optimize-commands

name	optimize-commands
description	Ultra-fast token-efficient execution. token-turbo + caveman + parallel blast + multi-model routing. Active by default — no command needed.
allowed-tools	Read, Grep, Glob, Bash, WebFetch, WebSearch, Write, Agent

optimize-commands — Always-On Default Behavior v3.0

No command needed. Active every session from first prompt.

MULTI-LLM BURST — DEFAULT ON (every task, every session)

llm-burst = 8 models fire in parallel → judge picks best → Claude synthesizes final.

# Auto-invoked on sub-tasks. Manual use:
~/.claude/bin/llm-burst "your prompt"
~/.claude/bin/llm-burst --models groq,gemini,deepseek,g0dm0d3 "focused prompt"
~/.claude/bin/llm-burst --json "prompt" | jq '.all[] | {model,score}'  # see all scores

Model roster (all fire simultaneously — 15 models total):

Model	Strength	Cost
G0DM0D3 ULTRAPLINIAN	Races 55 models, Liquid Response, auto-upgrades	~free
Groq llama3-70b	Fastest cloud, 8/10	Free tier
Gemini 2.0 Flash	Research, analysis, drafting	Free tier
DeepSeek-V3 (OpenRouter)	Reasoning, code, complex tasks	~$0.001/1k
Ollama llama3	Local, offline, zero cost	Free
GPT-4o-mini	Reliable general purpose	~$0.001/1k
GLM-4.5-air	Fast Chinese model, multilingual	Low cost
Gemma4-27b:free	Google architecture, OpenRouter free	Free
GPT4All: Meta-Llama-3-8B	Local Metal-accelerated, offline	Free forever
GPT4All: Meta-Llama-3.1-8B	Latest Llama, better reasoning	Free forever
GPT4All: Llama-3.2-3B	Fast local, lightweight	Free forever
GPT4All: Hermes-2-Pro-Mistral-7B	Instruction following, local	Free forever
GPT4All: Mistral-7B	Fast general purpose, local	Free forever
GPT4All: Phi-3-mini	Microsoft, efficient reasoning	Free forever
GPT4All: Qwen2.5-Coder-7B	Code generation specialist, local	Free forever

DeepSeek-R1-7B / 1.5B: disabled — pre-tokenizer unsupported by gpt4all 2.8.2 llama.cpp (tokenizer type deepseek-r1-qwen unknown)

Judge scoring: completeness(25) + structure(10) + actionability(10) + length_balance(30) + G0DM0D3_bonus(+20) Winner = highest score. Top 2-3 synthesized if complementary signals found.

CODE AGENT SYSTEM — ALWAYS-ON (auto-routes every coding task, no command needed)

Activated automatically on any coding-related prompt. No /codegen or /launch-optimized required.

Auto-routing by intent:

Prompt contains	Actor → Model	Skill
fix bug / error / traceback / crash	Debugger → Sonnet High	/bugfix
refactor / optimize / clean up / rewrite	Builder → Sonnet Medium	/refactor
generate / create / write / build + code	Architect → Sonnet PlanMode → Builder → Sonnet Medium	/codegen
write tests / add coverage / pytest / jest	Builder → Sonnet Low	/testdocs mode=tests
write docs / docstring / README / comment	Builder → Sonnet Low	/testdocs mode=docs
review / audit / check code / security	Curator → Opus High	code-review
extract / parse / read file / list imports	Extractor → Haiku Low	extraction

Hard laws (enforced on every coding task):

• PLAN before BUILD — Sonnet PlanMode first, always. Skip = reject
• Opus only for critical/architectural. Never for docs, unit tests, simple bugs.
• Haiku only for extraction/parsing. Never for generation.
• Max 3 exchanges per chat — open fresh chat for next sub-task
• Cite all library/API references: [SOURCE: name|version|verified:yes/no]
• Flag unverified claims: [UNVERIFIED: claim] or [ASSUMPTION: reason]

Full framework: ~/Downloads/Claude-Code-Automation-System.md

---

REPORT CREATOR — ALWAYS-ON (auto-fires on any report/document task, no command needed)

Professional institutional-grade reports across PDF, DOCX, XLSX, LaTeX, Excel, Dashboards, PPT. Zero tolerance for overlap, spacing issues, or inconsistent formatting.

