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meta-ad-policy-checker

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8月20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.

其他

中风险

  • 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:1 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/composites/meta-ad-policy-checker" 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/composites/meta-ad-policy-checker" 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/composites/meta-ad-policy-checker" 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/composites/meta-ad-policy-checker" 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/composites/meta-ad-policy-checker" 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: 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 Ad Policy Checker

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.

When to Use

  • Before launching any new Meta ad
  • After generating ad copy variants (call this on each variant before showing or submitting)
  • When auditing an existing live ad for policy risk
  • When troubleshooting a recently disapproved ad
  • Before pushing copy through any Meta MCP / API write tool

Phase 0: Intake

  1. Advertiser context (1–2 sentences)
    • What the business does
    • What product / service / offer is being advertised
    • Primary conversion goal
  2. Ad asset(s)
    • Headline(s)
    • Primary text / body
    • Description (if applicable)
    • CTA button text
    • Destination URL (optional — enables a landing-page cross-check)
  3. Special Ad Category — declared by user: None / Employment / Credit / Housing / Social Issues, Elections or Politics (this changes the applicable rules significantly)
  4. Targeting summary (optional) — useful for discrimination checks (age, gender, location exclusions)
  5. Visual description (optional) — text-in-image is policy-relevant
  6. Mode — pre-flight (block until clean) or audit (flag-only, used for already-live ads)

Phase 1: Determine Which Policies Apply

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.

Baseline (every ad)

  • Community Standards
  • Personal Attributes
  • Sensational Content
  • Misinformation
  • Engagement Bait / Spam
  • Grammar & Profanity
  • Non-Functional Landing Pages

Content-driven (add when present)

TriggersPolicy lookup keys
Income, earnings, payouts, "make money", specific dollar amountsPersonal financial requirements; unrealistic outcomes
Health, weight loss, supplements, wellness claimsHealth and wellness; before-and-after photos
Targeting by age, gender, race, religion, nationalityDiscriminatory practices
Crypto, weapons, adult, drugs, alcohol, gambling, tobaccoRestricted content
Political, social-issue, election contentSocial issues, elections or politics
Profanity, slurs, sensitive languageProfanity; inflammatory content
Anything that implies tracking / scraping / circumventionCircumventing systems

Category-driven (add based on declared Special Ad Category)

Special Ad CategoryAdd
EmploymentEmployment
CreditCredit
HousingHousing
Social Issues, Elections or PoliticsSocial issues, elections or politics

Output of Phase 1: an ordered list of policy lookup keys to resolve and fetch in Phase 2.

Phase 2: Fetch + Cache Live Policy Text

Fetch Meta's ad-standards index first:

https://transparency.meta.com/policies/ad-standards/

For each lookup key from Phase 1:

  1. Resolve it from the index to Meta's canonical policy page URL. Prefer exact title matches, then closest title / category matches.
  2. Fetch the resolved canonical URL. Do not build a URL by appending the lookup key directly to the ad-standards base path; those flat URLs 404 for many current policies because Meta nests policy pages under category paths.
  3. Cache the lookup key → canonical URL → page text mapping.

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.

Phase 3: Reason — Ad vs. Policy

For each fetched policy, walk through every element of the ad (headline, body, description, CTA, link, visual description if provided) and ask:

  1. Does any phrase, implication, or pattern in the ad match a restricted pattern in this policy's text?
  2. What specific clause from the policy applies? Pull the direct quote.
  3. What is the severity?

Severity model — three levels:

SeverityDefinition
BlockClear violation. Ad will almost certainly be disapproved. Do not submit until fixed.
Fix RequiredLikely violation or explicit risk. Ad may pass but is at meaningful risk of disapproval or under-delivery. Fix recommended before submission.
CautionEdge case. Ambiguous wording or pattern Meta sometimes flags. Worth knowing about; not necessarily worth changing.

For each issue identified, produce:

  • Issue — exact phrase or pattern in the ad
  • Policy — name + URL
  • Citation — direct quote from Meta's policy page
  • Severity — one of the three above
  • Why — one-line explanation grounding the call in the cited policy text
  • Suggested rewrite — preserves the advertiser's intent, removes the risk

Phase 4: Landing-Page Cross-Check (if URL provided)

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:

  • Are the claims made in the ad reflected on the LP?
  • Are required disclosures present (terms, eligibility, conditions)?
  • Does the LP make any claim that, if it were on the ad, would be flagged?
  • Is the LP functional (load, render, no broken redirects)? — this is a separate Meta policy (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.

Phase 5: Produce the Output

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

Phase 6: Integration Hooks

This skill is built to be both standalone-runnable and callable from other skills. Recommended chain patterns:

  • Variant generation: messaging-ab-tester produces N variants → meta-ad-policy-checker runs on each → only PASS / FIX REQUIRED variants surface to the user
  • Campaign launch: meta-ads-campaign-builder produces a brief with multiple ads → meta-ad-policy-checker runs on every ad → block launch if any return BLOCK
  • Pre-write gate: before any tool call that writes to Meta (via MCP, native API, or otherwise), the calling workflow checks the verdict and aborts on BLOCK
  • Diagnostic on under-delivery: meta-ads-analyzer flags an ad with near-zero delivery → suggest running meta-ad-policy-checker to rule out a silent disapproval

The skill returns structured output (verdict + per-issue array) so calling code can gate on verdict !== "BLOCK" programmatically.

Output Standards (Mandatory)

  • Cite, don't paraphrase. Every finding includes a direct quote from Meta's policy page. If you can't quote, the finding isn't grounded — drop it.
  • Severity is a calibration, not a guess. A clear, specific match to a "you may not" clause in the policy = Block. An "ambiguous but risky" match = Fix Required. An edge case Meta sometimes flags but often doesn't = Caution.
  • Rewrites preserve intent. A rewrite that changes the offer or the audience is not a rewrite — it's a different ad. Rewrites change how the offer is expressed, not what it is.
  • Don't replace Meta's review. This is pre-flight; Meta is final gatekeeper. If a rewrite still gets disapproved, that's information for the next iteration — log it.
  • Echo the advertiser context. Always restate what was assumed, so the user can correct misinterpretation.

What This Skill Will Not Do

  • Won't replace Meta's actual ad review. Meta is the final gatekeeper. This catches the obvious and the well-documented; Meta enforcement evolves.
  • Won't read images for text. Text-in-image violations need a separate vision pass; out of scope for v1. The skill will reason about visual descriptions if provided.
  • Won't determine Special Ad Category eligibility. The user declares the category. Whether the ad should be in that category is a separate (legal/business) judgment.
  • Won't enforce the BLOCK. It produces a verdict; the calling skill, workflow, or human enforces the gate.
  • Won't track historical disapprovals on your account. Account-level history affects Meta's review, but isn't visible to this skill. Treat the verdict as the floor of risk, not the ceiling.

Maintenance Note

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.

Related Skills

  • messaging-ab-tester — runs upstream; generates variants this skill should check
  • meta-ads-campaign-builder — runs upstream; produces multi-ad briefs this skill should validate before launch
  • ad-to-landing-page-auditor — paired pre-flight; different concern (message-match vs. policy compliance), same checkpoint
  • meta-ads-analyzer — runs downstream; if a live campaign shows symptoms of a silent disapproval (near-zero delivery, throttling), this skill is the diagnostic step
  • ad-campaign-analyzer — loose link; disapprovals show up as underdelivery in performance data, so cross-reference when a creative shows zero delivery

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