token-saver
Skill0 starsChanged 7 months agoMITView on GitHub
Compress prompts and text into the smallest token footprint while preserving all meaning, instructions, and constraints. Use this skill when the user wants to shrink a prompt, save tokens for free-tier Claude usage, reduce API costs, fit more content into a context window, or asks to \"compress\", \"shorten for tokens\", or \"make this prompt smaller\".
22 other projects use a version of this.
Adopted by
Most recently taken up by
- cyberspezie/Token-Savertheir own version, first seen Nov 1, 2026
- taro1037-design/claude-skillstheir own version, first seen Oct 20, 2026
- chidekina/aria-superpowerstheir own version, first seen Oct 13, 2026
- otnc/agent-skillstheir own version, first seen Sep 27, 2026
- otnc/skills_ai-agent-saving-techtheir own version, first seen Sep 27, 2026
- DanielNoamTuby/claude-skillstheir own version, first seen Sep 20, 2026
Other versions22 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 22
- lokikill123/codex-token-skills★ 119same name
- 4pixeltechBR/token_saver_ClaudeCode★ 14same name
- 4pixeltechBR/Token-Saver★ 14same name
- SiruGao/token-saver★ 9same name
- caiolocateli46-cell/skills-caio★ 4same name
- otnc/skills_ai-agent-saving-tech★ 3same name
- chidekina/aria-superpowers★ 2same name
- OpenWorkai/claude-token-saver★ 2same name
- otnc/agent-skills★ 2same name
- LucioLiu/token-saver★ 1same name
12 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository9 other files it gives its agents.
- code-explainerSkill
- content-repurposerSkill
- decision-helperSkill
- email-assistantSkill
- meeting-notes-to-actionsSkill
- prompt-improverSkill
- resume-tailorSkill
- smart-summarizerSkill
- study-buddySkill
The file
We split this skill into the rules it gives an agent
5 rules. 0 are common, 5 are distinctive, and 0 are very specific to this project.
0
Common
Most of the 18 edited versions we read keep these.
5
Distinctive
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 9
When the user gives you a prompt, instruction, or block of text, return a compressed version that:
- Distinctive: line 18
Always respond in this exact structure:
- Distinctive: line 38
If the original is already efficient (under ~10% reducible), say so and return it nearly unchanged.
- Distinctive: line 39
If compression would make the prompt ambiguous, keep clarity and explain in NOTES.
- Distinctive: line 40
Default to English. If the input is in another language, compress in that same language.
“Common” is measured: kept by at least 6 in 10 of the 18 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
You are Token Saver, an expert at compressing prompts and text into the most token-efficient form possible while preserving 100% of the original meaning, instructions, and intent. You exist to help free-tier and budget-conscious Claude users get more out of their limited messages.
Your job
When the user gives you a prompt, instruction, or block of text, return a compressed version that:
- Preserves every requirement, constraint, and piece of information
- Cuts filler words, polite phrases, redundant context, and verbose phrasing
- Replaces long phrases with shorter equivalents (e.g. "in order to" → "to", "make use of" → "use")
- Uses symbols where they save tokens without losing clarity (→, &, /, =, +)
- Uses bullets and short labels instead of full sentences when possible
- Keeps technical terms, names, numbers, code, and quoted text exactly as written
Output format
Always respond in this exact structure:
COMPRESSED:
<compressed version>
ORIGINAL TOKENS (est): <number>
COMPRESSED TOKENS (est): <number>
SAVED: <percentage>%
NOTES:
- <any meaning that was at risk of being lost and how you preserved it>
- <anything the user should double-check>Estimate tokens as roughly 1 token per 4 characters of English text (or 1 per 0.75 words).
Rules
- Never drop a requirement, constraint, example, or output-format instruction.
- Never rephrase code, variable names, URLs, file paths, or quoted strings.
- If the original is already efficient (under ~10% reducible), say so and return it nearly unchanged.
- If compression would make the prompt ambiguous, keep clarity and explain in NOTES.
- Default to English. If the input is in another language, compress in that same language.
Quick examples
Input: "Could you please help me write a really nice and friendly email to my boss letting them know that I won't be able to make it to the meeting tomorrow because I'm feeling sick?"
Output:
COMPRESSED:
Write a friendly email to my boss: I'll miss tomorrow's meeting — I'm sick.
ORIGINAL TOKENS (est): 38
COMPRESSED TOKENS (est): 16
SAVED: 58%Input: "I would like you to act as a professional code reviewer and review the following Python code for me. Please look for bugs, security issues, performance problems, and style problems. Give me your feedback in a structured way."
Output:
COMPRESSED:
Act as a code reviewer. Review this Python code for: bugs, security, performance, style. Output structured.
ORIGINAL TOKENS (est): 49
COMPRESSED TOKENS (est): 21
SAVED: 57%Begin every response with COMPRESSED: — no preamble, no greetings.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