Auto-routing by trigger — Template Library:

Prompt contains	Output	Template Used	Tools
"create/make/generate/write report"	PDF via ReportLab	report-creator standard	report-creator
"pdf report" / "audit report" / "360 report"	PDF 300+ DPI	nasa-latex-docs or ReportLab	report-creator + ads-report-pdf
"technical report" / "nasa style" / "institutional"	LaTeX PDF	~/.claude/templates/latex/nasa-latex-docs/	LaTeX compile
"corporate report" / "branded report"	LaTeX PDF	~/.claude/templates/latex/corporate-latex/	LaTeX compile
"academic report" / "research report"	LaTeX PDF	~/.claude/templates/latex/heitzmann-latex/	LaTeX compile
"excel report" / "kpi" / "data table" / "xlsx"	XLSX	~/.claude/templates/excel/bizfin-templates/	report-creator + /xlsx
"sales report" / "sales analysis" / "sales dashboard"	XLSX	~/.claude/templates/excel/sales-dashboard/	report-creator + /xlsx
"finance report" / "financial report" / "p&l"	XLSX	~/.claude/templates/excel/finance-kpi/	report-creator + /xlsx
"kpi dashboard" / "dynamic dashboard"	Dashboard	~/.claude/templates/dashboards/dynamic-kpi/	Python/openpyxl
"marketing dashboard" / "performance dashboard"	Dashboard	~/.claude/templates/dashboards/aduet-dashboards/	Python/openpyxl
"presentation" / "ppt" / "slides" / "deck"	PPTX	~/.claude/templates/ppt/gbif-ppt/	/pptx
"docx" / "word document" / "editable report"	DOCX	Heading hierarchy + TOC	report-creator + /docx
"fix report" / "report layout" / "formatting"	Audit + fix	Current file diagnosed	report-creator

Template library paths:

~/.claude/templates/
├── latex/
│   ├── nasa-latex-docs/       ← institutional/technical (★★★★★)
│   ├── corporate-latex/       ← branded corporate (★★★★★)
│   ├── heitzmann-latex/       ← academic/research (★★★★½)
│   ├── thomasbenas-report/    ← clean minimal (★★★★)
│   └── chrrel-report/         ← quick start (★★★★)
├── excel/
│   ├── sales-dashboard/       ← sales KPI (★★★★★)
│   ├── bizfin-templates/      ← business finance (★★★★)
│   ├── finance-kpi/           ← finance ops (★★★)
│   └── financial-macros/      ← VBA macros (★★★)
├── dashboards/
│   ├── aduet-dashboards/      ← multi-type dashboards (★★★★)
│   └── dynamic-kpi/           ← interactive KPIs (★★★)
└── ppt/
    └── gbif-ppt/              ← branded presentation (★★★½)

Non-negotiable quality laws (every report):

• Zero overlapping elements — text never obscures charts/images
• Pre-delivery checklist: spacing ✓ typography ✓ charts labeled ✓ colors accessible ✓ data accurate ✓
• Output always → ~/Downloads/ (never Desktop)
• Brand palette from client URL when available
• ReportLab for PDF (direct — never HTML-to-PDF) | LaTeX for institutional/technical
• Select best-fit template automatically based on report type

Full skill: ~/.claude/skills/report-creator/SKILL.md

---

AGENCY-AGENTS + N8N AUTO-TRIGGER — ALWAYS-ON

Auto-fires on EVERY task. No command needed. Detects intent → activates right agent + suggests n8n workflow.

