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render-whiteboard-explainer

Put your AI agent on the growth team.

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项目 README

来源文件:README.md

抓取于 2026年10月1日
CleanShot 2026-07-13 at 20 15 47@2x CleanShot 2026-07-13 at 20 16 54@2x

AI Skills for Brand Growth

Put your AI agent on the growth team.

Research customers and competitors, analyze what is working, create the next campaign, and learn from the result. Goose Skills gives Claude Code, Cursor, Codex, and other coding agents ready-to-use workflows for ads, social media, content, competitive intelligence, SEO, lead generation, and GTM.

Browse all skills at https://skills.gooseworks.ai

Works with Claude Code · Cursor · Codex

npm version License: MIT Skills


Contents


Quick Start

AI Coding Agents (Claude Code, Cursor, Codex, etc)

Paste this into your coding agent (Claude Code, Cursor, or Codex) and it'll set everything up:

Install the Gooseworks skills:

In the terminal, run `npx gooseworks install --all`.

Then run `npx gooseworks login` and it'll open a browser to sign in and set up the tools, then confirm it worked.

The skills can be used with /gooseworks <prompt>

Claude Cowork

Run this command in a terminal first:

npx gooseworks install --all

Then authenticate:

npx gooseworks login

Then make sure you're working inside a local folder on your machine, and then you can use the skills in Cowork like this:

Use /gooseworks skill to generate some ad creatives

Install manually

Prefer to run it yourself? Use the command directly:

npx gooseworks install --all       # All detected agents

This gives your coding agent access to the full catalog of 200+ skills. After installing, just ask your agent to use any skill by name.

If you want a cloud-based AI coworker that already knows all these skills and more, sign up to Gooseworks


Brand Growth collection

The Brand Growth collection is a curated path through the normal Goose Skills catalog for consumer and ecommerce brand work. It is not a separate package or command: install GooseWorks once, then ask /gooseworks for the outcome you need.

StageWhat your agent can doExample skills
ResearchUnderstand the brand, customers, competitors, audiences, creators, trends, comments, and product demandbrand-research, audience-research, comment-mining, competitor-social-research, influencer-prospecting, trend-discovery, product-demand-research
AnalyzeDiagnose ads, creator profiles, transcripts, policy risk, landing-page message match, and unusual social performancecompetitor-ad-intelligence, creator-profile-teardown, transcript-intelligence, meta-ads-analyzer, meta-ad-policy-checker, ad-to-landing-page-auditor, outlier-post-finder
CreateRepurpose research, remix graphic ads, make product photography and social graphics, and animate static imagescontent-repurposing, remix-graphic-ad-from-reference, product-photoshoot, goose-graphics, animate-image
Learn and iterateBring results back into research and analysis, then decide the next testRe-run the relevant analysis skill with current performance and audience evidence

ScrapeCreators powers structured public social and ad-library research behind several workflows. Signed-in GooseWorks users access it through the managed first-party proxy and do not need a separate ScrapeCreators key. The user-facing skills turn that source data into a brief, shortlist, analysis, or recommendation instead of returning raw API output.

Browse the Brand Growth collection

After installation, start with:

/gooseworks onboard me

The agent will collect the useful company context for future growth work and finish by asking what you want to do first. Existing users can skip onboarding and keep using /gooseworks exactly as they do today.


Commands

npx gooseworks search "reddit scraping"   # Search the skill catalog
npx gooseworks credits                     # Check your credit balance
npx gooseworks update                      # Update to latest skill version

Skills Catalog

200+ skills across the growth stack, grouped by focus area:

CategoryWhat's inside
AdsResearch, build, and analyze paid campaigns across Meta and Google
SEOKeyword research, content gaps, SERP analysis, technical audits
Lead generationFind, enrich, and qualify prospects for your pipeline
OutreachDraft, personalize, and run outbound across email and social
ContentBlog posts, social content, carousels, video scripts, newsletters
ResearchCompany, market, and prospect deep-dives
Competitive intelTrack competitor pricing, launches, positioning, and ads
MonitoringWatch for mentions, signals, and changes across the web
SocialScrape and analyze social platforms and audiences
BrandVoice, positioning, and visual brand assets

Browse and search every skill at skills.gooseworks.ai.


