About this skill

Ad copy often fails not because it is unclear, but because it crosses legal or brand boundaries before publication. This skill turns pre-launch review into a reusable rule-based workflow: load client data, scan the copy, and emit a structured risk report.

Core capabilities

Checks brand tone, banned words, and platform restrictions against brand.md and banned_words.md
Flags common ad-law risks such as absolute claims and medical effect implications
Uses scripts/review.py to output matched terms, risk type, severity, and replacement suggestions
Can optionally call an LLM to generate a rewrite that removes violations while preserving intent
Supports batch HTML reports via generate_report.py or webapp.py

Boundaries

The default engine is keyword + regex matching, not full semantic understanding, so rephrased violations may be missed
--client must point to a client directory containing brand.md and banned_words.md
generate_report.py processes input as one ad per line by default, so multi-line ads may need different handling
Only .txt and .md text are supported; Word, PDF, and images must be exported to plain text first

Screenshots

Use Cases

An ads ops person checks promo copy for absolute claims and medical-implication wording before launch
A client manager reviews new beauty-client copy against brand.md and banned_words.md for tone and banned terms
A sales team scans past client ads with generate_report.py and produces an HTML compliance report
A content lead plugs review.py into the submission workflow to flag violations and suggest replacements

Best For

Ads ops who must verify promo copy against ad-law and platform rules before launch
Client managers who need copy checked against brand red lines with replacement suggestions
Sales or presales teams who want client ad-risk data packaged into sendable HTML reports
Content leads who want to embed compliance checks into submission or review workflows

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