| 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.
~/.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}'
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 |
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 simultaneouslygrep -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
free-coding-models --help
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
meta-ads-spy quick start:
cd ~/installed-repos/ads-creative/meta-ads-spy
pip install -r requirements.txt
python3 discover_competitors.py
python3 pull_ads.py
codex-plugin-cc quick start:
cd ~/installed-repos/ads-creative/codex-plugin-cc
npm install
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
semantic-kernel quick start:
cd ~/installed-repos/microsoft/semantic-kernel/python
pip install semantic-kernel
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:
- Google Stitch MCP → pixel-perfect mockup from prompt
- Nano Banana/2 → shadows, textures, depth refinement
- GitHub UX/UI skill pack → spacing + hierarchy rules auto-applied
- 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):
- Claude writes 20 scripts (testimonial / DR / pattern interrupt / problem-solution / social proof)
- Actor matching (age/vibe/energy per script)
- Parallel render to Arcads API (all 20 simultaneously)
- MP4s land in
~/ugc-output/ named by hook type
Agency math: $1,500/mo in · ~$150/mo tools · 90% gross margin
Setup:
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
kimi --help
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
~/.claude/bin/llm-burst --models kimi "your prompt"
~/.claude/bin/llm-burst --models kimi-long "your prompt"
~/.claude/bin/llm-burst --models kimi-k2 "your prompt"
~/.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
kimi("analyze this ad copy", model="moonshot-v1-8k")
kimi("review this codebase", model="moonshot-v1-128k")
kimi("reason through this strategy", model="kimi-k2.5")
kimi("analyze this video ad", model="kimi-k2.6")
kimi("...", model="kimi-k3")
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:
- Brief Extractor (Kimi 8K) → extract business type, audience, vibe, colors, sections
- Design Director (UI/UX Pro Max) → style system, color palette, font pairing, design spec JSON
- Component Selector (21st.dev MCP / Kimi K2.5) → Hero, Features, Testimonials, Pricing, CTA, Footer
- Site Builder (Claude Code) → Next.js + Tailwind + Framer Motion, full file structure
- 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:
- Brief Generator (Kimi 8K) → structured extraction prompt from rough request
- Vibe Prospecting Extractor (MCP) →
fetch-entities + enrich-prospects + export-to-csv
- Apollo Enricher (MCP) →
apollo_mixed_companies_search + apollo_people_match + apollo_contacts_search
- Data Formatter (Python/openpyxl) → Excel with Name, Address, Phone, Email, Website, LinkedIn, Instagram, Facebook, Rating, Reviews
- Outreach Sequence (Kimi K2.5) → personalized email + LinkedIn DM + cold DM per lead → Mailchimp CSV
Quick-start prompts:
"Find top 20 [BUSINESS TYPE] in [CITY]. Get phone, email, website, Instagram, Google rating. Export Excel."
"For each business, find owner/marketing manager name + email via Apollo"
"Write personalized cold email for each lead offering [SERVICE]. Export CSV for Mailchimp."
MCP tools wired:
mcp__Vibe_Prospecting__fetch-entities — search businessesmcp__Vibe_Prospecting__enrich-prospects — add contact datamcp__Vibe_Prospecting__export-to-csv — download datasetmcp__8b8885d8-497d-4b96-be50-89e1511947c7__apollo_mixed_companies_search — find companiesmcp__8b8885d8-497d-4b96-be50-89e1511947c7__apollo_people_match — find decision makersmcp__8b8885d8-497d-4b96-be50-89e1511947c7__apollo_contacts_search — filter contacts
Output: ~/Downloads/leads.xlsx — 11-column Excel, auto-width, bold headers