Usage Examples

After installing, just ask your coding agent naturally:

"/gooseworks Generate static ad creatives for my brand"
"/gooseworks Use the reddit-post-finder skill to search r/startups"
"/gooseworks Use the apollo-lead-finder skill to find CTOs at AI companies"
"/gooseworks Use the competitor-intel skill to research Acme Corp"
"/gooseworks Use the goose-graphics skill to create a LinkedIn carousel about our launch"

Your agent will search the GooseWorks catalog, download the skill, and run it automatically.


Building from Source

git clone https://github.com/gooseworks-ai/goose-skills.git
cd goose-skills
node scripts/validate-skills.js  # Validate SKILL.md + skill.meta.json contract
node scripts/build-index.js      # Generate skills-index.json
node bin/goose-skills.js list    # Test locally

Skill Metadata Contract

Each skill directory must include:

  • SKILL.md — Skill documentation and usage guide
  • skill.meta.json — Machine-readable metadata

skill.meta.json fields:

FieldRequiredDescription
slugYesUnique kebab-case identifier
categoryYescapabilities, composites, or playbooks
tagsYesString array of category tags
installation.base_commandYesInstall command
installation.supportsYesArray: claude, codex, cursor
featuresNoFeature flags
github_urlNoSource repository URL
authorNoSkill author
example_promptNoCopyable prompt shown in the catalog and docs for trying the skill

Security & Trust

These skills run inside your coding agent, so it's worth knowing exactly what they do:

  • Open source & inspectable. Every skill — its SKILL.md instructions and all scripts — lives in this repo under the MIT license. The gooseworks CLI fetches skills at runtime so recipes stay current, but the source you'd run is right here to read, diff, or pin before you run it.
  • Scripts run locally. Skill scripts execute on your machine and write to /tmp/gooseworks-scripts/, never into your project directory. Only API requests go through GooseWorks servers; review any script before letting your agent run it.
  • Your agent stays in control. The skills are a tool your agent reaches for when it fits the task (data at scale, sources behind auth, a specific provider) — not a replacement for its built-in web search or fetch on quick lookups. You can read or edit any installed SKILL.md to tune that behavior.
  • Credentials stay local. Auth is a Bearer token stored at ~/.gooseworks/credentials.json (file mode 0600). Third-party provider keys (Apify, Apollo, etc.) are held server-side — your token never touches them. All network calls are HTTPS.
  • The MCP server is opt-in. Registering the GooseWorks MCP server is off by default; it only happens if you explicitly run gooseworks install --mcp.

Found something that looks off? Open an issue — we'd rather fix it in public.


License

MIT — see LICENSE for details.

The skill files and CLI in this repository are MIT-licensed. The GooseWorks API they connect to is a separate paid service governed by its own terms.

文档与办公

低风险

  • 来源需自行核对维护者身份。
  • 未检测到明显脚本安装指令。
  • 未检测到明显外部权限要求。
  • 未检测到高风险命令。
  • 扫描发现:0 条。

Codex — Git Clone 安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 克隆仓库:git clone https://github.com/gooseworks-ai/goose-skills.git
  3. 将 "skills/ads/capabilities/render-whiteboard-explainer" 文件夹复制到 Codex 的 skills 目录中。
  4. 重启 Codex 让新的 skill 生效。

Codex — 手动复制安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 从源仓库下载 SKILL.md 及相关文件。
  3. 在 Codex 的 skills 目录中创建新文件夹。
  4. 将所有 skill 文件复制到新文件夹中。
  5. 重启 Codex 让新的 skill 生效。

Claude Code — Git Clone 安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 克隆仓库:git clone https://github.com/gooseworks-ai/goose-skills.git
  3. 将 "skills/ads/capabilities/render-whiteboard-explainer" 文件夹复制到 Claude Code 的 skills 目录中。
  4. 重启 Claude Code 让新的 skill 生效。

