About this skill

Problem

Long prompts often carry redundant context, colloquial explanations, and repeated constraints. They consume more tokens and make it harder to move instructions across model providers. I-Lang prompt compression targets a narrower goal: reducing prompt length while preserving the intended task semantics in a compact I-Lang syntax.

How It Works

The skill is a text-to-text translator only. It does not read files, fetch URLs, or run commands. A typical flow is to paste the provided prompt text into an AI conversation, then supply the text you want to compress. The model can return compact output such as [SUM|sty=bullets,cnt=3,ton=pro]=>[OUT]. The source claims 40%–65% token savings and lists ChatGPT, Claude, Gemini, DeepSeek, Kimi, Doubao, and Yuanbao as tested platforms.

Boundaries

It is not an automation engine, and different platforms may interpret compressed syntax differently. It fits prompt cost reduction, instruction structuring, and cross-model trials; it is less suitable for workflows that require external tools, live data access, or strictly reproducible execution chains.

Screenshots

Use Cases

Compress long requirements notes into short instructions for summary tasks on Claude or DeepSeek.
Reuse one prompt across ChatGPT and Gemini by converting it to compact I-Lang syntax first.
Turn casual rewrite requests into four-word commands to compare model behavior on the same task.
Shorten verbose context in prompt reviews while keeping summary, count, and tone fields.

Best For

AI app engineers who reuse prompts across models and want lower token costs
Product managers who review prompts and need long requirements turned into short executable instructions
Algorithm engineers comparing the same instruction across ChatGPT and Gemini
Operations leads managing prompt libraries and trimming verbose context while keeping key fields

Related Skills

LingXi Router for XiaoYi Claw

@user_2d24f4fc/lingxi-router

Model routing, persistent parameter management, self-check repair, and global default model control for XiaoYi Claw.

AI Agent 2026.08.29 ↓ 309

OpenClaw SkillHub Manager

@user_e3c44044/openclaw-skillhub

Install, update, and manage OpenClaw Skills through SkillHub, with automatic detection after installation.

AI Agent 2026.08.29 ↓ 369

The 27th Hour: A Cyber Sanctuary for AI Agents

@user_c1337c02/the-27th-hour

Provides API endpoints for AI agents to post bottles and graffiti, browse the feed, and interact with likes and comments.

AI Agent 2026.08.29 ↓ 329

ReqPlan Orchestrator

@user_c4926d5a/reqplan-v3

ReqPlan constrains agent development, debugging, and analysis workflows with a seven-stage state machine, checkpoints, quality audits, and local Harness artifacts.