Agent skill

Product Meaning Extractor

by AnastasiyaW in AnastasiyaW/codex-claude-code-config

Deep product analysis before creating videos, presentations, or ads.

MITAuto-check passedMedia & Creative

Install Product Meaning Extractor

skills CLI
$ npx skills add AnastasiyaW/codex-claude-code-config --skill product-meaning-extractor -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install AnastasiyaW/codex-claude-code-config product-meaning-extractor --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/AnastasiyaW/codex-claude-code-config.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/video-production/product-meaning-extractor .claude/skills/product-meaning-extractor && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
product-meaning-extractor
GitHub stars
154
Token cost
~2.7k tokens
SKILL.md length
766 words
Files
1
Skills in repo
50
Repo updated
First seen
Licence
MIT

At a glance

Deep product analysis before creating videos, presentations, or ads.

  • Works in 4 steps: Gather Raw Material → The "So What?" Test → Fill the Product Brief → …
  • : analyze product
  • SKILL.md covers Why This Exists, Process, Anti-Patterns and Frameworks Reference, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Product Meaning Extractor is an agent skill from AnastasiyaW/codex-claude-code-config. Deep product analysis before creating videos, presentations, or ads. Use when: 'analyze product', 'extract value', 'product brief', 'what makes this product special', 'prepare brief', 'understand the product', 'video brief'. Takes a URL or product description and outputs a structured brief with core insight, enemy, transformation, proof, mechanism, and emotional hooks. Based on JTBD, StoryBrand, Obviously Awesome (April Dunford), and Value Proposition Canvas frameworks. Do NOT use for writing the script or scene…

Its SKILL.md is about 2.7k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Media & Creative, covering Video production, Copywriting and User stories. It works with Remotion. The repository describes itself as: Claude Code, Codex, and multi-agent configuration system: principles, hooks, skills, and workflow patterns for AI-assisted development. The licence is MIT.

When your agent uses it

  • : analyze product
  • What makes this product special
  • Understand the product
  • Writing the script

Example prompts

  • “analyze product”
  • “extract value”
  • “product brief”
  • “/product-meaning-extractor”

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. Gather Raw Material
  2. The "So What?" Test
  3. Fill the Product Brief
  4. Brief Validation Checklist

What it can do on your machine

Read from SKILL.md and the folder at commit 67709af. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • strategyzer.com
    • ftc.gov

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Product Meaning Extractor loads about 2.7k tokens when it runs. Until then it costs about 187 tokens; SKILL.md has 766 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~187
When it runs · the whole SKILL.md, loaded when a task matches
~2.7k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from AnastasiyaW/codex-claude-code-config at commit 67709af, republished under its MIT licence (© AnastasiyaW). 766 words, ~2,671 tokens.

Download SKILL.mdSave it as .claude/skills/product-meaning-extractor/SKILL.md (or your agent's skills folder).
name
product-meaning-extractor
description
Deep product analysis before creating videos, presentations, or ads. Use when: 'analyze product', 'extract value', 'product brief', 'what makes this product special', 'prepare brief', 'understand the product', 'video brief'. Takes a URL or product description and outputs a structured brief with core insight, enemy, transformation, proof, mechanism, and emotional hooks. Based on JTBD, StoryBrand, Obviously Awesome (April Dunford), and Value Proposition Canvas frameworks. Do NOT use for writing the script or scene timing (use video-narrative-arc), scoring an existing script (use script-evaluator), or rendering video (use remotion-production-guide); this is the upstream brief-only step before any script is written.

Product Meaning Extractor

Extract the REAL value from a product before writing a single line of video/presentation code. Without this step, content is a flat list of features. With it, content tells a story.

Why This Exists

A feature list alone may not explain why the product matters to this audience. Product analysis connects capabilities to a relevant, supportable customer outcome; it does not guarantee engagement.

