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 video-polishgit 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/video-polish)<a href="https://agentmods.dev/skills/gooseworks-ai/goose-skills/video-polish"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/video-polish/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/video-polish"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/video-polish.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 8 findings, up to medium
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 →
- medium Output Handling · line 29 Output size or generation rate is not bounded. Unbounded output enables denial-of-service through resource exhaustion, log flooding, or context-window stuffing.Fix: Set explicit limits on output length, generation count, and rate. Use max_tokens and truncation to prevent unbounded output.
- medium MCP Rug Pull · line 39 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 360 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 59 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 70 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 92 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 170 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 297 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
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 | $0.00044 | $0.03778 |
| Opus 5 | $0.00022 | $0.01889 |
| Sonnet 5 | $0.00009 | $0.00756 |
| Haiku 4.5 | $0.00004 | $0.00378 |
Grade A, and why
video-polish scanned grade A with 1 finding 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 9d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -L -o /tmp/ggml-base.en.bin "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-base.en.bin" How it starts
The opening of the file, as written. The whole thing — 365 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Video Polish Skill
You take an existing video (screen recording, demo, walkthrough, Loom) and add professional zoom/pan effects that follow the narration. The output looks like a professionally edited video where the camera zooms into whatever the speaker is discussing.
What This Skill Does
Input: A raw video file (screen recording, Loom, product demo) + optionally a soundtrack Output: The same video with smooth zoom/pan effects synchronized to the narration
What it adds:
- Zoom-in effects on UI elements, metrics, text, code when the narrator mentions them
- Smooth pan/slide effects across sections (e.g., sliding across table columns)
- Transitions with ease-in-out easing (no jarring jumps)
- Optional audio replacement (background music instead of or mixed with original narration)
What it does NOT do:
- Generate new video content
- Add avatars or talking heads
- Edit or cut the video (no trimming, no removing sections)
- Add text overlays or annotations
Prerequisites
- Node.js (v18+) and npm — required for Remotion
- Remotion — Video rendering framework. If not already set up, create a project:
npx create-video@latest --yes --blank --no-tailwind video-polish cd video-polish && npm i - whisper-cpp — For audio transcription. Install via
brew install whisper-cppon macOS - Whisper model — Download the base English model:
curl -L -o /tmp/ggml-base.en.bin "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-base.en.bin" - Python 3 + Pillow — For frame extraction and coordinate grid overlays (
pip install Pillow)
Before starting: Verify that Node.js, whisper-cpp, and Python 3 with Pillow are installed. If any are missing, instruct the user to install them before proceeding.
How This Skill Works
Step 1: Analyze the Source Video
Get video metadata:
npx remotion ffprobe -v quiet -print_format json -show_format -show_streams <video_path>
What ships with it
1 file 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.
- 9d ago First seen · 365 lines · 44 tokens per session scan A 41217addc068
video-polish is a skill published in the GitHub repository gooseworks-ai/goose-skills (1,202 stars, last pushed 11d ago), licensed MIT. It adds 44 tokens to every session and 3,778 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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