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-ig-live-gallerygit 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-ig-live-gallery)<a href="https://agentmods.dev/skills/gooseworks-ai/goose-skills/render-ig-live-gallery"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/render-ig-live-gallery/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-ig-live-gallery"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/render-ig-live-gallery.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00141 | $0.00823 |
| Opus 5 | $0.00071 | $0.00411 |
| Sonnet 5 | $0.00028 | $0.00165 |
| Haiku 4.5 | $0.00014 | $0.00082 |
Grade A, and why
render-ig-live-gallery 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 — 55 lines — stays where its author put it; the contents beside it link to each section on GitHub.
render-ig-live-gallery
Render the ig-live-gallery format from a config. Each of the brand's REAL hero product stills is presented as the "live video" inside an authentic Instagram-Live card — dark gradient scrims top & bottom over the bright product, an IG gradient-ring avatar + username + verified check + red LIVE badge + viewer count + close X across the top, a short live-comment feed + an EMPTY "Add a comment…" bar + heart/share icons across the bottom, and pink/red reaction hearts floating up the right edge. A benefit sentence builds one short phrase per slide as the top overlay, and it closes on a clean brand logo card with the payoff line + CTA.
Deterministic and FREE — no generative image/video, no AI-rendered text. The paid music bed is
a separate capability (create-music-elevenlabs) muxed on afterward.
Run
python3 scripts/build.py --config config.json --assets <stills-dir> --out master-silent.mp4
# quick check — one frame per slide:
python3 scripts/build.py --config config.json --assets <stills-dir> --stills <dir>
config.example.json is a full worked config (Glossier). Config shape:
username,verified,palette,slide_dur,endcard_dur,crossfadeslides[]—{ image, phrase, viewers, comments: [[handle, text], …] }per productendcard—{ logo, logo_is_white, payoff, handle, cta }music—{ prompt, length_ms, trim_intro_sec }(consumed bycreate-music-elevenlabs)
Image paths in the config resolve against --assets.
Craft rules (baked into the renderer)
- Center each product on its TOP-HALF silhouette, never the full non-white bbox — the base
drop-shadow otherwise inflates the box and the product reads shifted sideways. The renderer
measures the top 50% of the silhouette with an
L<246threshold (catches white-product edge shading too) and centers that midpoint. - Reaction hearts float up the right edge as a full column and may overlap the centered product — that's fine; don't shrink them to a thin edge ribbon.
- Comments must be claim-free brand-descriptor vibe (2-3 words, generic handles, NO emoji — PIL can't render color emoji); the comment INPUT bar stays empty. LIVE badge + viewer count + hearts are ambient live-stream chrome, not proof claims.
- Endcard is the clean logo card (bg + wordmark + @handle + CTA + payoff), never a model face.
- Real product stills + real wordmark only. Music bed only, no VO.
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.
- 13d ago First seen · 55 lines · 141 tokens per session scan A ddebb80e0cae
render-ig-live-gallery is a skill published in the GitHub repository gooseworks-ai/goose-skills (1,202 stars, last pushed 11d ago), licensed MIT. It adds 141 tokens to every session and 823 once invoked, about $0.0007 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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