SkillAtlasSkill 详情

write-video-ad-script

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.

内容与创作

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/write-video-ad-script" 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/write-video-ad-script" 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/write-video-ad-script" 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/write-video-ad-script" 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/write-video-ad-script" 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: write-video-ad-script
description: Write the words of a short-form video ad (voiceover, dialogue, chat bubbles, on-screen lines) the way performance creative teams do instead of from a blank page. Builds the script from the buyers' own words, the beat sheet of an ad that already works and three deliberately different angles, filters them with a rule check and a second non-Claude model, and takes the strongest into the review with the other two as one-line swaps. Use it in every video ad run before any paid step, and whenever the user asks to write, rewrite or improve a video ad script or says a script sounds generic or AI-written.
status: active

write-video-ad-script

A model asked to "write a 30-second ad for this product" writes the average of every ad it has read. That is why AI scripts sound generic. The tools and teams whose scripts perform never start there. They build each script from four things, and so does this skill:

  1. What buyers actually say, word for word (reviews, comments, complaints).
  2. The beat sheet of an ad that already works in this format: borrow the persuasion (hook type, timing, proof, objection, CTA), never the words.
  3. Angles that are different on purpose: one specific person, one pain, one angle type each, and never the first idea every brand in the category runs.
  4. A filter: a rule check a machine can decide, then a second opinion from a different model family.

The output is one script in the format's own shape, two runner-up concepts the user can swap to, and a record of what the script was built on.

When to use it, and when not

  • Every video ad run, before any paid step, for any format whose ad has words: voiceover, dialogue, a chat thread, on-screen lines, lyrics. The goose-video-local runtime calls it after reading the format's recipe and before it assembles the review.
  • When the user asks to write, rewrite or improve a video ad script.
  • The user gave their own lines: keep them verbatim. Run only the rule check in its report-only mode, and raise only what changes something for them (a line too long to say in time, a claim the brand can't make). Change nothing unless they say so.
  • The format has no words (a voiceless dance story, a music-only product loop) apart from an end card: skip this skill.

When the angle is already decided

These answers are the frame. Never ask them again:

  • a recipe choice whose answer sets the script (a script angle, story, hook angle or story shape: any choice whose sets list includes the script);
  • the brief's angle or hook;
  • a batch concept's angle;
  • an idea the user picked from ad-angle-miner;
  • a remix's direction.

If the answer leaves room, the three concepts all work inside it, differing in the person, the pain or the proof.

If it fixes the whole angle (a remix of a finished video, a batch concept with its own hook), write one concept on it and vary only the hooks.

What you work from

  • The project brief and the answers to the format's choices (tone, narrator, setting).
  • The brand rules file the video runtime wrote (name, pronunciations, must say, never say, product facts). Product facts come only from there.
  • The format's recipe: its instructions, config and assets.
  • Anything already researched: buyer quotes saved for this brand, an angle bank from ad-angle-miner, quotes in the brief.

The working files live in the project's working folder, under a script subfolder. Their exact shapes, and how to run the two scripts, are in this skill's files reference: read it before writing them. Run both scripts from the folder that holds the working folder, calling them where this skill's scripts were saved.

Step 1. The script shape

Read the recipe's instructions and config, and write the shape file. It lists:

  • the beats in order, each with an id, who speaks, its seconds and its kind (spoken, on-screen, chat bubble or lyric);
  • which beat is the CTA;
  • the words per second.

Take the words per second from the recipe first (many configs carry a word budget or per-beat lines). If the recipe has none, measure the demo ad: its spoken words divided by its spoken seconds. With neither, use 3.0 for conversational talking-head delivery and 2.5 for slow narration.

  • A spoken beat fits about seconds times words-per-second words.
  • An on-screen card fits 8 words unless the format says otherwise.

The format's own rules win on shape. When the recipe says "a 13-sentence testimonial" or "one hook line on screen", the shape says that.

Step 2. Buyer quotes (the input that matters most)

Practitioners name this as the single biggest lever. Real phrases from real buyers replace the model's generic idea of the customer.

Reuse before you collect. Check these in order:

  1. Quotes saved for this brand in the GooseWorks workspace: read them with the MCP file tools, at video-scripts, then the brand id, then customer-words.json. Use them if they are under 60 days old.
  2. An angle bank ad-angle-miner wrote in this session or the workspace. Its quotes come with links.
  3. Quotes in the brief or the batch concept.

