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-search-gridgit 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-search-grid)<a href="https://agentmods.dev/skills/gooseworks-ai/goose-skills/render-search-grid"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/render-search-grid/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-search-grid"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/render-search-grid.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 | $0.00130 | $0.00942 |
| Opus 5 | $0.00065 | $0.00471 |
| Sonnet 5 | $0.00026 | $0.00188 |
| Haiku 4.5 | $0.00013 | $0.00094 |
Grade A, and why
render-search-grid 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 — 57 lines — stays where its author put it; the contents beside it link to each section on GitHub.
render-search-grid
Render the 'search-grid' format from a config. It is a deterministic assembler — no
generative image/video, no AI-rendered text. Everything on screen is the brand's REAL
product/lifestyle photography + logo, so the typed hook, feature captions, wordmark, and
photos stay pixel-crisp. The only paid input is an optional music bed, produced upstream
by create-music-elevenlabs and passed to render.py --music.
The format (four beats, one continuous ~18s motion piece, 1080×1920)
- Search (0–5s) — a 3-column masonry grid of the brand's catalog behind a Pinterest search bar; a believable phrase types in letter-by-letter. Side columns drift DOWN, the middle column drifts UP (counter-parallax).
- Cards (5–7s) — 3 room/product cards slide in from the RIGHT and stack over a warm blurred backdrop.
- Features (7–14.5s) — the TOP card physically expands (its box grows from the
stacked rect to full-screen, animating width/height — NOT
transform:scale, which would stretch the image), then swipe-left → swipe-left through the SAME 3 rooms, each now full-bleed with a caption. The 3 cards ARE the 3 features. - End card (14.5–18s) — hero + wordmark + tagline + CTA on a warm background.
Scripts (all free / deterministic)
scripts/build_html.py --config config.json --out index.html— config → a single self-contained HTML page exposingwindow.seek(tMs)(images base64-embedded).scripts/capture.js --html index.html --out frames --fps 30 --duration 18000— headless Chromium frame-stepsseek()to a PNG per frame (auto-discovers a cached Playwright chromium, or pass--exe).scripts/render.py --config config.json [--music bed.m4a] --out master.mp4— orchestrates build → capture → FFmpeg (muxes the bed with-map 0:v:0 -map 1:a:0when--musicis given;$0silent pass without it).scripts/prep_assets.py crop in.jpg out.jpg/logo logo.jpg wordmark.png— the two fixes this format needs almost every time: crop baked-in white L/R margins off heroes, and key the white out of a black-on-white logo JPG to a transparent PNG.
What ships with it
7 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 · 57 lines · 130 tokens per session scan A 0f5cd153d818
render-search-grid is a skill published in the GitHub repository gooseworks-ai/goose-skills (1,202 stars, last pushed 11d ago), licensed MIT. It adds 130 tokens to every session and 942 once invoked, about $0.0006 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.
Other skills, from other repositories
excalidraw-ai
Create professional Excalidraw diagrams by generating JSON directly. This skill provides the Excalidraw JSON schema reference and professional icon libraries for AI agents to autonomously create diagrams without templates.
generate-image
Generate or edit images with AI models through the OpenRouter Image API (Gemini, Seedream, Recraft, GPT-Image, Riverflow). Use for photos, illustrations, artwork, concept art, visual assets, logos, and image editing or compositing from reference images. For flowcharts, circuits, pathways, and other technical diagrams…
infographics
Create professional infographics using Nano Banana Pro AI with smart iterative refinement. Uses Gemini 3.6 Flash for quality review. Integrates research-lookup and web search for accurate data. Supports 10 infographic types, 8 industry styles, and colorblind-safe palettes.
animation-reverse-engineering
Reverse-engineer any motion reference (a video from X/Twitter, Dribbble, a screen recording, a GIF) into production animation code through frame-level dissection. Use when the user shares a video/URL and says "implement this animation", "recreate this motion", "port this interaction", "how does this animate", "clone…
design-elevation
Comprehensive design elevation system that automatically transforms functional visual outputs into polished, professional designs. Use when creating ANY visual output including presentations (pptx), spreadsheets (xlsx), dashboards, reports, HTML artifacts, PDFs, web pages, or data visualizations. Applies systematic…
is-this-photo-real
Verify whether an image or video is authentic, original and correctly captioned — provenance checks, error level analysis, noise and JPEG compression analysis, clone and copy-move detection, lighting and shadow consistency, C2PA Content Credentials, deepfake and AI-generation tells, and the honest limits of…