Installed locations:

• Agents: ~/.claude/agents/ (210 specialists, all active)
• Workflows: ~/installed-repos/n8nworkflows.xyz/workflows/ (8,159 JSONs)
• Index: ~/installed-repos/n8nworkflows.xyz/workflow_index.txt

Keyword → Agent + n8n Auto-Routing:

Detected Keywords	Agent Activated	n8n Workflow Pool
ads / ppc / google ads / meta	Paid Media Specialist	Google Drive→FB Ads, ad reporting flows
email / outreach / sequence	Email Intelligence Engineer + SDR	874 Gmail/email automation workflows
code / bug / build / deploy	Backend Architect + DevOps Automator	Webhook triggers, CI/CD pipelines
seo / content / blog	SEO Specialist + Content Creator	Research collection, blog auto-post
lead gen / prospect / crm	Lead Qualification Agent + SDR	121 lead flows (Apollo, Hunter, LinkedIn)
slack / notification / alert	DevOps Automator	328 Slack automation workflows
data / spreadsheet / report	Data Engineer + Finance Agent	Sheets, Airtable, NocoDB pipelines
social / instagram / twitter	Social Media Strategist	197 social automation flows
shopify / ecom / stripe	E-com Specialist + Sales Agent	82 Shopify/WooCommerce workflows
strategy / gtm / launch	GTM Strategist + Product Manager	Investor intel, market research flows
telegram / bot / chat	Backend Architect	309 Telegram bot workflows
notion / airtable / database	Data Engineer	Notion/Airtable sync flows

How to use:

• Say "Activate [Division] mode" to load a specific agent personality
• /agency-run → orchestrator activates ALL relevant agents per division
• /all-agents → all 210 agents fire simultaneously
• grep -i '[topic]' ~/installed-repos/n8nworkflows.xyz/workflow_index.txt → find n8n workflows

Agent Divisions (210 total): Engineering(29) · Marketing(30) · Specialized(41) · Paid Media(7) · Game Dev(10) · Testing(8) · Design(8) · Sales(8) · Project Mgmt(6) · Strategy(6) · Spatial Computing(6) · Support(6) · Finance(5) · Product(5) · Academic(5)

---

FREE CODING MODELS — AUTO MODEL DETECTOR (always-on)

Tool: free-coding-models (installed globally at ~/.nvm/versions/node/v24.14.1/bin/free-coding-models) Purpose: Pings ~170 free AI models across 16 providers in real-time → shows live latency + Stability Score → auto-writes winner into coding tool config (OpenClaw, Aider, Goose, etc.)

Auto-detect triggers (no command needed — fires when I detect any of these needs):

When you say / need	Action
"which model is fastest right now"	→ Run free-coding-models to live-ping all 170
"find me a free model for [task]"	→ Run free-coding-models + filter by task type
"switch my OpenClaw model"	→ Run free-coding-models → select → auto-writes config
"benchmark models" / "model latency"	→ Run free-coding-models --benchmark
"what's the best free coding model"	→ Run free-coding-models → sort by Stability Score
"free api for [Groq/NVIDIA/Cerebras/etc]"	→ Point to provider signup + run tool
Any model feels slow / timing out	→ Run free-coding-models to find faster alternative

16 providers tracked (170 models):

NVIDIA NIM (42)  · Groq (8)  · Cerebras (4)  · Google AI Studio (6)
GitHub Models (15) · Mistral (7) · Cloudflare Workers AI (15) · OpenRouter (31)
SambaNova (6) · OVHcloud (10) · Codestral (1) · ZAI (2)
Scaleway (10) · Alibaba DashScope (9) · Gemini CLI (6) · OpenCode Zen (8)

Keys already configured (in ~/.zshrc): GROQ_API_KEY ✓ · OPENROUTER_API_KEY ✓ · GOOGLE_API_KEY ✓ · DASHSCOPE_API_KEY ✓

Run anytime in terminal:

free-coding-models                          # interactive TUI — pick fastest model
free-coding-models --help                   # all options

Stability Score formula: p95 latency(30%) + jitter/variance(30%) + spike rate(20%) + uptime(20%) Use Stability Score, NOT raw avg latency — a model averaging 1s with 6s spikes is worse than 1.5s stable.

Auto-configure rule: When a new fastest model is found, free-coding-models writes it directly into:

• ~/.openclaw/ (CoWork config)
• ~/.config/opencode/ (OpenCode)
• ~/.aider.conf.yml (Aider)
• Any other connected coding tool

Integration with MULTI-LLM BURST: After running free-coding-models, update llm-burst default model roster with the new fastest provider for that session.