Claude Code — 手动复制安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 从源仓库下载 SKILL.md 及相关文件。
  3. 在 Claude Code 的 skills 目录中创建新文件夹。
  4. 将所有 skill 文件复制到新文件夹中。
  5. 重启 Claude Code 让新的 skill 生效。

Cursor — Git Clone 安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 克隆仓库:git clone https://github.com/gooseworks-ai/goose-skills.git
  3. 将 "skills/ads/capabilities/render-whiteboard-explainer" 文件夹复制到 Cursor 的 skills 目录中。
  4. 重启 Cursor 让新的 skill 生效。

Cursor — 手动复制安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 从源仓库下载 SKILL.md 及相关文件。
  3. 在 Cursor 的 skills 目录中创建新文件夹。
  4. 将所有 skill 文件复制到新文件夹中。
  5. 重启 Cursor 让新的 skill 生效。

GitHub Copilot — Git Clone 安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 克隆仓库:git clone https://github.com/gooseworks-ai/goose-skills.git
  3. 将 "skills/ads/capabilities/render-whiteboard-explainer" 文件夹复制到 GitHub Copilot 的 skills 目录中。
  4. 重启 GitHub Copilot 让新的 skill 生效。

GitHub Copilot — 手动复制安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 从源仓库下载 SKILL.md 及相关文件。
  3. 在 GitHub Copilot 的 skills 目录中创建新文件夹。
  4. 将所有 skill 文件复制到新文件夹中。
  5. 重启 GitHub Copilot 让新的 skill 生效。

Windsurf — Git Clone 安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 克隆仓库:git clone https://github.com/gooseworks-ai/goose-skills.git
  3. 将 "skills/ads/capabilities/render-whiteboard-explainer" 文件夹复制到 Windsurf 的 skills 目录中。
  4. 重启 Windsurf 让新的 skill 生效。

Windsurf — 手动复制安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 从源仓库下载 SKILL.md 及相关文件。
  3. 在 Windsurf 的 skills 目录中创建新文件夹。
  4. 将所有 skill 文件复制到新文件夹中。
  5. 重启 Windsurf 让新的 skill 生效。
查看 SKILL.md 原文
name: render-whiteboard-explainer
description: Assemble a whiteboard explainer video ad from a beats file — a narrator explains one idea while a real whiteboard fills up in black marker, with a hand-lettered title, bulleted rows down the left, a drawing filling the right, and a payoff that letters the closing line and rings the claim. The board is a PHOTOGRAPH and the ink is multiplied onto it, so the surface sheen and window light come through the strokes; the drawings are generated as line art and traced to ordered strokes, then revealed in drawing order on the word they belong to. The layout is SOLVED from the beats, never hand-placed. FREE assembly (Pillow plus ffmpeg) apart from one board photo and one drawing per subject, both one-time per brand. Use for the whiteboard format.
status: draft

render-whiteboard-explainer

The renderer for the whiteboard video ad format: a voice explains one idea while a board fills up in marker, the way a graphic recorder works a room. Every mark lands on the word it belongs to, and the board is wiped and reused between sections.

Siblings in the chat-UI family are render-imessage-chat, render-chatgpt-chat and render-apple-notes-chat, where a screen is the creative. Reach for this one when the creative is someone explaining a thing by drawing it.

The three decisions that make this format work

The board is a photograph. A drawn board reads as a drawn board, and a plain white frame reads as a sketch film. Both were built and both were rejected. One generated still of a real blank whiteboard in a real room is the plate, and the ink is multiplied onto it so the surface sheen and the window light come through the strokes rather than sitting on top as flat black. The handheld drift is generated over both layers at once, so nothing can slide against anything.

The drawings are generated as line art, then traced. Do not hand-code them, and do not trace painterly images. Art traced from a photograph carries every contour the photograph had and reads as clip-art; art generated as a marker drawing traces to a handful of confident paths. An open hand came back as a single continuous stroke. Chain each generation off the first so the line weight matches across the set.

