复制安装命令
用 Codex 或 Claude 安装复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它先审查 Skill 页面再帮你安装。
复制前请先查看来源、License 和安全提示。
Put your AI agent on the growth team.
用 Codex 或 Claude 安装复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它先审查 Skill 页面再帮你安装。
复制前请先查看来源、License 和安全提示。
来源文件:README.md
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
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>
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
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
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.
| Stage | What your agent can do | Example skills |
|---|---|---|
| Research | Understand the brand, customers, competitors, audiences, creators, trends, comments, and product demand | brand-research, audience-research, comment-mining, competitor-social-research, influencer-prospecting, trend-discovery, product-demand-research |
| Analyze | Diagnose ads, creator profiles, transcripts, policy risk, landing-page message match, and unusual social performance | competitor-ad-intelligence, creator-profile-teardown, transcript-intelligence, meta-ads-analyzer, meta-ad-policy-checker, ad-to-landing-page-auditor, outlier-post-finder |
| Create | Repurpose research, remix graphic ads, make product photography and social graphics, and animate static images | content-repurposing, remix-graphic-ad-from-reference, product-photoshoot, goose-graphics, animate-image |
| Learn and iterate | Bring results back into research and analysis, then decide the next test | Re-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.
npx gooseworks search "reddit scraping" # Search the skill catalog
npx gooseworks credits # Check your credit balance
npx gooseworks update # Update to latest skill version
200+ skills across the growth stack, grouped by focus area:
| Category | What's inside |
|---|---|
| Ads | Research, build, and analyze paid campaigns across Meta and Google |
| SEO | Keyword research, content gaps, SERP analysis, technical audits |
| Lead generation | Find, enrich, and qualify prospects for your pipeline |
| Outreach | Draft, personalize, and run outbound across email and social |
| Content | Blog posts, social content, carousels, video scripts, newsletters |
| Research | Company, market, and prospect deep-dives |
| Competitive intel | Track competitor pricing, launches, positioning, and ads |
| Monitoring | Watch for mentions, signals, and changes across the web |
| Social | Scrape and analyze social platforms and audiences |
| Brand | Voice, positioning, and visual brand assets |
Browse and search every skill at skills.gooseworks.ai.
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.
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
Each skill directory must include:
SKILL.md — Skill documentation and usage guideskill.meta.json — Machine-readable metadataskill.meta.json fields:
| Field | Required | Description |
|---|---|---|
slug | Yes | Unique kebab-case identifier |
category | Yes | capabilities, composites, or playbooks |
tags | Yes | String array of category tags |
installation.base_command | Yes | Install command |
installation.supports | Yes | Array: claude, codex, cursor |
features | No | Feature flags |
github_url | No | Source repository URL |
author | No | Skill author |
example_prompt | No | Copyable prompt shown in the catalog and docs for trying the skill |
These skills run inside your coding agent, so it's worth knowing exactly what they do:
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./tmp/gooseworks-scripts/, never into your project directory. Only API requests go through GooseWorks servers; review any script before letting your agent run it.SKILL.md to tune that behavior.~/.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.gooseworks install --mcp.Found something that looks off? Open an issue — we'd rather fix it in public.
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.
Built by GooseWorks
name: meta-ad-policy-checker
description: Pre-flight policy check for Meta ads. Takes ad copy plus advertiser context, resolves and fetches the relevant Meta transparency-center policy pages at runtime, and returns a Pass / Fix Required / Block verdict with cited findings and rewrites.
tags: [ads]Meta disapproves ads for policy reasons constantly, and most disapprovals are preventable. The pattern is almost always the same: an advertiser (or an AI agent generating variants) writes copy that uses a phrase or implies a claim that violates Meta's published advertising standards. The fix is cheap if you catch it before submission, expensive if you don't — repeated disapprovals on the same account can throttle delivery or trigger account-level restrictions.
This skill is a pre-flight check. It reads ad copy, figures out which Meta policies apply, fetches the live policy text from Meta's transparency center, and returns a clear verdict with specific findings, citations, and rewrites. It does not hardcode policy rules — Meta updates those, and a static rule list goes stale. Instead, the skill uses Meta's own canonical policy pages as ground truth on every run.
Core principle: The skill provides the methodology — what to check, how to reason, what severity to assign. Meta provides the source of truth — the actual policy text. This separation is what keeps the skill correct as Meta's standards evolve.
None / Employment / Credit / Housing / Social Issues, Elections or Politics (this changes the applicable rules significantly)pre-flight (block until clean) or audit (flag-only, used for already-live ads)Reason about the ad before fetching. Most ads need 3–6 policy pages, not all 25. Always include the baseline set, then add content-driven pages based on what the ad mentions, then add category-driven pages based on declared Special Ad Category.
