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Review Audit

  • 355 installs
  • 146 repo stars
  • Updated June 11, 2026
  • motion-team/creative-strategy-skills

review-audit is an agent skill that analyzes customer reviews to extract voice-of-customer insights and ad-ready language for developers building messaging strategy from real customer feedback.

About

review-audit is an agent skill from motion-team/creative-strategy-skills that analyzes positive customer reviews to surface voice-of-customer insights for ad copy and messaging strategy. The skill organizes output by product when multiple are present and buckets findings into pain points, trigger moments, objections, transformation outcomes, and ad-ready language. Developers reach for review-audit when users provide review text and ask for VOC analysis, customer language mining, or creative strategy inputs. Triggers include phrases like analyze these reviews, what are customers saying, and find insights in these reviews.

  • Brand alignment check
  • Messaging critique
  • Audience fit review
  • Channel consistency
  • Creative gap analysis

Review Audit by the numbers

  • 355 all-time installs (skills.sh)
  • +9 installs in the week ending Aug 4, 2026 (Skillselion tracking)
  • Ranked #722 of 1,880 Design & UI/UX skills by installs in the Skillselion catalog
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
npx skills add https://github.com/motion-team/creative-strategy-skills --skill review-audit

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Listed on Skillselion
Installs355
repo stars146
Last updatedJune 11, 2026
Repositorymotion-team/creative-strategy-skills

How do you extract VOC insights from customer reviews?

Audit creative strategy, messaging, and brand assets before build so campaigns and product surfaces align with audience, positioning, and channel goals.

Who is it for?

Developers and marketers turning raw customer reviews into structured VOC insights and ad copy inputs before campaign or landing page work.

Skip if: Developers who need codebase architecture docs, GA4 traffic reports, or fund compliance validation instead of review text analysis.

When should I use this skill?

The user provides customer reviews and asks for VOC analysis, review insights, ad-ready language, or messaging strategy from customer feedback.

What you get

Organized review analysis with pain points, trigger moments, objections, transformation outcomes, and ad-ready customer language by product.

  • VOC insight report
  • Ad-ready customer language
  • Messaging strategy inputs

By the numbers

  • Organizes review insights into 5 buckets: pain points, trigger moments, objections, transformation, and ad-ready languag

Files

SKILL.mdMarkdownGitHub ↗

Review Audit

This system mines positive customer reviews to extract the insights that make ad copy actually work — the real language, real pain, real moments, and real transformations that customers experienced. The output feeds directly into creative strategy and hook writing.

The goal is not to summarize reviews. The goal is to find the raw material for ads.

---

What You Need Before Starting

Reviews can be provided in any format:

  • Pasted directly into the chat
  • CSV or spreadsheet upload
  • Copy/pasted from a document

If multiple products are present in the review set, identify them before beginning. All output is separated by product.

If the format is unclear or product attribution is ambiguous, ask before proceeding.

---

Step 1: Group by Product

If the brand sells multiple products, sort all reviews by product first. Every subsequent step runs separately per product.

If all reviews are for a single product, skip grouping and proceed.

---

Step 2: Score Review Quality (1–5)

Before analysis, score every review for quality. This determines what gets analyzed and what gets discarded.

ScoreWhat it looks like
1Garbage — gibberish, swear words, 2–3 meaningless words, zero signal ("great product", "love it", "👍")
2Low signal — very short, vague, no specific detail or emotion
3Moderate — mentions the product, some specificity, but no vivid detail or emotional depth
4High quality — specific, describes a real experience, references a before/after or a feeling
5Gold — long, emotional, vivid, paragraph-level detail; the customer was so moved they wrote an essay about it

Score 5 reviews are the priority. They contain the most usable language and the deepest insight.

---

Step 3: Filter

Discard all reviews scored 1. Do not include them in analysis.

Analyze scores 2–5, with emphasis on 4s and 5s. Low-scoring reviews (2–3) can contribute to pattern identification but should not be the source of pulled quotes.

---

Step 4: Extract Insights by Bucket

Run this analysis separately for each product. Within each bucket, group similar insights together and write a brief summary of the pattern. Then pull the best word-for-word quotes that exemplify it.

Do not editorialize the quotes. Pull them exactly as written.

---

Bucket 1: Pain Points

What problem were they experiencing before they found this product?

Look for: descriptions of the problem they had, how long they'd had it, what they'd tried before, how it affected their life, the emotional weight of living with it.

For each pain theme identified:

  • Name the theme
  • Write a 2–3 sentence summary of the pattern across reviews
  • Flag the strongest quotes for the swipe file

---

Bucket 2: Trigger Moments

What finally made them buy?

