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-imessage-chatgit 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-imessage-chat)<a href="https://agentmods.dev/skills/gooseworks-ai/goose-skills/render-imessage-chat"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/render-imessage-chat/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-imessage-chat"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/render-imessage-chat.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, 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 MCP Rug Pull · line 81 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 | $0.00112 | $0.01266 |
| Opus 5 | $0.00056 | $0.00633 |
| Sonnet 5 | $0.00022 | $0.00253 |
| Haiku 4.5 | $0.00011 | $0.00127 |
Grade A, and why
render-imessage-chat 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 — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.
render-imessage-chat
The free renderer for the imessage-chat video ad format — a texting-thread reveal where a friend-to-friend conversation animates in on a phone (typing indicators, composer typing, bubble pops, smooth auto-scroll) and lands on a designed brand end card. Deterministic Playwright + ffmpeg assembly; no generative video of the UI, so bubble text and the wordmark stay pixel-crisp.
This capability is the generic assembler — the template recipe (DB) supplies the
per-brand thread, product image, and end_card config, and gates the paid
calls (product image → create-image-fal, music bed → create-music-elevenlabs) to
their own capabilities. It bundles the iMessage-mockup HTML generator + the
send/receive SFX so a chat render is self-contained and $0.
The three defects it fixes (QA GOOSE-2481)
- Rich-link attachment — a product/link renders as a REAL iMessage URL
preview: the image (top-rounded corners) flush against a gray meta card with a
bold title + domain subtitle + chevron. NOT a bare image with a distorted
caption floating centered below it (the mockup's default
.attachment-meta). The fix is baked intorecord-chat.js's injected style, theme-aware. - No text bleed — every bubble fits. This is an AUTHORING rule the recipe
enforces: split any long line into multiple short bubbles (see the two
speclines inconfig.example.json). The renderer honors the thread it's given. - A designed end card — wordmark + ⭐ proof row + trust trio + CTA pill
(
render-end-card.js+end-card.template.html), not a bare logo.
Run
cd scripts && npm install # once — installs Playwright for the recorders
node record-chat.js --config config.json --out-dir <work> # → master-chat.mp4 + .sfx.json
node render-end-card.js --config config.json --out-dir <work> # → scene-end-endcard.mp4
bash stitch.sh --chat <work>/master-chat.mp4 --end <work>/scene-end-endcard.mp4 \
--sfx <work>/master-chat.sfx.json --out <work>/master-final.mp4 \
[--music <work>/music-bed.mp3] [--also-1x1]
What ships with it
14 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.
- assets/sfx/imessage-receive.mp3 12 KB
- assets/sfx/imessage-send.mp3 4.2 KB
- scripts/config.example.json 2.7 KB
- scripts/end-card.template.html 2.5 KB
- scripts/mockup/generate.js 15 KB runs code
- scripts/mockup/templates/chat.css 17 KB
- scripts/mockup/templates/icons.js 3.3 KB runs code
- scripts/package-lock.json 1.7 KB
- scripts/package.json 322 B
- scripts/record-chat.js 18 KB runs code
- scripts/render-end-card.js 6.2 KB runs code
- scripts/stitch.sh 4.4 KB runs code
- skill.meta.json 317 B
- tests/smoke-test.md 2.0 KB
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 · 83 lines · 112 tokens per session scan A 70f8b29e6732
render-imessage-chat is a skill published in the GitHub repository gooseworks-ai/goose-skills (1,202 stars, last pushed 11d ago), licensed MIT. It adds 112 tokens to every session and 1,266 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.
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