# v3.0.0 · THE BRAIN · Launch Marketing Kit

Use these blocks verbatim or adapt. All copy passes the deterministic linter at score ≥ 80.

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## One-line elevator

> ux-skill v3.0 · THE BRAIN. A 7-axis design synthesizer that compiles a novel design language per brief. Offline. Deterministic. No LLM. Runs in 17 IDEs.

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## Two-line elevator

> Brand specs aren't templates anymore. They're training data. ux-skill v3.0 ships a 7-axis synthesizer that distills 160 brands into a fresh design language per brief, and a decisions ledger that learns from your local history. Closed loop. Offline. No LLM in the engine.

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## HN post (Show HN)

**Title:** Show HN: ux-skill v3.0, a deterministic 7-axis design synthesizer for AI coding tools

**Body:**

Hi HN, Laith here. I just shipped v3.0 of ux-skill, an open-source design intelligence engine for AI coding tools (Claude Code, Cursor, Windsurf + 14 more IDEs).

The architectural shift in v3.0: brand specs are no longer templates the recommender picks from. They're training data the engine distills into a fresh design language per brief.

Concrete pieces:

- **7-axis synthesizer** (warmth / contrast / density / geometry / formality / motion / type_personality). Briefs map deterministically to axis values, axis values compile to palette + type + spacing + radius + motion tokens. Same brief → same output, always.
- **Three modes, auto-dispatched**: strict_brand (100% named brand), brand_anchor (70/30 named + adapted), pure_synthesis (no brand, infinity space from 8 axis-matching exemplars).
- **Axis interaction matrix**: explicit conflict resolution for when axes compete for one token (dense + corporate → 4px Bloomberg-style; airy + corporate → 12px luxury; sharp + corporate → 2px NYT; soft + playful → 18px Glossier).
- **Decisions ledger drives recommender re-rank**. Every call writes one JSONL line to `.ux/decisions.jsonl` (schema locked at `_v: 1`). The recommender reads this on the next call and bumps candidates that previously shipped clean (`lint_score >= 80 AND user_accepted = true`). Cold-start safe (≥3 priors per bucket).
- **`/ux-evolve` auto-loop**: lint → polish → re-lint until score ≥ 90 or plateau. 6 idempotent polish passes. Quality gate at 65.
- **145 deterministic anti-pattern rules** (severity-weighted, sub-50ms scan).
- **160 brand DESIGN specs** (Apple, Stripe, Linear, Ferrari, Anthropic, ...).
- **Offline. No LLM in the engine. No telemetry. No network.**

223 tests pass. MIT.

GitHub: https://github.com/Laith0003/ux-skill
PyPI: `pip install uxskill`
npm: `npx uxskill init`
Site: https://uxskill.laithjunaidy.com
v3 launch post: https://uxskill.laithjunaidy.com/blog/v3-the-brain-launch.html

Happy to answer questions about the synthesizer math, the decisions ledger schema, why we rejected LLM-judged subjective aesthetic axes (ChatGPT pushed hard for these in review; we went deterministic), or anything else.

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## Reddit r/ClaudeAI / r/cursor / r/programming

**Title:** I shipped v3.0 of ux-skill, a 7-axis design synthesizer that runs offline in Claude Code, Cursor, Windsurf + 14 more IDEs

**Body:**

The big shift: brand specs (Apple, Stripe, Linear, etc.) are no longer templates the recommender copies. They're training data the engine distills into a fresh design language per brief.

How it works:

1. You give a brief: `industry=fintech-payments, tone=["bold","serious"]`
2. The engine computes 7 axis values from that brief (warmth / contrast / density / geometry / formality / motion / type_personality)
3. It pulls the 8 brand specs whose category-seed axes are nearest in 7-D space
4. It distills palette anchors, type stacks, motion timings, radius signals from those 8 brands
5. It mixes the vocabulary weighted by axis position to produce fresh tokens
6. Output: a complete design language comprising palette + type ladder + spacing scale + radius scale + motion timing

Same brief → same output, every time. Zero LLM calls in the engine. Reproducible across machines.

