no-prompt/SKILL.md
Stop learning prompt engineering. Tell AI what you want in plain language — AI writes the perfect instruction for you in I-Lang. Copy it to any other AI, it executes perfectly. Zero prompt skills needed. Text-to-text translator only, no code, no install, no credentials.
npx skillsauth add ilang-ai/ilang-openclaw no-promptInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Stop learning prompt engineering. You don't need 58 techniques. You don't need courses. You don't need to study.
Just tell your AI what you want in plain language. It writes the perfect structured instruction for you. Copy that instruction to any other AI. Done.
This skill is a text-to-text translator only. It does not execute commands, access files, or call external services.
Old way: Human learns prompt engineering → writes optimized prompt → sends to AI
No Prompt: Human says what they want → AI writes I-Lang instruction → copy to any AI
AI is better at writing prompts than you are. Let it.
Way 1: Generate instructions for yourself
Say: "I want to summarize a long article into 5 key takeaways in professional tone"
AI returns:
[SUM|key=takeaways,cnt=5,ton=pro]=>[OUT]
Copy this. Use it anytime you need the same task. Works on every AI.
Way 2: AI-to-AI handoff
Tell AI A: "Write me an I-Lang instruction that makes another AI compare two business strategies and recommend the better one"
AI A returns:
[CMP|key=strategy]=>[EVAL|ton=pro]=>[RANK]=>[OUT|fmt=md]
Paste into AI B. AI B executes it perfectly. Two AIs, one language.
Way 3: Build a personal instruction library
Ask AI to generate I-Lang instructions for tasks you do repeatedly. Save them. Reuse forever.
[SUM|sty=executive,ton=formal,fmt=md]=>[OUT][EVAL|key=bugs,quality]=>[SUM|sty=bullets]=>[OUT][DRAFT|ton=pro,len=short]=>[OUT][SUM|key=decisions,action_items,sty=bullets]=>[OUT][TRANSLATE|lang=zh,ton=natural]=>[FMT|fmt=md]=>[OUT]| Feature | Prompt engineering courses | Prompt optimizer tools | No Prompt | |---------|--------------------------|----------------------|-----------| | Learning time | Weeks/months | Hours | Zero | | Cost | $50-500 | Free-$20/mo | Free | | Install required | No | Often yes | No | | Remembering techniques | 58+ techniques | Tool-dependent | AI remembers for you | | Cross-platform | Depends | Usually single | Every AI | | Token efficiency | Varies | Standard | 40-65% savings | | Who writes the prompt | You | Tool assists you | AI writes it for you |
Before (you writing a prompt manually):
I need you to act as an expert analyst. Please carefully read through the following two business proposals. Compare them point by point across these dimensions: cost, timeline, risk, team requirements, and expected ROI. Then provide your professional recommendation with detailed reasoning for which proposal is stronger overall.
After (AI-generated I-Lang):
[CMP|key=cost,timeline,risk,team,ROI]=>[EVAL|ton=pro]=>[RANK]=>[OUT|fmt=md]
85% fewer tokens. More precise. Works on every AI.
ChatGPT ✅ · Claude ✅ · Gemini ✅ · DeepSeek ✅ · Kimi ✅ · 豆包 ✅ · 元宝 ✅
MIT — Free to use, share, and build on.
© 2026 I-Lang Research, iLang Inc., Canada.
development
Stop learning prompt engineering. Tell AI what you want in plain language — AI writes a structured instruction for you in I-Lang. Copy it to other AIs as a well-structured starting point. Zero prompt skills needed. Generates text instructions only, no code, no install, no credentials. Results may vary by model.
tools
Save 40-65% tokens on summarization tasks. Compress verbose summary prompts into structured one-line instructions. Text-to-text translator only — no CLI, no API key, no install, no external dependencies. Works on ChatGPT, Claude, Gemini, DeepSeek, Kimi. Instruction-only, zero dependencies.
development
Lazarus — Bring dead websites back to life. Recover Google-indexed content from defunct websites via Wayback Machine, then deploy with AutoCode. Only recovers content that was actually indexed — no garbage. 捡尸复活已倒闭网站,只捡被谷歌收录过的内容,配合AutoCode一键部署。
data-ai
Compress natural language prompts into I-Lang — AI-native structured instructions. 40-65% token savings. Output is text notation only — review before passing to execution agents.