Collect when there is nothing to reuse. Free sources come first:

  • the brand's saved learnings and kit;
  • its product pages, fetched raw (review widgets load by script, so a plain fetch shows only a few reviews);
  • its marketplace listing.

Then the paid sources, through the GooseWorks data proxy (ScrapeCreators): comments on the brand's own best posts, product reviews, and a category complaint search. Fetch ad-angle-miner and follow its customer-voice section for the exact paths.

Paid calls need one yes from the user, asked with a rough credit count. Inside the video runtime, that question rides in the recipe's choices round; never ask it in a round of its own. Run on its own, ask it once, before the first paid call.

Aim for 20 to 30 quotes. Mix:

  • outcomes from happy buyers;
  • objections and doubts from the 1 to 3 star reviews;
  • complaints about competitors;
  • small specific moments ("3am, staring at the ceiling").

Keep each quote verbatim, with its link and a tag: pain, desire, objection, outcome, moment or switching. Never paraphrase one. A quote without a link is not a quote.

Save the bank to the workspace path above with the MCP file tools, so the next video for this brand reuses it for free. If the file tools refuse, skip saving: the bank still lives in this project's working folder. Never write it into the user's own folders.

When nothing can be found (a new brand with no reviews anywhere), build on the brand's own facts and the category's complaints from competitors' reviews. Tell the user in one line that the scripts aren't built on their buyers' words yet.

Step 3. References (borrow the persuasion, never the words)

Reference one is the format's demo ad. Read its lines and timing from the recipe's instructions and config first; the template's extracted script is often empty. Watch the demo video with the watch skill only when the recipe doesn't carry its lines.

Add up to three more ads in the same format from the evidence already gathered:

  • organic posts far above the account's usual views;
  • ads still running after 30 or more days, or with 3 or more variants;
  • the brand's saved inspiration (social inspiration library or search).

Ad libraries show what runs, not what converts, so treat every one as a candidate.

For each reference, write a persuasion record:

  • the hook line and its family (see the hook families reference);
  • the beat map, with seconds and word counts;
  • when the product enters;
  • the proof device;
  • the objection it answers;
  • the CTA wording;
  • one line on why it works;
  • a transfer rule: what you keep (the structure, the move), and what belongs to the other brand and is never reused (its words, claims, offer, names, faces).

Step 4. Angles: different on purpose

Models converge on the same few ideas, and a creative system prompt does little to change that. What works: generate many, rate how obvious each one is, and keep the unobvious ones that have real evidence behind them.

  1. List 15 candidate angles. Each one is:
    • one specific person in one situation (not "busy moms", but "a nurse coming off a night shift who can't switch off");
    • one pain or desire, anchored to one or more quote ids;
    • an awareness stage: unaware, problem-aware, solution-aware, product-aware or most-aware;
    • an angle type: pain, outcome, identity, switching, proof, contrast or objection;
    • one concrete product fact it rests on.
  2. Rate how likely a typical ad writer for this category is to write it, from 0 to
    1. Be honest: "it saves you time" is 0.9.
  3. Drop anything above 0.4, unless its evidence is the strongest you have (many quotes, or a reference that has run for months).
  4. Keep three that differ in both the person and the angle type. Never two on the same quote, and never two on the same hook family.

In a batch, build the quotes and the angle list once for the brand. Give every concept whose angle is open a different angle from that list.

Step 5. Write

For each concept, write the body on the reference's beat map, in the format's shape. Then write 3 or 4 hooks, each from a different family in the hook families reference. At least one hook reuses a buyer's own phrase.

The laws:

  • One message. A script carrying two beliefs carries none.
  • The first line lands the pain, the claim or the moment. No wind-up, no brand introduction, no "Have you ever".
  • Specific beats general: a named moment, a physical detail the viewer can check, a real number from the facts.
  • Show the proof: a demo, a test, a before and after, a reaction. Don't just say it.
  • The body pays off exactly what the hook promised.
  • End on the CTA. Nothing is said after it (an end card may follow).
  • Write how this person talks: contractions, fragments, the buyers' own words, short sentences. Read every line out loud; if a person wouldn't say it, rewrite it.
  • Fit the budget. Count words per beat: overstuffed lines get rushed, thin ones drag.
  • Brand rules always hold. Nothing in never-say, in words or in meaning. Every product claim (a result, number, ingredient, price, comparison) comes from the facts or a quote. The speaker's situation, feelings and small human details are craft, not claims, and they are what make it feel real.

