score higher than ugc-fixloop; compare them before choosing.

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Frequently asked questions

How do I install ugc-fixloop?
Run npx skills add gooseworks-ai/goose-skills --skill ugc-fixloop. The install tabs above show the steps for each supported agent.
Which AI agents does ugc-fixloop work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is ugc-fixloop safe to use?
It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is ugc-fixloop still maintained?
The repository was last updated 33 days ago, so ugc-fixloop is actively maintained.

name: ugc-fixloop description: the UGC fix-loop toolkit — surgically re-render a bad window/beat of a single-take UGC master (stitch_replacement.py, pure FFmpeg) and GPT cross-model review a Seedance prompt before render (vet_seedance_prompt.py, routed through the openai-proxy). Fetch it into a one-shot UGC recipe so both scripts resolve on any machine and the vet call charged to your GooseWorks credits. status: active

ugc-fixloop

The UGC fix-loop toolkit. The one-shot UGC video recipes (create-ugc-*-video-from-refs) render a single continuous Seedance 2.0 reference-to-video master with native lip-synced audio. This capability ships the two scripts those recipes run, so they exist on the remote machine (fetched into /tmp/gooseworks-scripts/ugc-fixloop/).

Any re-render of a replacement clip goes through the same proxy path the recipe uses for the take (create-video-fal / fal-proxy), NEVER a direct fal.run call.

Env / deps

  • stitch_replacement.py — no API key, no network. Needs ffmpeg + ffprobe on PATH (all local FFmpeg).
  • vet_seedance_prompt.py — routes through the GooseWorks openai-proxy (<api_base>/api/internal/openai-proxy/v1/chat/completions), reading creds from ~/.gooseworks/credentials.json — no direct OpenAI call, no local key; the call charged to your GooseWorks credits. Exits 3 if the proxy/creds are unavailable so the recipe can fall back to an inline self-review (the vet is advisory, not a gate).

Run — vet_seedance_prompt.py (GPT cross-model prompt review)

A second opinion from a different model family on the Seedance prompt before you spend the render (a model reviewing its own prompt is a weaker signal). Takes the prompt as an argument:

vet_seedance_prompt.py --prompt-file working/seedance-prompt.txt \
    [--brief "one-line intent"] [--refs "@Image1=avatar; @Image2=product; @Image3=env"] \
    [--words 28] [--out working/seedance-review.md]

Prints + saves the structured review (verdict, line edits, word budget, consistency risk).

Run — stitch_replacement.py (surgical beat/window swap, deterministic)

Replaces one segment of the master on the VIDEO track only; the master's audio (VO + ambience) plays straight through, so lip-sync on talking beats is never touched. Output is re-encoded H.264 / yuv420p at the master's fps + resolution.

Required: --master M.mp4 --replacement R.mp4 --output O.mp4. Pick the window ONE of two ways:

# By beat (1-indexed segment between auto-detected scene cuts):
stitch_replacement.py --master M.mp4 --replacement R.mp4 --output O.mp4 --replace-beat 2

# By explicit window (seconds):
stitch_replacement.py --master M.mp4 --replacement R.mp4 --output O.mp4 \
    --window-start 4.21 --window-end 8.75 --fit stretch

All args:

  • --master (required) — the single-take master mp4.
  • --replacement (required) — the re-rendered silent replacement clip (generated via create-video-fal).
  • --output (required) — output mp4 path.
  • --window-start / --window-end (float seconds) — explicit hole to replace.
  • --replace-beat (int, 1-indexed) — pick the segment between detected scene cuts.
  • --scene-threshold (float, default 0.3) — scene-cut sensitivity for --replace-beat.
  • --fit {stretch,trim,freeze} (default stretch) — reconcile replacement length to the hole.
  • --dry-run — print the ffmpeg command without running.

Warns if output duration drifts >0.15s from the master (audio-sync check).

Related Skills

View on GitHub
GitHub Stars1.2k
CategoryAI
Updated1mo ago
Forks208

Languages

Python

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions