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 footage-cutlistgit 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/footage-cutlist)<a href="https://agentmods.dev/skills/gooseworks-ai/goose-skills/footage-cutlist"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/footage-cutlist/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/footage-cutlist"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/footage-cutlist.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00178 | $0.02141 |
| Opus 5.5 | $0.00071 | $0.00856 |
| Sonnet 5.5 | $0.00036 | $0.00428 |
| Haiku 4.5 | $0.00018 | $0.00214 |
Grade A, and why
footage-cutlist 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 5d 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 — 120 lines — stays where its author put it; the contents beside it link to each section on GitHub.
footage-cutlist
Picking which moment of a customer's footage plays under which line is a judgement, not a formula. A position map ("beat 3 is 40% through the reel, so take the footage 40% through") was measured up to 5.7s off a person's picks on a reference build. So this capability does the free, mechanical parts and leaves the decision to the agent and the user:
| Step | Script | Who decides |
|---|---|---|
| Look at the footage | survey.py |
nobody; it just shows it |
| Choose a window per line | the agent writes cutlist.json |
agent, then the user |
| Show the choices | preview.py |
the user corrects them |
| Render the approved choices | cut.py |
nobody |
All free. ffmpeg + Pillow + numpy only.
Run
python survey.py --video footage.mp4 --out work/survey # whole clip, ~1 frame/s
python survey.py --video footage.mp4 --out work/s-12 --from 12 --to 18 --every 0.25 --frames
python preview.py --cutlist work/cutlist.json --out work/review.png
python cut.py --cutlist work/cutlist.json --out work/layer.mp4 [--draft]
survey.json lists cuts (scene changes), motion (change per second) and still
(runs of 1.5s+ with nothing moving: a dead screen reads as a frozen video). Read the
sheets; open a single frame-*.png (from --frames) when you need to read small UI text.
The cut list
{
"size": [1080, 1920], "fps": 30, "seam": 768, "creator_side": "bottom", "bg": "auto",
"sources": {"demo": "footage/demo.mp4"},
"beats": [
{"id": "b1", "start": 0.0, "end": 3.1, "state": "creator", "vo": "..."},
{"id": "b2", "start": 3.1, "end": 7.4, "state": "split", "vo": "...",
"source": "demo", "in": 12.0, "out": 16.3, "fit": "width", "why": "the brand kit fills in at 13.4s"}
]
}
state:creator(creator full frame),split(footage in the product zone, creator in the other),product(footage full frame).inis where the window starts in the source;outdefaults toin + slot(1.0x). A window may play between 0.5x and 2x; it is never looped or frozen to fill a slot.fit:width(whole frame, letterboxed; the default),cover(fill + crop aroundfocus),crop(a source box[x0,y0,x1,y1]in fractions, then fit by width).bg:autosamples the footage's own corner colour so the letterbox and the footage read as one surface;blur; or#rrggbb.look: "screen": frame the footage as a screen filmed at close range (thin bezel, dark room, faint moire, grain, slow handheld drift).croppicks the source region,screen: {rot, keystone, fill, fit, drift}the geometry,maskboxes are blurred in the source (an email, a customer name). Inserts over a creator:keystone ~0.007,rotwithin ±1°. Walkthroughs:keystone ~0.024,rot-1.5..0,fill ~0.80. Never bigger angles and never alternate them between beats (read as a wonky camera).transition: {"dissolve_frames": 7}(top level): cross-dissolve every beat into the next. A hard cut between two screens reads as an edit; 6-7 frames reads as the camera moving.- A source can be a still image (png/jpg/webp): it holds for its slot. Give it
look: "screen"so the drift keeps it alive. why: one line on what the window shows. It is printed on the review sheet so the user can see the reasoning, and it makes the agent say what it saw.
What ships with it
9 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.
- 5d ago Changed · +1 lines 857fcd3da9b7
- 11d ago Changed · +6 lines 5d6c38fbe379
- 19d ago First seen · 113 lines · 178 tokens per session scan A 3f62fefd3961
footage-cutlist is a skill published in the GitHub repository gooseworks-ai/goose-skills (1,254 stars, last pushed today), licensed MIT. It adds 178 tokens to every session and 2,141 once invoked, about $0.0007 per session on Opus 5.5. 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 2026-09-29.
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