Write the candidates file: the concepts with their angle, person, awareness stage, quote ids, reference id, typicality, hooks and beats.

Step 6. Check: rules, then a second model

The rule check. Run the lint script on the candidates, with the shape, the brand rules and the buyer quotes.

It fails on:

  • a line over budget, a missing beat, beats out of the format's order, or anything said after the CTA;
  • a dead opener;
  • a phrase the brand quoted as banned;
  • a concept with no buyer quote behind it.

It warns on:

  • a line that may break a brand rule. Rewrite it, unless it clearly means something else ("I work overnights" against "never claim it works overnight");
  • AI tells and stiff, contraction-free lines;
  • numbers no fact or quote backs;
  • the brand name in the first line;
  • a concept that never uses its buyers' words;
  • softer openers;
  • duplicate hooks.

Fix every error and read every warning. Run it again until it passes.

The second opinion. Run the critique script with the same files and the brief. A model from a different family (never Claude) judges every concept twice, once in each order, because judges favour whatever they read first. It scores hook, specificity, how spoken it sounds, proof, payoff and freshness, and gives a best hook, line edits and a ranking. It costs about 2 credits and runs without asking.

The script's exit codes:

  • 3: it wrote one MCP call per pass under the working folder's mcp-requests folder. For each, make the call (data post provider, then poll the job until it is complete), save the result where the request says, then run the same command again. The relay needs the video project id exported, like every paid call in the runtime.
  • 4: the critic gave no usable answer. Judge the concepts against the same rubric yourself, and carry on.

Apply the edits that hold up. Never apply an edit that adds a claim the facts don't back, or one that only makes a line flatter. Drop a concept the critic killed in both passes, if its reason is real. Then run the rule check again.

The critic raises the floor. It does not pick the winner: the user does, and later the ad's results.

Step 7. Into the review (no extra pause)

Take the top-ranked concept and its best hook. Put the script into the recipe's own script shape (a thread, beats with voiceover lines, slates, lyrics) and hand it to the runtime's review step. That review's single approval covers it.

In the same review, list the two runner-ups, one line each: the angle and the hook. The user can swap to one in a word. A swap redoes only the cheap pieces built from the script.

Add a note to the review labelled "How this script was made", with:

  • the angle;
  • what the buyers said, as a theme ("built on 6 buyer reviews about 3am wake-ups");
  • the kind of ad it borrows its structure from.

Never put the quotes themselves or their links in the note. Review sets can be remixed into other brands' videos.

When the user asks to choose ("show me a few scripts"), show the three concepts before the review: the angle and the hook, one line each. Then build the review on the one they pick.

Talk to the user like a creative partner. Never mention files, scripts, scores, models, the rule check or the second opinion unless they ask. If they change a line, their words are kept verbatim. Run the rule check in report-only mode, and raise only what changes something for them.

Step 8. Remember

Keep a script history for the brand in the GooseWorks workspace, next to the buyer quotes, as one JSON line per run. The file tools can't append, so read it, add the line and write it back. Each line records:

  • the date and the format;
  • the concept that shipped, and its hook;
  • the concepts passed over;
  • every line the user changed, before and after.

The next run reads it first: lean toward what they kept, away from what they passed on, and write the way their edits show.

A standing rule the user states ("never mention price", "we don't say 'cure'") is a brand rule. Save it to the brand the way the runtime says, not only to the history.

Cost

StepCost
Writing, the rule check, workspace readsFree
The second opinionAbout 2 credits, billed to the video project, not asked
Paid buyer-research sourcesBilled per call, asked once, saved so the brand pays once

Rules that never bend

  • Never invent a customer, a quote, a number or a result.
  • Never reuse a reference's lines, claims, offer, names or faces.
  • The user's own words are kept verbatim.
  • Nothing paid runs before the runtime's approval, except the second opinion (about 2 credits) and buyer research the user said yes to.

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