Motion Video in Remotion
ooiyeefei/ccc
Builds marketing and explainer videos in Remotion from rendered scenes, with one real product capture as proof, and cuts them for each platform's formats.
Deep product analysis before creating videos, presentations, or ads.
$ npx skills add AnastasiyaW/codex-claude-code-config --skill product-meaning-extractor -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install AnastasiyaW/codex-claude-code-config product-meaning-extractor --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ 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-srcUse ~/.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/
Install the "product-meaning-extractor" agent skill from https://github.com/AnastasiyaW/codex-claude-code-config/tree/main/skills/video-production/product-meaning-extractor into .claude/skills/product-meaning-extractor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "product-meaning-extractor", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/AnastasiyaW/codex-claude-code-config/tree/main/skills/video-production/product-meaning-extractorType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add AnastasiyaW/codex-claude-code-config --skill product-meaning-extractor -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install AnastasiyaW/codex-claude-code-config product-meaning-extractor --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/AnastasiyaW/codex-claude-code-config.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/video-production/product-meaning-extractor .agents/skills/product-meaning-extractor && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "product-meaning-extractor" agent skill from https://github.com/AnastasiyaW/codex-claude-code-config/tree/main/skills/video-production/product-meaning-extractor into .agents/skills/product-meaning-extractor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "product-meaning-extractor", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add AnastasiyaW/codex-claude-code-config --skill product-meaning-extractor -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install AnastasiyaW/codex-claude-code-config product-meaning-extractor --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/AnastasiyaW/codex-claude-code-config.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/video-production/product-meaning-extractor .cursor/skills/product-meaning-extractor && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "product-meaning-extractor" agent skill from https://github.com/AnastasiyaW/codex-claude-code-config/tree/main/skills/video-production/product-meaning-extractor into .cursor/skills/product-meaning-extractor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "product-meaning-extractor", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/AnastasiyaW/codex-claude-code-config.git --path skills/video-production/product-meaning-extractor--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add AnastasiyaW/codex-claude-code-config --skill product-meaning-extractor -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install AnastasiyaW/codex-claude-code-config product-meaning-extractor --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/AnastasiyaW/codex-claude-code-config.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/video-production/product-meaning-extractor .gemini/skills/product-meaning-extractor && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "product-meaning-extractor" agent skill from https://github.com/AnastasiyaW/codex-claude-code-config/tree/main/skills/video-production/product-meaning-extractor into .gemini/skills/product-meaning-extractor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "product-meaning-extractor", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install AnastasiyaW/codex-claude-code-config product-meaning-extractorInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add AnastasiyaW/codex-claude-code-config --skill product-meaning-extractor -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/AnastasiyaW/codex-claude-code-config.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/video-production/product-meaning-extractor .github/skills/product-meaning-extractor && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "product-meaning-extractor" agent skill from https://github.com/AnastasiyaW/codex-claude-code-config/tree/main/skills/video-production/product-meaning-extractor into .github/skills/product-meaning-extractor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "product-meaning-extractor", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add AnastasiyaW/codex-claude-code-config --skill product-meaning-extractor -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install AnastasiyaW/codex-claude-code-config product-meaning-extractor --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/AnastasiyaW/codex-claude-code-config.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/video-production/product-meaning-extractor .opencode/skills/product-meaning-extractor && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "product-meaning-extractor" agent skill from https://github.com/AnastasiyaW/codex-claude-code-config/tree/main/skills/video-production/product-meaning-extractor into .opencode/skills/product-meaning-extractor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "product-meaning-extractor", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
product-meaning-extractorDeep 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. 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.
4 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 67709af. It shows what the files ask for, not the result of running them.
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.
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.
Links to these hosts (documentation or services it may open):
strategyzer.comftc.govFrom URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
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.
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.
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.
The full file from AnastasiyaW/codex-claude-code-config at commit 67709af, republished under its MIT licence (© AnastasiyaW). 766 words, ~2,671 tokens.
.claude/skills/product-meaning-extractor/SKILL.md (or your agent's skills folder).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.
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.
From the product URL:
--primary, --accent, meta theme-color)From reviews/testimonials (if available):
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.
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.
Output this structured brief (fill EVERY field, mark unknowns as [needs data]):
# 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]
...Run these checks before using the brief:
[needs data]| Anti-Pattern | Why It's Bad | Fix |
|---|---|---|
| Feature listing | "We have X, Y, Z" - nobody cares about features | Use "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 tension | No enemy = flat content | The 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..." |
JTBD (Jobs-to-be-Done):
StoryBrand (Donald Miller):
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
© AnastasiyaW, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in skills/video-production/product-meaning-extractor of AnastasiyaW/codex-claude-code-config.
Open the folder on GitHubat commit 67709af
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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Product Meaning Extractor this skillAnastasiyaW/codex-claude-code-config | 154 | — | ~2.7k | Automated safety check: Pass | MIT | |
| Motion Video in Remotionooiyeefei/ccc | 495 | — | ~2.9k | Automated safety check: Pass | MIT | |
| Stitch to Remotion Walkthrough Videosgoogle-labs-code/stitch-skills | 8.5k | 6 repos | ~3.2k | Automated safety check: Notes | Apache-2.0 | |
| Video ShotcraftVincentwei1021/video-shotcraft | 11k | — | ~2.6k | Automated safety check: Pass | Apache-2.0 | |
| HyperFrames Video Entry Pointheygen-com/hyperframes | 60k | 3 repos | ~5.2k | Automated safety check: Pass | Apache-2.0 | |
| Writing Docsremotion-dev/remotion | 63k | 1 repos | ~1.9k | Automated safety check: Pass | Custom licence |
ooiyeefei/ccc
Builds marketing and explainer videos in Remotion from rendered scenes, with one real product capture as proof, and cuts them for each platform's formats.
google-labs-code/stitch-skills
Builds walkthrough videos from Stitch design projects using Remotion, with transitions, zoom effects and text overlays on each screen.
Vincentwei1021/video-shotcraft
Makes cinematic product videos with Remotion from shot recipe cards, a ready template, real page screenshots, camera moves and sound design, or builds a single animated shot.
heygen-com/hyperframes
Entry point for making, editing and rendering videos from HTML compositions with HyperFrames, routing each request to the right workflow.
remotion-dev/remotion
Guides for writing and editing Remotion documentation. An agent skill from remotion-dev/remotion.
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Works with
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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.
Product Meaning Extractor fits situations like: : analyze product; what makes this product special; understand the product; writing the script.
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.
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.
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.
SKILL.md names no scripts, command-line tools or credentials: Product Meaning Extractor is instructions for the agent only.
SKILL.md names 2 domains. As links in the text: strategyzer.com and ftc.gov. This is read from the text; nothing was executed.
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.
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.
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.
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.
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.