This skill forces you to find what actually matters: the enemy, the transformation, the mechanism, and the emotional hook. Everything else flows from these.

Process

Step 1: Gather Raw Material

From the product URL:

  1. Visit the site, extract ALL text (hero, features, pricing, about, FAQ)
  2. Screenshot key visuals (hero, before/after, product shots)
  3. Extract brand colors from CSS (--primary, --accent, meta theme-color)
  4. Note the tone: formal/casual, technical/simple, premium/accessible

From reviews/testimonials (if available):

  1. Find testimonials on the site itself
  2. Check App Store / Product Hunt / G2 / Trustpilot / Reddit mentions
  3. Extract relevant VERBATIM customer phrases with their source, author/context, and date. Do not turn a paraphrase or invented phrase into a customer quotation.

Evidence travels with the brief: For each factual number, capability, comparison, customer name, or testimonial, retain the source URL/file and relevant scope/date. Separate verified observations, attributed vendor claims, and hypotheses. Examples below illustrate a structure, not facts about the current product. If evidence is missing, use [needs data], omit the claim, or write a clearly labelled hypothesis; continue the useful brief without inventing proof to fill a field.

Step 2: The "So What?" Test

For EVERY feature on the site, ask "So what?" until you reach the real value. Most features need 3-4 "so what?" iterations:

Feature: "Outputs .PSD with layers"
So what? → "You can edit individual elements"
So what? → "You don't redo the whole job if one thing is wrong"
So what? → "It saves hours of re-work and frustration"
REAL VALUE: "Never redo work from scratch again"
Feature: "AI-powered analysis"
So what? → "It finds patterns humans miss"
So what? → "Decisions are based on data, not gut feeling"
So what? → "You stop guessing and start knowing"
REAL VALUE: "Confidence in every decision"

Do this for every feature. Most products have 3-4 real values buried under 10+ feature bullets.

Step 3: Fill the Product Brief

Output this structured brief (fill EVERY field, mark unknowns as [needs data]):

markdown
# Product Brief: [Product Name]

## Core Insight
[One sentence: WHY does this product exist? Not what it does - why the world needs it.
Test: remove the product name. If the sentence still makes sense, it's good.
BAD: "ProductX uses AI to optimize workflows" (about the product)
GOOD: "Creative teams shouldn't choose between speed and quality" (about the world)]

## Enemy
[What is specifically bad without this product? Be concrete and visceral.
BAD: "Manual work is time-consuming"
GOOD: "Retouchers spend 45 minutes per photo removing scratches pixel by pixel.
       A 200-product catalog = 150 hours of mind-numbing work. Client wants changes? Start over."
The enemy should make the reader think: "yes, that's exactly my problem."]

## Transformation
**Before:** [A specific "day in the life" WITHOUT the product. What does the person DO, FEEL, WASTE?
            Write it as a mini-scene, not a bullet point.]
**After:**  [Same person WITH the product. What changed? Be specific about outcomes AND feelings.]

## Unique Mechanism
[HOW does it solve the problem? The specific approach that makes it different.
BAD: "Uses AI to improve results"
GOOD: "Pixel-level neural retouching that preserves original resolution and DPI,
       outputting editable .PSD with layers - not a flattened, compressed JPG"
The mechanism answers: "Why should I believe this works?"]

## Proof Points
1. [Measured result, if available: source + metric + sample/context + date; retain limitations]
2. [Social proof, if available: source + actual person/company + attributed experience]
3. [Comparison, if available: source + versions/conditions + supported specific advantage]
4. [If no hard data available: mark as [needs data] and suggest what to measure]

## Emotional Hooks (rank top 3)
Pick the strongest emotional transitions for this specific product:
- [ ] Frustration → Relief ("Stop spending hours on...")
- [ ] Fear → Safety ("Never lose quality when...")
- [ ] Chaos → Control ("Finally, one tool that...")
- [ ] Shame → Pride ("Deliver work that...")
- [ ] Scarcity → Abundance ("Unlimited [X] without...")
- [ ] Complexity → Simplicity ("Just upload and...")
- [ ] Slow → Fast ("[X] in seconds, not hours")
- [ ] Expensive → Affordable ("Premium results at...")
- [ ] Isolation → Belonging ("Join [X] teams who...")
- [ ] Ignorance → Insight ("Finally see what...")