There is no colour. Black marker throughout. Do not add an accent.

Choices

The recipe asks these before any paid step; this renderer only draws what the beats say.

  • the script — what the narrator says. Everything downstream is anchored to its word timings, so it is settled first and never changed afterwards.
  • the beats — for each moment, what is SAID and what is DRAWN. A row of text, a drawing, or both. One number can be marked as the hero, which letters it large instead of as another row.
  • the title and subtitle — lettered on the first board.
  • the payoff — the closing line, lettered on the last board, with a ring closing around the claim it refers to.
  • the boards — how many times the board is wiped and reused. Three suits a half-minute.

Brand facts come from the brand kit.

What it renders

  1. The plate. One photograph of a blank board in a room, generated once per brand, then cropped so the board fills the frame with its side edges running out of shot. The writable surface is measured off the image and pulled inside the caption safe zone before anything is mapped through it.
  2. The drawings. One black line drawing per subject the script names, generated once per brand and traced into ordered stroke paths.
  3. The layout. Solved from the beats, not authored. Rows go down a left column, drawings down a right one, with an enforced gutter between them, and the content runs the full height of the board. Boards are split at a pause near a balanced boundary, which is where a person would wipe.
  4. The video. Marks appear stroke by stroke in drawing order, each starting on its own word. Text is written letter by letter. The board wipes between sections. Captions sit inside the safe zone and never run ahead of the voice.
  5. The master. Gentle compression before a measured two-pass loudness normalisation, then a limiter. Targets minus fourteen LUFS with true peak under minus one and a half, and keeps the payoff hold intact.

Non-negotiables

  • Every mark lands on its own word. The voiceover is the clock. An anchor that resolves to the wrong word does not look wrong, it silently reorders the video: one that matched an early word instead of a late one once dragged a whole section to the front, and the ad played its ending first with nothing reporting a problem. Anchors are resolved once, shared by the solver and the renderer, and an ambiguous one is refused rather than guessed at.
  • Nothing is hand-placed. Anything that refers to something else — an arrow, a note, a ring — takes its target as an argument and works out its own position. Anything sharing space with a drawing is bounded by that drawing's box. Two things placed at coordinates chosen independently will eventually meet.
  • Copy a reference's grammar, never its content. The reference board bullets its rows with a drawn eye and fans emphasis marks beside its phrases, but those belong to that board's brand. Reproduced on another script they are decoration that means nothing. Filler has to be about something: a drawing of what the line refers to, never abstract specks.
  • Two reviews, both human. The storyboard still costs seconds and is where relevance is judged — whether a mark is about the line it sits under, whether the payoff says the closing line. No automated check decides that. Then the finished cut, watched end to end with the watch skill.

Inputs

  • the spoken audio and its word-level timings, as described below
  • a beats file — see the example beside the scripts
  • a brand kit for the facts

A gap worth knowing about. The sanctioned voice capability, create-vo-elevenlabs, returns audio only. This format needs word-level timings for every mark, so they have to come with the audio. Until that capability can return them, the timings are supplied alongside. Never call the speech provider directly; the proxy attribution is required.

Checks it runs itself

The build refuses to continue when any of these fail, and names what broke:

  • every anchor resolves to exactly one intended word
  • sections start in script order
  • every mark finishes being drawn before its board is wiped
  • rows stay inside the column and cannot reach a drawing
  • loudness, true peak and the payoff hold

Cost

The board photo and the drawings are one-time per brand. A second video for the same brand costs only the voiceover. Everything else — the layout, the lettering, the tracing, the render and the master — is free and local. Rendering a half-minute takes under three minutes.

Honest ceiling

Measured against the filmed reference this reaches about a fifth of its ink cover, because the reference is a time-lapse of a much longer drawing session while every mark here waits for its word. Filler narrows that and does not close it. If a brief needs a genuinely full board, the script has to be longer or the marks have to stop waiting for words.

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