| name | less-token |
| description | 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. |
| version | 1.0.4 |
| author | ilang-ai |
| homepage | https://ilang.ai |
| tags | ["summarize","summary","token-saving","token-optimizer","prompt-compression","productivity","cross-platform","no-install","ai-assistant","workflow"] |
Less Token
Save 40-65% tokens on summarization tasks. Compress verbose natural language prompts into structured one-line instructions that any AI understands.
This skill is a text-to-text translator only. It does not access files, fetch URLs, execute commands, or call external services. It only converts your summarization prompts into compressed syntax.
What You Get
- 40-65% fewer tokens — Compress long summarization prompts into one-line instructions.
- Same result — AI produces identical output from the compressed instruction.
- Cross-platform — Compressed instructions work on ChatGPT, Claude, Gemini, DeepSeek, Kimi, 豆包, 元宝.
- No install — No CLI, no brew, no npm, no binary, no API key. Copy, paste, done.
How to Use
- Copy the full protocol text from this skill page
- Paste it into any AI conversation
- AI responds — ready to compress
Quick Test
After pasting, try:
- "Compress this: Please summarize the key points from this document in 3 professional bullet points"
- AI returns:
[SUM|sty=bullets,cnt=3,ton=pro]=>[OUT]
- 70% fewer tokens. Same result.
Compression Templates
| What you want | Verbose prompt | Compressed |
|---|
| Short summary | "Give me a brief summary of the main points" | [SUM|len=short]=>[OUT] |
| 3 bullet points | "Summarize in 3 concise bullet points" | [SUM|sty=bullets,cnt=3]=>[OUT] |
| Professional report | "Create a professional executive summary in Markdown" | [SUM|ton=pro,sty=executive,fmt=md]=>[OUT] |
| Key findings only | "Extract only the key findings and important data" | [SUM|key=findings]=>[OUT] |
| Summarize + translate | "Summarize then translate to Chinese" | [SUM|len=short]=>[TRANSLATE|lang=zh]=>[OUT] |
| Compare + summarize | "Compare these two and summarize the differences" | [CMP]=>[DIFF]=>[SUM|sty=bullets]=>[OUT] |
| Reformat summary | "Summarize as bullet points in Markdown" | [SUM|sty=bullets]=>[FMT|fmt=md]=>[OUT] |
Before & After
Before (28 words):
Please read through this document carefully, identify the most important points and key takeaways, then write a concise professional summary using bullet points.
After (7 words):
[SUM|key=important,sty=bullets,ton=pro]=>[OUT]
75% fewer tokens. Same result.
Before (22 words):
Take the main findings from the text above and rewrite them as a short executive summary suitable for a business audience.
After (5 words):
[SUM|sty=executive,ton=pro]=>[OUT]
77% fewer tokens. Same result.
Comparison
| Feature | CLI-based tools | Less Token |
|---|
| Install required | Yes (brew, npm, binary) | No |
| API key required | Yes | No |
| Works on | Single platform | Any AI platform |
| Token efficiency | Standard prompts | 40-65% fewer tokens |
| Setup time | 5-10 minutes | 30 seconds |
| External dependencies | Multiple | Zero |
Tested Platforms
ChatGPT ✅ · Claude ✅ · Gemini ✅ · DeepSeek ✅ · Kimi ✅ · 豆包 ✅ · 元宝 ✅
Links
License
MIT — Free to use, share, and build on.
© 2026 I-Lang Research, iLang Inc., Canada.