## Customer Language Bank
### Pain phrases (how they describe the problem):
- "[verbatim from reviews/testimonials]"
- "[verbatim]" 
- [If no reviews found: optional hypotheses labelled [inferred, not a customer quote]; do not attribute them to a person or use them as testimonials]

### Desire phrases (how they describe the dream state):
- "[verbatim]"

### Objection phrases (what they worried about before buying):
- "[verbatim or inferred]"

## Target Audience (max 3, ranked)
1. [Primary: WHO + their specific context + why they care MOST]
2. [Secondary: ...]
3. [Tertiary: ...]

## Competitive Positioning (April Dunford framework)
- **Competitive alternatives:** [What would they use if product didn't exist?]
- **Unique attributes:** [What can ONLY this product do?]
- **Value:** [What does the unique attribute enable?]
- **Target customer:** [Who cares most about that value?]
- **Market category:** [What frame makes the value obvious?]

## Brand Signals
- **Colors:** [Primary, accent, bg - with hex codes]
- **Tone:** [formal/casual, technical/simple, premium/accessible]
- **Visual style:** [dark/light, minimal/rich, photo-heavy/text-heavy]

## Video Angle Recommendations
### Angle 1: [Name] (best for [15s/30s/60s])
**Hook:** "[Specific opening line using customer pain phrase]"
**Structure:** [Narrative arc: PAS / BAB / Apple Keynote / Before-After]
**Key scene:** [The single most powerful visual moment]
**CTA:** "[Specific call to action]"

### Angle 2: [Name]
...
Step 4: Brief Validation Checklist

Run these checks before using the brief:

  • Core insight doesn't mention the product name (it's about the WORLD, not the product)
  • Enemy is specific enough to make someone say "that's me"
  • Transformation includes FEELINGS, not just features
  • Mechanism explains HOW, not just "AI-powered"
  • Every factual proof point is source-bound; absent numbers remain absent or [needs data]
  • Actual quotes retain provenance; inferred language is separate and never represented as testimony
  • No more than 3 target audience segments (focus!)
  • At least 2 video angles suggested with different hooks

Anti-Patterns

Anti-PatternWhy It's BadFix
Feature listing"We have X, Y, Z" - nobody cares about featuresUse "So What?" test to find real values
Jargon"Leveraging proprietary algorithms"Use customer words, test: would a friend say this?
Vague enemy"Current solutions are inadequate"Explain the observed problem; add numbers only when supported
Missing mechanism"Better results"HOW better? What's the secret sauce?
No tensionNo enemy = flat contentThe enemy must be REAL and FELT
Generic emotions"Save time"Time for WHAT? "Get home before kid's bedtime"
Company-first"We are the leader in..."Customer-first: "You deserve..."
Show full SKILL.md (266 more words)Show less

Frameworks Reference

JTBD (Jobs-to-be-Done):

  • Functional job: What task are they trying to accomplish?
  • Emotional job: How do they want to feel?
  • Social job: How do they want to be perceived?

StoryBrand (Donald Miller):

  1. Hero (customer) has a Problem
  2. Meets a Guide (your product) with Empathy + Authority
  3. Who gives them a Plan
  4. Calls them to Action
  5. Helps them avoid Failure
  6. And achieve Success

Obviously Awesome (April Dunford): Competitive alternatives → Unique attributes → Value → Target customer → Market category

Value Proposition Canvas (Strategyzer): Customer: Jobs + Pains + Gains ←→ Product: Products + Pain Relievers + Gain Creators

Gotchas

  • Don't skip the "So What?" test - it's where insights hide behind features
  • Customer language > clever copywriting. Always.
  • If you can't find the enemy, the product might not have a clear positioning - flag this
  • Brief should take 10-15 minutes of real analysis. 2-minute briefs are too shallow
  • Update the brief as you learn more during content creation
  • The brief carries evidence into subsequent work (video, ads, slides); it does not outrank the underlying source or turn a hypothesis into a fact.