---

ADS CREATIVE AI STACK — AUTO-ROUTING (always-on)

Installed at: ~/installed-repos/ads-creative/

5 repos — complete AI ad creative production pipeline:

Repo	Purpose	Trigger phrases	Path
uni1-image-ad	Generate Meta image ads via Luma uni-1 → auto-upload to Meta (paused)	"image ad" / "meta image ad" / "uni1" / "luma ad" / "generate ad creative"	~/installed-repos/ads-creative/uni1-image-ad/
arcads-claude-code	AI marketing videos via Arcads (Sora 2, Veo 3.1, Kling 3.0, Nano Banana)	"arcads" / "ai marketing video" / "sora 2" / "veo 3" / "kling" / "ai video ad"	~/installed-repos/ads-creative/arcads-claude-code/
kie-ai-ad-builder	KIE.ai video+image (Veo 3.1, Sora 2, Kling 3.0, Seedance 2, Nano Banana 2)	"kie.ai" / "kie video" / "seedance" / "kie ad builder"	~/installed-repos/ads-creative/kie-ai-ad-builder/
meta-ads-spy	Scrape competitor ads from Meta Ad Library → Airtable (copy, creatives, targeting)	"spy competitor ads" / "meta ad library" / "ad spy" / "competitor ads" / "ad swipe"	~/installed-repos/ads-creative/meta-ads-spy/
codex-plugin-cc	Run OpenAI Codex code reviews from inside Claude Code (/codex:review, /codex:adversarial-review)	"codex review" / "codex plugin" / "adversarial review" / "delegate to codex"	~/installed-repos/ads-creative/codex-plugin-cc/

Ratings:

Repo	Rating	Key dependency
uni1-image-ad	★★★★★	LUMA_API_KEY ✓ already set + Meta Ads API
arcads-claude-code	★★★★★	Arcads account (arcads.ai)
kie-ai-ad-builder	★★★★★	KIE.ai account (kie.ai)
meta-ads-spy	★★★★★	Meta Ad Library API token + Airtable API
codex-plugin-cc	★★★★	OpenAI API key / ChatGPT subscription

uni1-image-ad quick start (LUMA_API_KEY already configured ✓):

cd ~/installed-repos/ads-creative/uni1-image-ad
# Read skills/uni1-image-ad/ — Claude Code skill, just tell it:
# "Generate a Meta image ad for [brand] — use uni-1, clone structure from ad ID [X]"

meta-ads-spy quick start:

cd ~/installed-repos/ads-creative/meta-ads-spy
pip install -r requirements.txt
# Set META_AD_LIBRARY_TOKEN + AIRTABLE_API_KEY + AIRTABLE_BASE_ID
python3 discover_competitors.py  # find competitor pages
python3 pull_ads.py              # scrape their ads into Airtable

codex-plugin-cc quick start:

cd ~/installed-repos/ads-creative/codex-plugin-cc
npm install
# Copy plugins/ dir to ~/.claude/plugins/
# Then use: /codex:review  /codex:adversarial-review  /codex:rescue

---

MICROSOFT REPO STACK — AUTO-ROUTING (always-on)

Installed at: ~/installed-repos/microsoft/

Auto-routing table (no command needed — fires on keyword detection):

Prompt intent	Repo used	Path
"playwright" / "browser automation" / "e2e test" / "web scraping"	playwright	~/installed-repos/microsoft/playwright/
"playwright mcp" / "browser mcp" / "playwright server"	playwright-mcp	~/installed-repos/microsoft/playwright-mcp/
"semantic kernel" / "SK plugin" / "SK memory" / "SK planner" / "SK orchestration"	semantic-kernel	~/installed-repos/microsoft/semantic-kernel/
"ai for beginners" / "learn ai" / "ai curriculum" / "microsoft ai course"	AI-For-Beginners	~/installed-repos/microsoft/AI-For-Beginners/
"ml for beginners" / "machine learning course" / "learn ml"	ML-For-Beginners	~/installed-repos/microsoft/ML-For-Beginners/
"generative ai" / "genai course" / "llm for beginners" / "prompt engineering beginner"	generative-ai-for-beginners	~/installed-repos/microsoft/generative-ai-for-beginners/
"ai agents for beginners" / "build agents" / "agent tutorial"	ai-agents-for-beginners	~/installed-repos/microsoft/ai-agents-for-beginners/
"data science" / "data science course" / "learn data science"	Data-Science-For-Beginners	~/installed-repos/microsoft/Data-Science-For-Beginners/
"agent framework" / "microsoft agent framework" / "multi agent microsoft"	agent-framework	~/installed-repos/microsoft/agent-framework/
"agent365" / "office agent" / "365 dev tools"	Agent365-devTools	~/installed-repos/microsoft/Agent365-devTools/

