ugc-fixloop

ugc-fixloop is a skill for Claude Code, Codex from gooseworks-ai/goose-skills. It costs 91 tokens per session (911 once invoked), scanned A, original, MIT.

A toolkit for repairing UGC videos, meaning user-generated videos, by reviewing prompts and stitching replacement clips into an existing result. Its recipes use Seedance 2.0 to create continuous reference-based videos with automatically synchronized speech.

In plain words
What is it for?
Use it to review Seedance prompts and stitch replacement video clips with FFmpeg. It is intended for UGC video fix loops and requires the stated local video tools for stitching.
Why use it?
It provides a repeatable path for replacing a faulty clip while keeping the render workflow consistent. Local stitching avoids an extra service, while prompt review can catch issues before another render.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to review Seedance prompts and stitch replacement video clips with FFmpeg. It is intended for UGC video fix loops and requires the stated local video tools for stitching.

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Install with agentmods
npx agentmods add skills/gooseworks-ai/goose-skills/ugc-fixloop
About the project

Goose Skills is a library of workflows and data APIs that lets coding agents handle growth and go-to-market work such as advertising, social media, content, SEO, lead generation, and customer research. It is intended for teams using Claude Code, Cursor, Codex, and similar agents. The catalogue entries are its reusable skills.

gooseworks-ai/goose-skills · 1,202 stars · on GitHub · gooseworks.ai

Install

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.

Any agent
npx skills add gooseworks-ai/goose-skills --skill ugc-fixloop
Clone the repo
git clone --depth 1 https://github.com/gooseworks-ai/goose-skills

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for ugc-fixloop

README.md
[![agentmods](https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/ugc-fixloop/github.svg)](https://agentmods.dev/skills/gooseworks-ai/goose-skills/ugc-fixloop)
Your own site
<a href="https://agentmods.dev/skills/gooseworks-ai/goose-skills/ugc-fixloop"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/ugc-fixloop/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.

agentmods 80×15 button for ugc-fixloop

Your own site · 80×15
<a href="https://agentmods.dev/skills/gooseworks-ai/goose-skills/ugc-fixloop"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/ugc-fixloop.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 91 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 911 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, up to high

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • high Privilege Escalation · line 19
    Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.
    Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00091 $0.00911
Opus 5 $0.00046 $0.00456
Sonnet 5 $0.00018 $0.00182
Haiku 4.5 $0.00009 $0.00091

Measured 12d ago against content hash 0cf6faff5073, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

ugc-fixloop 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 12d ago.

The scan reads SKILL.md. This mod also ships 2 executable files (scripts/stitch_replacement.py, scripts/vet_seedance_prompt.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

skills/ads/capabilities/ugc-fixloop/SKILL.md · 56 lines

How it starts

The opening of the file, as written. The whole thing — 56 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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.jsonno direct OpenAI call, no local key; the call bills the Ads agent. 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 deliberately NON-Claude second opinion on the Seedance prompt before you spend the render (Claude 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.

Read the full file on GitHub · 56 lines

Files

What ships with it

4 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.

Changes

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.

  1. 12d ago First seen · 56 lines · 91 tokens per session scan A 0cf6faff5073

Subscribe to this mod's changes

ugc-fixloop is a skill published in the GitHub repository gooseworks-ai/goose-skills (1,202 stars, last pushed 11d ago), licensed MIT. It adds 91 tokens to every session and 911 once invoked, about $0.0005 per session on Opus 5. 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 2026-08-30.

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