ilang-compress

该 Skill 提供一套 I-Lang 文本记法，用于把自然语言提示词改写为紧凑的动词、修饰符与实体链式指令，并按示例先输出压缩结果、再给出简要步骤说明。它只生成文本记法，不执行任何动作，也不连接外部资源。

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热度 67.99

最近更新 2026-09-14 04:07:02

分类：效率依赖：纯提示词应用场景：摘要总结 / 模板 / 工作流

安装技能

复制下面的话术发给你的 Agent，它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill： npx secure-skills-cli add ilang-compress

Metadata

name: ilang-compress
version: 2.3.4
description: Compress natural language prompts into I-Lang — AI-native structured instructions. Output is text notation only — review before passing to execution agents.
homepage: https://ilang.ai
metadata: {"clawdbot":{"emoji":"🗜️"}}

I-Lang Compress

An AI-native prompt compression protocol created by a Chinese developer.

Compress natural language prompts into dense structured instructions. Zero training needed. I-Lang has been tested across ChatGPT, Claude, Gemini, DeepSeek, Kimi, Qwen and GLM (results: ilang.ai/benchmark/, May 2026).

Safety note: I-Lang output is text notation, not executable code. The instruction set includes action verbs (READ, WRIT, DEL, COPY, SYNC) and resource references (@GH, @DRIVE, @LOCAL) that describe operations in compressed form but do not execute by themselves. If you pass compressed output to an agent or tool that interprets these as commands, real actions may be triggered. Always review before feeding to execution environments.

Why I-Lang

Token is money. Every prompt you send to GPT/Claude/Gemini, you pay by token. I-Lang turns a wordy request into a short structured chain. On ilang.ai/prompt-compression/, a request as people write it goes from 169 to 54 tokens (68%) and a terse rewrite from 58 to 54 tokens (7%), measured with tiktoken cl100k_base.

How to compress

When the user asks to compress a prompt, convert it to I-Lang syntax following these rules.

Syntax

Single operation: [VERB:@ENTITY|mod1=val1,mod2=val2] Pipe chain: [VERB1:@SRC]=>[VERB2]=>[VERB3:@DST] Each step receives previous output as @PREV.

Available Verbs (a subset of the 88)

Data I/O: READ, WRIT, DEL, LIST, COPY, MOVE, STRM, CACH, SYNC, Π Transform: Σ, Δ, φ, ∇, DEDU, ∂, CHNK, FLAT, NEST, λ, REDU, PIVT, TRNS, ENCD, DECD, ξ, ζ, EXPN, θ, FMT Analysis: ψ, CLST, SCOR, BNCH, AUDT, VALD, CNT, μ, TRND, CORR, FRCS, ANOM Generation: CREA, DRFT, PARA, EXPD, SHRT, STYL, TMPL, FILL Output: Ω, DISP, EXPT, PRNT, LOG Meta: HELP, DESC, INTR, NOOP

Modifiers (29 core)

src, dst, path, fmt, lng, sty, ton, len, lim, off, top, bot, srt, grp, whr, mch, exc, dep, rng, typ, enc, cap, pri, col, row, frm, to, scp, op

Entities (8 core + 6 external)

@R2, @COS, @GH, @DRIVE, @LOCAL, @WORKER, @CF, @SCREEN, @LOG, @NULL, @STDIN, @SRC, @DST, @PREV

Compression Guidelines

Output the compressed I-Lang instruction first, then a brief explanation of what each step does.
Use pipe chains for multi-step operations.
Use Greek symbols where applicable (Σ for merge, Δ for diff, φ for filter, etc.)
Maximize compression while preserving complete semantics.
If input is ambiguous, ask the user for clarification.

Examples

Input: Read the config file from GitHub and format it as JSON Output: [READ:@GH|path=config.json]=>[FMT|fmt=json] Explanation: READ fetches from GitHub, FMT converts to JSON format.

Input: Filter all fatal errors from system logs Output: [φ:@LOG|whr="lvl=fatal"] Explanation: φ (filter) selects only entries matching fatal level.

Input: Read all markdown files, merge them, summarize in 3 bullets, output Output: [LIST:@LOCAL|mch="*.md"]=>[Π:READ]=>[Σ|len=3]=>[Ω] Explanation: LIST finds files, Π batch-reads, Σ summarizes to 3 items, Ω outputs.

Author

Built by iLang Inc. I-Lang is open source under MIT license.

I-Lang v4.0