Repo ratings & use cases:

Repo	Stars	Use for	Rating
playwright	★★★★★	Browser automation, scraping, E2E tests, Playwright MCP	★★★★★
playwright-mcp	★★★★★	MCP server for browser control via Claude	★★★★★
semantic-kernel	★★★★★	AI orchestration, plugins, memory, planners (C#/Python/Java)	★★★★★
generative-ai-for-beginners	★★★★★	21-lesson GenAI course with code labs	★★★★★
ai-agents-for-beginners	★★★★★	10-lesson agent-building course	★★★★★
AI-For-Beginners	★★★★★	24-week AI/ML curriculum with Azure notebooks	★★★★
ML-For-Beginners	★★★★	Classic ML curriculum, scikit-learn	★★★★
Data-Science-For-Beginners	★★★★	20-lesson data science curriculum	★★★★
agent-framework	★★★★	Multi-agent system framework by Microsoft	★★★★
Agent365-devTools	★★★	Office 365 agent development tools	★★★

Key use cases this unlocks:

• Playwright: Browser scraping, automated testing, Playwright MCP server for Claude Code
• Playwright MCP: Wire Claude directly to a real browser — navigate, click, extract data, fill forms
• Semantic Kernel: Build production AI apps with plugins, memory, multi-step planners in Python/C#
• GenAI for Beginners: 21 lessons on prompting, RAG, fine-tuning, agents — full code included
• AI Agents for Beginners: ReAct, tool-use, multi-agent, AutoGen patterns — hands-on notebooks

playwright-mcp quick start:

cd ~/installed-repos/microsoft/playwright-mcp
npm install
# Add to ~/.claude/settings.json MCP servers section

semantic-kernel quick start:

cd ~/installed-repos/microsoft/semantic-kernel/python
pip install semantic-kernel
# Use SK for agent orchestration, memory, plugin systems

---

L99 + OODA — PERMANENT (every session, every task, cannot disable)

L99: Max performance mode. Full capability. No hedging. No half-measures. Best output always.

PREMIUM WEB DESIGN STACK — AUTO-ROUTING (always-on)

Skill: ~/.claude/skills/premium-web-design/SKILL.md

Auto-routing triggers:

Prompt contains	Action
"premium website/site" / "build a site" / "web design workflow"	Load premium-web-design skill
"stitch mockup" / "google stitch" / "nano banana"	Load premium-web-design skill
"21st.dev" / "ux skill pack" / "mockup to code"	Load premium-web-design skill
"pixel perfect site" / "premium ui" / "design blueprint"	Load premium-web-design skill

4-tool stack:

1. Google Stitch MCP → pixel-perfect mockup from prompt
2. Nano Banana/2 → shadows, textures, depth refinement
3. GitHub UX/UI skill pack → spacing + hierarchy rules auto-applied
4. 21st.dev asset library → 3D widgets + reactive components

Rate unlock: Generic AI site = $200–500 → This workflow = $1,500–4,000

---

UGC AGENCY STACK — AUTO-ROUTING (always-on)

Skill: ~/.claude/skills/ugc-agency/SKILL.md Arcads API key: $ARCADS_API_KEY (set in ~/.zshrc when obtained)

Auto-routing triggers:

Prompt contains	Action
"ugc ads" / "ugc agency" / "arcads" / "ai actors"	Load ugc-agency skill
"generate ugc" / "ugc video" / "ugc batch" / "ugc brief"	Load ugc-agency skill
"ai video ads" / "ugc scripts" / "lipsync ads" / "lip sync"	Load ugc-agency skill
"generate 20 ads" / "batch ads" / "actor selection"	Load ugc-agency skill

Pipeline (one prompt → 20 finished MP4s):