Troubleshooting

  • No numeric result or testimonial: continue with supported capabilities and explicit unknowns; do not manufacture a metric or speaker to pass the checklist.
  • A later source contradicts the brief: correct the affected claim and downstream copy, retaining the source and scope of the correction.

Source basis

© AnastasiyaW, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/video-production/product-meaning-extractor of AnastasiyaW/codex-claude-code-config.

Open the folder on GitHubat commit 67709af

Compare with similar skills

Product Meaning Extractor next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Product Meaning Extractor compared with similar skills
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HyperFrames Video Entry Pointheygen-com/hyperframes60k3 repos~5.2kAutomated safety check: PassApache-2.0
Writing Docsremotion-dev/remotion63k1 repos~1.9kAutomated safety check: PassCustom licence

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Works with

Questions about Product Meaning Extractor

What does Product Meaning Extractor do?

Deep product analysis before creating videos, presentations, or ads. Product Meaning Extractor is an agent skill from AnastasiyaW/codex-claude-code-config. Deep product analysis before creating videos, presentations, or ads.

When should I use Product Meaning Extractor?

Product Meaning Extractor fits situations like: : analyze product; what makes this product special; understand the product; writing the script.

How do I install Product Meaning Extractor in Claude Code?

Run `npx skills add AnastasiyaW/codex-claude-code-config --skill product-meaning-extractor -a claude-code`. Or copy the skill folder (skills/video-production/product-meaning-extractor in AnastasiyaW/codex-claude-code-config) into .claude/skills/product-meaning-extractor in your project. Claude Code loads it when a task matches its description.

How do I install Product Meaning Extractor in Codex?

Run `npx skills add AnastasiyaW/codex-claude-code-config --skill product-meaning-extractor -a codex`. Or copy the skill folder (skills/video-production/product-meaning-extractor in AnastasiyaW/codex-claude-code-config) into .agents/skills/product-meaning-extractor in your project. Codex loads it when a task matches its description.

Can I use Product Meaning Extractor in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add AnastasiyaW/codex-claude-code-config --skill product-meaning-extractor -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/product-meaning-extractor, .gemini/skills/product-meaning-extractor, .github/skills/product-meaning-extractor and .opencode/skills/product-meaning-extractor in your project.

What does Product Meaning Extractor need to run?

SKILL.md names no scripts, command-line tools or credentials: Product Meaning Extractor is instructions for the agent only.

Does Product Meaning Extractor access the network?

SKILL.md names 2 domains. As links in the text: strategyzer.com and ftc.gov. This is read from the text; nothing was executed.

Is Product Meaning Extractor safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Product Meaning Extractor use?

Product Meaning Extractor is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Product Meaning Extractor use?

About 2.7k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Product Meaning Extractor?

Skills that share tags, products or a category with Product Meaning Extractor: Motion Video in Remotion (ooiyeefei/ccc, 495 stars), Stitch to Remotion Walkthrough Videos (google-labs-code/stitch-skills, 8.5k stars), Video Shotcraft (Vincentwei1021/video-shotcraft, 11k stars) and HyperFrames Video Entry Point (heygen-com/hyperframes, 60k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Product Meaning Extractor?

AnastasiyaW (a GitHub user) maintains it in AnastasiyaW/codex-claude-code-config, which has 154 GitHub stars. The repository holds 50 skills in this directory. The repository was last updated on October 9, 2026.

Source: AnastasiyaW/codex-claude-code-config on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.