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 render-creator-pip-listiclegit 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/render-creator-pip-listicle)<a href="https://agentmods.dev/skills/gooseworks-ai/goose-skills/render-creator-pip-listicle"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/render-creator-pip-listicle/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/render-creator-pip-listicle"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/render-creator-pip-listicle.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 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 Memory Poisoning · line 3 Skill attempts to fill the context window with filler content, displacing legitimate instructions and safety constraints. This can degrade agent performance or bypass safety boundaries.Fix: Implement context-window management that detects and rejects padding or stuffing attempts. Prioritize system instructions over user-injected content.
- medium Memory Poisoning · line 15 Skill attempts to fill the context window with filler content, displacing legitimate instructions and safety constraints. This can degrade agent performance or bypass safety boundaries.Fix: Implement context-window management that detects and rejects padding or stuffing attempts. Prioritize system instructions over user-injected content.
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 | $0.00313 | $0.02137 |
| Opus 5 | $0.00156 | $0.01069 |
| Sonnet 5 | $0.00063 | $0.00427 |
| Haiku 4.5 | $0.00031 | $0.00214 |
Grade A, and why
render-creator-pip-listicle 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 13d 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 — 93 lines — stays where its author put it; the contents beside it link to each section on GitHub.
render-creator-pip-listicle
Assemble a creator picture-in-picture product listicle ad from a config: an AI creator counts down N products in the brand's own voice, and the creator stays FULL-FRAME the whole time — there is NO cut to a full-frame product shot, ever. On each product beat, three persistent overlays ride on top of the full-frame creator for the WHOLE beat: (1) a title pill top-center (persistent, it carries the listicle title), (2) the DEMO in a rounded PiP window top-right — the brand's real UGC clip (MUTED), or for a no-UGC brand the product's own demo (a real screen-recording, or an autocropped high-res product-UI/dashboard still sized to fill the window), and (3) a product card pinned bottom (rounded thumbnail left + "N · CATEGORY" small-caps + product NAME in a serif face like Georgia). Hook + CTA beats are the creator full-frame with the title pill only (no PiP/card). The creator's voice + lips are generated together, natively per beat — there is no separate voiceover. This capability is the FREE, deterministic assembly — build the per-beat overlay PNG, cover-scale the creator clip + composite the overlay, concat all beats, and burn the captions.
scripts/config.example.json is the worked example (DIBS Beauty "5 products that replaced my whole
makeup bag", ~46s 1080×1920 9:16, a hook + 5 product beats + a CTA); scripts/PIPELINE.md maps
every config block to its source step and scripts/README.md documents the free assembly.
Run
This is the FREE, deterministic assembly stage — it spends nothing beyond the caption burn. The
paid inputs are separate capabilities — the creator anchor (create-image-fal, Seedream v5 Pro,
model bytedance/seedream/v5/pro/text-to-image with no fal-ai/ prefix) and one native Seedance
talking clip per beat (create-video-fal, model bytedance/seedance-2.0/reference-to-video,
generate_audio=ON, the SAME seed across beats so the face holds, 720p default). Given those native
clips + the brand's real UGC demo clips (or the product's own autocropped UI stills / screen
recordings) + the real product photos + the brand palette + the title copy,
render-creator-pip-listicle builds ONE full-1080×1920 transparent overlay PNG per beat (title pill
always; + demo PiP top-right + bottom product card + rank number on product beats), cover-scales the
creator clip to 1080×1920 and overlays the beat's overlay PNG for the whole beat while keeping the
native audio, concats all beats, and burns the captions last → the master. Re-cuts reuse the existing
native clips + overlays and cost $0.
What ships with it
5 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.
- 13d ago First seen · 93 lines · 313 tokens per session scan A c978fea64ef6
render-creator-pip-listicle is a skill published in the GitHub repository gooseworks-ai/goose-skills (1,202 stars, last pushed 11d ago), licensed MIT. It adds 313 tokens to every session and 2,137 once invoked, about $0.0016 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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