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.
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 gooseworks-ai/goose-skills --skill ugc-fixloopgit clone --depth 1 https://github.com/gooseworks-ai/goose-skillsWrote 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/gooseworks-ai/goose-skills/ugc-fixloop)<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.
<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>- NVIDIA SkillSpector warn
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.
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 | $0.00091 | $0.00911 |
| Opus 5 | $0.00046 | $0.00456 |
| Sonnet 5 | $0.00018 | $0.00182 |
| Haiku 4.5 | $0.00009 | $0.00091 |
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.
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 — 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 directfal.runcall.
Env / deps
stitch_replacement.py— no API key, no network. Needsffmpeg+ffprobeon 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 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 viacreate-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, default0.3) — scene-cut sensitivity for--replace-beat.--fit {stretch,trim,freeze}(defaultstretch) — reconcile replacement length to the hole.--dry-run— print the ffmpeg command without running.
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.
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.
- 12d ago First seen · 56 lines · 91 tokens per session scan A 0cf6faff5073
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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