- 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