Treat the entries below as policy lookup keys, not URL slugs. Meta's Transparency Center URLs are nested under category paths and change over time, so never construct a flat policy URL directly from these labels.
| Triggers | Policy lookup keys |
|---|---|
| Income, earnings, payouts, "make money", specific dollar amounts | Personal financial requirements; unrealistic outcomes |
| Health, weight loss, supplements, wellness claims | Health and wellness; before-and-after photos |
| Targeting by age, gender, race, religion, nationality | Discriminatory practices |
| Crypto, weapons, adult, drugs, alcohol, gambling, tobacco | Restricted content |
| Political, social-issue, election content | Social issues, elections or politics |
| Profanity, slurs, sensitive language | Profanity; inflammatory content |
| Anything that implies tracking / scraping / circumvention | Circumventing systems |
| Special Ad Category | Add |
|---|---|
| Employment | Employment |
| Credit | Credit |
| Housing | Housing |
| Social Issues, Elections or Politics | Social issues, elections or politics |
Output of Phase 1: an ordered list of policy lookup keys to resolve and fetch in Phase 2.
Fetch Meta's ad-standards index first:
https://transparency.meta.com/policies/ad-standards/
For each lookup key from Phase 1:
Caching rule: in-memory for the current session only. A batch check of 10 ad variants should produce 3–6 policy-page fetches total, not 30–60. Skip persistent caching to avoid stale-cache bugs across sessions.
Fallback: if the index cannot be parsed or a resolved page 404s, use a site-restricted web search for the policy title on Meta's transparency domain and navigate to the closest-matching current policy. Log this as a "policy URL drift" note in the output so the lookup list can be updated.
For each fetched policy, walk through every element of the ad (headline, body, description, CTA, link, visual description if provided) and ask:
Severity model — three levels:
| Severity | Definition |
|---|---|
| Block | Clear violation. Ad will almost certainly be disapproved. Do not submit until fixed. |
| Fix Required | Likely violation or explicit risk. Ad may pass but is at meaningful risk of disapproval or under-delivery. Fix recommended before submission. |
| Caution | Edge case. Ambiguous wording or pattern Meta sometimes flags. Worth knowing about; not necessarily worth changing. |
For each issue identified, produce:
Common disapproval reason: ad claims that aren't substantiated on the LP, or LP claims more aggressive than the ad. Run a brief cross-check:
non-functional-landing-pages)This is policy-specific cross-check — not message-match. For message-match (does the LP feel like a continuation of the ad?), use ad-to-landing-page-auditor.
Use this exact structure.
VERDICT: PASS | FIX REQUIRED | BLOCK
ADVERTISER CONTEXT (echo back so the user knows what was assumed)
SPECIAL AD CATEGORY: [declared]
POLICIES CHECKED: [list of slugs fetched, with URLs]
PER-ISSUE FINDINGS:
- Issue: [exact phrase or pattern from the ad]
Policy: [name] (URL)
Citation: "[direct quote from Meta's policy page]"
Severity: Block | Fix Required | Caution
Why: [one-line explanation grounded in the citation]
Suggested rewrite: [safer alternative preserving intent]
RISK SCORE: Low | Medium | High
(factors: count of Block issues, count of Fix Required issues, special-category status)
3 SAFER VARIANTS OF THE FULL AD:
(only generated if any Block or Fix Required issues exist)
- Variant A: [full ad rewrite — headline + body + CTA]
- Variant B: [full ad rewrite — different angle on the same offer]
- Variant C: [full ad rewrite — most conservative version]
NOTES:
- Areas where Meta enforcement is known to vary (best-effort observation)
- LP-related findings (if URL was provided)
- Anything requiring human judgment beyond what this skill can verify
- Any "policy URL drift" notes from Phase 2 fallback handling
This skill is built to be both standalone-runnable and callable from other skills. Recommended chain patterns:
messaging-ab-tester produces N variants → meta-ad-policy-checker runs on each → only PASS / FIX REQUIRED variants surface to the usermeta-ads-campaign-builder produces a brief with multiple ads → meta-ad-policy-checker runs on every ad → block launch if any return BLOCKmeta-ads-analyzer flags an ad with near-zero delivery → suggest running meta-ad-policy-checker to rule out a silent disapprovalThe skill returns structured output (verdict + per-issue array) so calling code can gate on verdict !== "BLOCK" programmatically.
The list of policy slugs in Phase 1 is the only mutable piece of this skill. Meta occasionally renames or restructures policy pages. The Phase 2 fallback handles individual page drift gracefully, but periodic review of the slug list (annually, or any time several "policy URL drift" notes appear in outputs) keeps the skill efficient. The slug list lives inline in this SKILL.md so updates are a single-file change.
messaging-ab-tester — runs upstream; generates variants this skill should checkmeta-ads-campaign-builder — runs upstream; produces multi-ad briefs this skill should validate before launchad-to-landing-page-auditor — paired pre-flight; different concern (message-match vs. policy compliance), same checkpointmeta-ads-analyzer — runs downstream; if a live campaign shows symptoms of a silent disapproval (near-zero delivery, throttling), this skill is the diagnostic stepad-campaign-analyzer — loose link; disapprovals show up as underdelivery in performance data, so cross-reference when a creative shows zero delivery
评论 (0)
暂无评论,成为第一个评论者吧!