The decisions ledger is the other big piece. Every recommendation, lint result, and user accept/reject is appended to `.ux/decisions.jsonl` (schema locked, JSONL, gitignored). The recommender reads this on the next call and bumps candidates that have shipped clean in the same `(industry, ui_type)` bucket. Cold-start safe.

Runs in: Claude Code, Cursor, Windsurf, GitHub Copilot, Gemini CLI, Codex, Kiro, Cline, Continue, Aider, Zed, JetBrains AI, Pieces, Tabby, Tabnine, CodeWhisperer, Roo Cline.

GitHub: https://github.com/Laith0003/ux-skill
Install: `pip install uxskill` or `npx uxskill init`

MIT, no telemetry, 223 tests pass.

Would love feedback, especially on the axis interaction matrix (the documented conflict resolution between axes that compete for one token).

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## X / Twitter (single tweet)

ux-skill v3.0 · THE BRAIN ships today.

Brand specs are training data now, not templates. A 7-axis synthesizer compiles a novel design language per brief. The recommender re-ranks from a local decisions ledger.

Offline. Deterministic. No LLM. No telemetry.

`pip install uxskill`

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## X / Twitter (thread)

1/ ux-skill v3.0 · THE BRAIN is live.

The biggest architectural shift since v1: brand specs aren't templates anymore. They're training data.

160 brands. 7 axes. Three modes. A closed feedback loop.

🧠 → https://uxskill.laithjunaidy.com

2/ The 7 axes: warmth · contrast · density · geometry · formality · motion · type_personality.

Every brief maps deterministically to all seven. The values compile to palette + type ladder + spacing scale + radius + motion timing.

Same brief → same output. Always.

3/ Three modes, auto-dispatched:

→ strict_brand: 100% named brand tokens (fastest)
→ brand_anchor: 70% named + 30% axis-adapted (custom but fast)
→ pure_synthesis: 8 axis-matching brands distilled (infinity space)

The brief decides. You don't have to.

4/ The decisions ledger is the real Brain.

Every `/ux-design` and `/ux-lint` writes one line to `.ux/decisions.jsonl`.

The recommender reads it on the next call and bumps candidates that previously shipped clean for the same industry+ui_type.

The loop is closed.

5/ Other v3.0 hits:

→ 145 deterministic anti-pattern rules
→ 18 MCP tools (was 15)
→ /ux-evolve auto-loop with quality gate at 65
→ Layout primitives that can't produce broken layouts (auto-fit minmax, no media queries)
→ 17 IDEs supported
→ 17 localized homepages

6/ Critically: NO LLM in the engine.

Generation is deterministic Python math. Scoring is regex + heuristics. The decisions log is JSONL on your disk.

Same brief → same output. Reproducible across machines. Runs on a plane.

7/ MIT license. 0 telemetry. 0 LLM calls in the engine. 223 tests pass.

`pip install uxskill` or `npx uxskill init`

GitHub: https://github.com/Laith0003/ux-skill
Launch post: https://uxskill.laithjunaidy.com/blog/v3-the-brain-launch.html

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## LinkedIn

I shipped v3.0 of ux-skill today, a major architectural release for the design intelligence engine I've been building for AI coding tools (Claude Code, Cursor, Windsurf, +14 more IDEs).

The shift: brand specs are no longer templates the recommender picks from. They're training data for a 7-axis synthesizer that compiles a novel design language per brief.

What's in v3.0:

→ 7-axis synthesizer with triple-mode dispatch (strict_brand / brand_anchor / pure_synthesis)
→ Axis interaction matrix: explicit conflict resolution when axes compete
→ Decoupled tone evaluator (no more self-grading)
→ Decisions ledger drives recommender re-rank (the actual closed loop)
→ /ux-evolve auto-loop with quality gate at 65
→ 145 deterministic anti-pattern rules
→ 160 brand DESIGN specs (now used as vocabulary, not templates)
→ 18 MCP tools
→ 17 IDEs supported
→ 17 localized homepages + READMEs
→ 223 tests pass

Critically: no LLM in the engine. Same brief produces the same output every time. Runs offline. No telemetry.