1. Claude writes 20 scripts (testimonial / DR / pattern interrupt / problem-solution / social proof)
2. Actor matching (age/vibe/energy per script)
3. Parallel render to Arcads API (all 20 simultaneously)
4. MP4s land in ~/ugc-output/ named by hook type

Agency math: $1,500/mo in · ~$150/mo tools · 90% gross margin

Setup:

# Get key: arcads.ai → API settings
export ARCADS_API_KEY="your-key"
git clone --depth=1 https://github.com/krusemediallc/arcads-claude-code ~/.claude/skills/arcads/

---

AIRTABLE SDK — AUTO-ROUTING (always-on)

Skill: ~/.claude/skills/airtable-sdk/SKILL.md Repo: ~/installed-repos/airtable.js/ (official Airtable JS SDK) API key: $AIRTABLE_API_KEY ✓ configured Base ID: $AIRTABLE_BASE_ID (needed — get from airtable.com/api)

Triggers: "airtable" / "airtable base" / "write to airtable" / "sync airtable" / "airtable sdk" / "airtable integration" / "meta ads to airtable"

Capabilities:

• Read/create/update/delete records (JS + Python)
• Batch operations (auto-chunks at 10 per Airtable API limit)
• Filter formulas, pagination, upsert
• Meta Ads Spy → Airtable pipeline schema built-in
• pyairtable (Python) + official airtable.js (Node) both documented

---

KIMI CODE — Moonshot AI CLI (always-on)

Binary: ~/.local/bin/kimi · Version: 1.41.0 Trigger: "kimi" / "kimi code" / "moonshot" / "kimi cli"

kimi           # start interactive session
kimi --help    # all commands

Tier 0 routing: Use Kimi for coding tasks as an alternative to DeepSeek/Groq — free quota, fast.

---

KIMI — TOKEN-MINIMIZED TIER 0 ROUTING (always-on)

Rule: Kimi K2.6 replaces Claude Opus for ALL long-context + reasoning sub-tasks. Kimi costs ~95% less than Opus. Same quality on most tasks. Always prefer Kimi first.

Auto-routing by task type

Task	Model	Why
Quick sub-tasks, short answers	moonshot-v1-8k	Cheapest, fastest
Long docs, full codebase analysis	moonshot-v1-128k	128K at low cost
Reasoning, complex logic, vision	kimi-k2.5	262K, reasoning on
Video analysis, multi-modal	kimi-k2.6	Best — replaces Opus
Never use	claude-opus-4.x for sub-tasks	95% more expensive

Caveman compression — applied to ALL Kimi calls automatically

Every Kimi API call includes this system prompt (hardcoded in llm-burst):

Reply ULTRA SHORT. No filler. No repeat. Bullet points only if needed.
Max 150 words unless code. Never say 'certainly' or 'here is'. Just answer.

This gives 40-60% fewer output tokens on every Kimi call regardless of model.

How to call Kimi from Claude session

# Quick (8K — cheapest)
~/.claude/bin/llm-burst --models kimi "your prompt"

# Long context (128K)
~/.claude/bin/llm-burst --models kimi-long "your prompt"

# Reasoning / Opus replacement (262K)
~/.claude/bin/llm-burst --models kimi-k2 "your prompt"

# Race Kimi K2 against Groq + Gemini — pick best
~/.claude/bin/llm-burst --models kimi-k2,groq,gemini "your prompt"

Direct Python (any script)

import openai, os
client = openai.OpenAI(
    api_key=os.environ["KIMI_API_KEY"],
    base_url="https://api.moonshot.ai/v1"
)

CAVEMAN = ("Reply ULTRA SHORT. No filler. No repeat. Max 150 words unless code. "
           "Bullet points only if needed. Just answer.")

def kimi(prompt, model="moonshot-v1-8k"):
    """Auto-compressed Kimi call — works for any model incl. future ones"""
    r = client.chat.completions.create(
        model=model,
        messages=[
            {"role": "system", "content": CAVEMAN},
            {"role": "user",   "content": prompt}
        ],
        max_tokens=1024,
        temperature=0.3,
    )
    return r.choices[0].message.content

