meta-ad-policy-checker

meta-ad-policy-checker is a skill for Claude Code, Codex from gooseworks-ai/goose-skills. It costs 52 tokens per session (2,804 once invoked), scanned A, original, MIT.

A pre-submission checker for Meta advertising, using Meta's current published policies to assess ad copy and advertiser details.

In plain words
What is it for?
Use it to receive a Pass, Fix Required, or Block result, understand policy issues, and revise ad copy.
Why use it?
It helps identify wording or claims that could cause an ad to be rejected before the campaign is submitted.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to receive a Pass, Fix Required, or Block result, understand policy issues, and revise ad copy.

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Install with agentmods
npx agentmods add skills/gooseworks-ai/goose-skills/meta-ad-policy-checker
About the project

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.

gooseworks-ai/goose-skills · 1,202 stars · on GitHub · gooseworks.ai

Install

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.

Any agent
npx skills add gooseworks-ai/goose-skills --skill meta-ad-policy-checker
Clone the repo
git clone --depth 1 https://github.com/gooseworks-ai/goose-skills

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for meta-ad-policy-checker

README.md
[![agentmods](https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/meta-ad-policy-checker/github.svg)](https://agentmods.dev/skills/gooseworks-ai/goose-skills/meta-ad-policy-checker)
Your own site
<a href="https://agentmods.dev/skills/gooseworks-ai/goose-skills/meta-ad-policy-checker"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/meta-ad-policy-checker/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.

agentmods 80×15 button for meta-ad-policy-checker

Your own site · 80×15
<a href="https://agentmods.dev/skills/gooseworks-ai/goose-skills/meta-ad-policy-checker"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/meta-ad-policy-checker.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 52 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,804 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00052 $0.02804
Opus 5 $0.00026 $0.01402
Sonnet 5 $0.00010 $0.00561
Haiku 4.5 $0.00005 $0.00280

Measured 13d ago against content hash 2777e69baa43, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

meta-ad-policy-checker 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.

skills/ads/composites/meta-ad-policy-checker/SKILL.md · 205 lines

How it starts

The opening of the file, as written. The whole thing — 205 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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. Modepre-flight (block until clean) or audit (flag-only, used for already-live ads)

Read the full file on GitHub · 205 lines

Files

What ships with it

1 file 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.

Changes

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.

  1. 13d ago First seen · 205 lines · 52 tokens per session scan A 2777e69baa43

Subscribe to this mod's changes

meta-ad-policy-checker is a skill published in the GitHub repository gooseworks-ai/goose-skills (1,202 stars, last pushed 11d ago), licensed MIT. It adds 52 tokens to every session and 2,804 once invoked, about $0.0003 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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