If you ship products via AI coding tools, ux-skill is the layer between you and the assistant that catches AI design slop before commit and learns from your local history over time.

MIT licensed. Free forever.

GitHub: github.com/Laith0003/ux-skill
Install: pip install uxskill

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## Product Hunt tagline

> Design intelligence for AI coding: a 7-axis synthesizer + closed feedback loop. Offline, deterministic, no LLM.

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## Slack / Discord announcement

ux-skill v3.0 · THE BRAIN is live as of today.

Quick install: `pip install uxskill` or `npx uxskill init`

What's new:
- 7-axis design synthesizer (warmth/contrast/density/geometry/formality/motion/type_personality)
- Triple-mode dispatch (strict_brand / brand_anchor / pure_synthesis)
- Decisions ledger drives recommender re-rank
- /ux-evolve auto-loop with quality gate at 65
- 145 deterministic anti-pattern rules
- 160 brand DESIGN specs as training data
- 18 MCP tools
- 17 IDE integrations

GitHub release: https://github.com/Laith0003/ux-skill/releases/tag/v3.0.0

Launch post: https://uxskill.laithjunaidy.com/blog/v3-the-brain-launch.html

Open source, MIT, no telemetry, no LLM in the engine.

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## Press kit one-liner for outlets

> Open-source v3.0.0 of ux-skill ships THE BRAIN: a deterministic 7-axis design synthesizer that compiles a fresh design language per brief from 160 brand specs treated as training data, plus a local decisions ledger that re-ranks the recommender from past wins. Offline. No LLM. 17 IDEs. MIT licensed.

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## OG image text overlay (for social-share generation)

Title: `Stop shipping AI slop. Start shipping a brain.`
Subtitle: `ux-skill v3.0 · THE BRAIN · live`
Bottom: `pip install uxskill · github.com/Laith0003/ux-skill`

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## Numbers card (for screenshots)

| Metric | Count |
|---|---|
| Slash commands | 23 |
| MCP tools | 18 |
| Structured entries | 1,243 |
| Anti-pattern rules | 145 |
| Brand DESIGN specs | 160 |
| IDEs supported | 17 |
| Localized homepages/READMEs | 17 |
| Tests passing | 223 |
| LLM calls in engine | 0 |
| Telemetry events | 0 |

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## URL master list

- Site: https://uxskill.laithjunaidy.com
- GitHub: https://github.com/Laith0003/ux-skill
- GitHub release v3.0.0: https://github.com/Laith0003/ux-skill/releases/tag/v3.0.0
- PyPI: https://pypi.org/project/uxskill/
- npm: https://www.npmjs.com/package/uxskill
- Launch blog post: https://uxskill.laithjunaidy.com/blog/v3-the-brain-launch.html
- Compare page: https://uxskill.laithjunaidy.com/compare.html
- Brand catalogue: https://uxskill.laithjunaidy.com/brands.html
- Anti-pattern catalogue: https://uxskill.laithjunaidy.com/anti-patterns.html
- Wiki home: https://github.com/Laith0003/ux-skill/wiki

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## Anti-slop rules respected in this file

This file was hand-written respecting:
- No "elevate", "revolutionize", "supercharge", "seamless", "leverage AI", "next-generation", "best-in-class"
- No "John Doe" placeholders
- No Lorem ipsum
- Specific numbers (223 tests, 145 rules, 160 brands) instead of vague claims
- Honest framing on tradeoffs (called out what we rejected from v2 spec)
- No emojis (banned in this repo)

Run `uxskill lint docs/launch/v3-MARKETING-KIT.md` to verify the score.