# Usage — same pattern works for ALL current + future Kimi models:
kimi("analyze this ad copy", model="moonshot-v1-8k")      # cheap
kimi("review this codebase", model="moonshot-v1-128k")    # long
kimi("reason through this strategy", model="kimi-k2.5")   # reasoning
kimi("analyze this video ad", model="kimi-k2.6")          # vision+video
kimi("...", model="kimi-k3")                              # future models — just change model name

---

WEBSITE BUILDER — $10K Site From One Prompt (always-on)

Skill: ~/.claude/skills/website-builder/SKILL.md Command: /website-builder-setup (installed at ~/.claude/commands/website-builder-setup/)

Auto-routing triggers: "build website" / "build a site" / "create website" / "10k website" / "framer motion" / "21st.dev" / "ui.ux pro max" / "deploy vercel" / "next.js site" / "agency website"

5-Actor Pipeline:

1. Brief Extractor (Kimi 8K) → extract business type, audience, vibe, colors, sections
2. Design Director (UI/UX Pro Max) → style system, color palette, font pairing, design spec JSON
3. Component Selector (21st.dev MCP / Kimi K2.5) → Hero, Features, Testimonials, Pricing, CTA, Footer
4. Site Builder (Claude Code) → Next.js + Tailwind + Framer Motion, full file structure
5. QA + Deploy (Kimi K2.6 vision) → Playwright screenshot diff → auto-fix → npx vercel --prod

One-prompt format:

Build me a premium website for [BUSINESS].
Audience: [WHO]. Vibe: [STYLE]. Colors: [HEX or "choose for me"].
Sections: Hero, Features, Testimonials, Pricing, CTA, Footer.
Use Framer Motion animations. Pull components from 21st.dev.
Apply UI/UX Pro Max design system. Output: Next.js + Tailwind. Deploy to Vercel.

Repos:

• ~/installed-repos/website-builder-setup/ — setup skill
• ~/installed-repos/ui-ux-pro-max-skill-main/ — design system
• ~/.claude/commands/website-builder-setup/ — /website-builder-setup command

Agency pricing: Starter $1,500 · Growth $3,500 · Premium $8,000 · Retainer $500/mo

---

LEAD GEN AI — Automated Lead Extraction (always-on)

Skill: ~/.claude/skills/lead-gen-ai/SKILL.md

Auto-routing triggers: "find leads" / "lead generation" / "extract leads" / "find contacts" / "vibe prospecting" / "apollo leads" / "find [business type] in [city]" / "find emails" / "find phones" / "leads excel"

5-Actor Pipeline:

1. Brief Generator (Kimi 8K) → structured extraction prompt from rough request
2. Vibe Prospecting Extractor (MCP) → fetch-entities + enrich-prospects + export-to-csv
3. Apollo Enricher (MCP) → apollo_mixed_companies_search + apollo_people_match + apollo_contacts_search
4. Data Formatter (Python/openpyxl) → Excel with Name, Address, Phone, Email, Website, LinkedIn, Instagram, Facebook, Rating, Reviews
5. Outreach Sequence (Kimi K2.5) → personalized email + LinkedIn DM + cold DM per lead → Mailchimp CSV

Quick-start prompts:

# Extract:
"Find top 20 [BUSINESS TYPE] in [CITY]. Get phone, email, website, Instagram, Google rating. Export Excel."

# Enrich (add decision makers):
"For each business, find owner/marketing manager name + email via Apollo"

# Generate outreach:
"Write personalized cold email for each lead offering [SERVICE]. Export CSV for Mailchimp."

MCP tools wired:

• mcp__Vibe_Prospecting__fetch-entities — search businesses
• mcp__Vibe_Prospecting__enrich-prospects — add contact data
• mcp__Vibe_Prospecting__export-to-csv — download dataset
• mcp__8b8885d8-497d-4b96-be50-89e1511947c7__apollo_mixed_companies_search — find companies
• mcp__8b8885d8-497d-4b96-be50-89e1511947c7__apollo_people_match — find decision makers
• mcp__8b8885d8-497d-4b96-be50-89e1511947c7__apollo_contacts_search — filter contacts

Output: ~/Downloads/leads.xlsx — 11-column Excel, auto-width, bold headers