Look for: the specific moment, event, or realization that pushed them over the edge. This is the thing that turned a maybe into an add-to-cart. It could be a life event (wedding, diagnosis, vacation), a recommendation (friend, doctor, TikTok), hitting a breaking point, or running out of patience with other solutions.

For each trigger theme identified:

  • Name the theme
  • Write a 2–3 sentence summary of the pattern
  • Flag the strongest quotes for the swipe file

---

Bucket 3: Objections Before Purchasing

What almost stopped them from buying?

Look for: skepticism they mention having had, comparisons to other products they'd tried, price hesitation, disbelief that this would actually work, fear of wasting money again.

Note: In positive reviews, objections are almost always mentioned in past tense — "I was skeptical but..." or "I almost didn't try it because..." These are gold for objection-handling ad copy.

For each objection theme identified:

  • Name the theme
  • Write a 2–3 sentence summary of the pattern
  • Flag the strongest quotes for the swipe file

---

Bucket 4: Transformations

What changed for them after using the product?

Look for: the specific result they experienced, how their life is different now, the emotional shift (confidence, relief, freedom, pride), and — most importantly — how they describe the transformation in their own words. The more specific and visceral, the better.

For each transformation theme identified:

  • Name the theme
  • Write a 2–3 sentence summary of the pattern
  • Flag the strongest quotes for the swipe file

---

Bucket 5: Standout Language & Ad-Ready Phrases

Exact language worth stealing for ads.

This bucket is different from the others. It is not organized by theme — it is a curated collection of the most vivid, emotionally charged, specific, and scroll-stopping phrases pulled from across all buckets. These are the lines that made you stop while reading. The ones that don't need to be rewritten. The ones a copywriter would highlight and build an ad around.

Pull these verbatim. Note which product they're from.

What to look for:

  • Unusually specific descriptions of pain or transformation
  • Phrases that capture an emotion in a way you couldn't have written yourself
  • Before/after language that is visceral and concrete
  • Lines that could work as a hook with zero editing
  • Anything that made you feel something while reading it

---

Output Format

Produce a separate full output for each product. Structure:

─────────────────────────────────────
PRODUCT: [Product Name]
Reviews analyzed: [X] | Discarded (score 1): [X]
─────────────────────────────────────

BUCKET 1: PAIN POINTS

[Theme Name]
Summary: [2–3 sentences on the pattern]

[Theme Name]
Summary: [2–3 sentences on the pattern]

---

BUCKET 2: TRIGGER MOMENTS

[Theme Name]
Summary: [2–3 sentences on the pattern]

---

BUCKET 3: OBJECTIONS BEFORE PURCHASING

[Theme Name]
Summary: [2–3 sentences on the pattern]

---

BUCKET 4: TRANSFORMATIONS

[Theme Name]
Summary: [2–3 sentences on the pattern]

---

BUCKET 5: STANDOUT LANGUAGE & AD-READY PHRASES

"[Exact quote]"
"[Exact quote]"
"[Exact quote]"
[etc.]

─────────────────────────────────────

All word-for-word quotes are collected in Bucket 5. Do not scatter quotes throughout buckets 1–4 — keep the summaries clean and let the swipe file be the dedicated place for raw language.

---

How This Feeds the Rest of the Stack

The output of this analysis plugs directly into creative strategy and execution:

  • Pain Points → Creative Strategy Engine — pain buckets map directly to the pain/desire anchor layer
  • Trigger Moments → Hook Writing — trigger moments are often the most powerful hook material; they capture the exact moment of emotional readiness
  • Objections → Hook Writing / Creative Mechanics — objections inform Borrowed Enemy, Reframe, and Risk Reversal mechanics and hook tactics
  • Transformations → Hook Writing — transformation language feeds aspirational and social proof hooks
  • Standout Language → Hook Voice Patterns — the best phrases can be added directly to the swipe file as native voice patterns pulled from real customers

---

Notes on Quality

  • Score 5 reviews should be read in full and treated as primary sources
  • Score 2–3 reviews are useful for pattern confirmation but not quote sourcing
  • If the review set is small (under 20 reviews), note this — patterns may not be statistically meaningful but language is still usable
  • If a product has too few quality reviews to surface meaningful patterns, flag it rather than manufacturing themes that aren't there

Related skills

How it compares

Use review-audit to mine existing customer reviews for language; use copywriting-core to draft new GTM copy from positioning briefs.

FAQ

What insight buckets does review-audit produce?

review-audit surfaces five buckets: pain points, trigger moments, objections, transformation outcomes, and ad-ready language. Output is organized by product when multiple products are present.

What input does review-audit require?

review-audit expects customer review text from the user. The skill analyzes positive reviews to extract VOC insights and phrasing usable in ad copy and messaging strategy.

Design & UI/UXbrandingux

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