技能详情（站内镜像，无评论）
作者：静水流深 @adsorgcn
许可证：MIT-0
MIT-0 ·免费使用、修改和重新分发。无需归因。
版本：v2.3.1
统计：⭐ 2 · 279 · 0 current installs · 0 all-time installs
⭐ 2
安装量（当前） 0
🛡 VirusTotal ：良性 · OpenClaw ：良性
Package：adsorgcn/ilang-compress
安全扫描（ClawHub）
- VirusTotal ：良性
- OpenClaw ：良性
OpenClaw 评估
The skill is an instruction-only prompt-compression translator (I-Lang) and its declared requirements and instructions are consistent with that purpose.
目的
The name/description (compress natural-language prompts into I-Lang) matches the provided SKILL.md, examples, and manifest. There are no unexpected required binaries, env vars, or config paths. The presence of entities like @GH, @R2, @COS, @LOCAL is reasonable for a compression format that can reference common storage targets — the skill does not itself request access to those services.
说明范围
SKILL.md only instructs the agent how to translate user text into the I-Lang syntax and return a brief explanation. It does not instruct the agent to read local files, access environment variables, contact external endpoints, or execute I-Lang commands. The rule to ask for clarification on ambiguity is appropriately scoped.
安装机制
This is an instruction-only skill with no install spec and no code files to run — lowest-risk install profile. Nothing is downloaded or written to disk by an installer.
证书
The skill declares no required environment variables, credentials, or config paths. Although the I-Lang vocabulary includes entities that reference cloud storage and services, the skill itself does not request or require credentials to produce compressed prompts.
持久
always is false and model invocation is allowed (the platform default). The skill does not request elevated persistence or modification of agent/system configuration.
综合结论
This skill is an instruction-only translator that converts your natural-language prompts into a compact I-Lang representation. It does not itself access your files or cloud accounts and asks no credentials, so installing it is coherent with its stated purpose. Be aware: the compressed outputs can reference external targets (GitHub, cloud storage, local files). If you later pair this skill with another skill or tool that executes I-Lang instruc…
安装（复制给龙虾 AI）
将下方整段复制到龙虾中文库对话中，由龙虾按 SKILL.md 完成安装。
请把本段交给龙虾中文库（龙虾 AI）执行：为本机安装 OpenClaw 技能「I-Lang Compress」。简介：Compress natural language prompts into I-Lang — AI-native structured instructio…。
请 fetch 以下地址读取 SKILL.md 并按文档完成安装：https://raw.githubusercontent.com/openclaw/skills/refs/heads/main/skills/adsorgcn/ilang-compress/SKILL.md
（来源：yingzhi8.cn 技能库）SKILL.md
---
name: ilang-compress
description: Compress natural language prompts into I-Lang — AI-native structured instructions. 40-65% token savings.
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 that any AI understands natively. 40-65% token savings, zero training needed.
## Why I-Lang
Token is money. Every prompt you send to GPT/Claude/Gemini, you pay by token. I-Lang compresses your instructions into a fraction of the original size — AI reads it just as well, you pay less.
## 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 (62)
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, EXTD, SHRT, STYL, TMPL, FILL
Output: Ω, DISP, EXPT, PRNT, LOG
Meta: VERS, HELP, DESC, INTR, SELF, ECHO, NOOP
### Modifiers (28)
tgt, src, dst, frm, to, scp, dep, rng, whr, mch, exc, lim, off, top, bot, fmt, lng, sty, ton, len, col, row, srt, grp, typ, enc, chr, cap
### Entities (14)
@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.
**Saved:** 55%
**Input:** Filter all fatal errors from system logs
**Output:** `[φ:@LOG|whr="lvl=fatal"]`
**Explanation:** φ (filter) selects only entries matching fatal level.
**Saved:** 55%
**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.
**Saved:** 65%
## Links
- Homepage: https://ilang.ai
- Dictionary: https://github.com/ilang-ai/ilang-dict
## Author
Built by ilang-ai from China. I-Lang is open source under MIT license.
I-Lang v2.0