Token efficiency is one of the easiest wins in AI right now. If you are burning through tokens on Claude, Fable 5 or any coding agent, Rust Token Killer (RTK) vs Caveman is the comparison you want — two free, open-source tools that slash how many tokens you use.
I have tested both hands-on. The short version: they save tokens in two completely different places, so the real answer is not ‘either/or’. Here is how each works, what I actually saved, and which to use.
Last updated: July 2026.
Key takeaways
- RTK strips padding from shell command output — I saved ~82.9% (README claims 60–90%).
- Caveman makes the agent reply short & blunt — ~69% fewer output tokens, ~37% cheaper.
- They target different token sources, so the best move is to stack both.
What Is Rust Token Killer (RTK)?
RTK is an open-source filter that sits between your AI agent and your shell. When the agent runs a command, RTK strips out the padding and duplicate output before the agent ever reads it — so you get the same result using far fewer tokens.
In my own testing it saved 82.9% on average, and the RTK README claims 60–90%. There is barely any overhead: about a 14ms delay. It is around 6.6MB, installs in one command on Linux/macOS, knows how to shorten roughly 100 everyday commands, and it is trending hard with 68,000+ GitHub stars.
The classic example is git diff. Swap it for the RTK version and it strips the repeated headers and unchanged lines: in my test the output dropped from 373,000 characters to 29,000 — 92% less for the agent to read — while the full output is still saved to a file if you ever need it.
What Is Caveman?
Caveman attacks a different problem: the agent’s own replies. It is a free skill — really just a rules text file — that tells your agent to answer short, blunt and direct, dropping the filler like ‘Sure, I’d be happy to help!’ and the three-paragraph warm-ups.
On my five-prompt test with Fable 5 it used about 69% fewer output tokens (one answer went from 1,349 tokens to 324) and came out ~37% cheaper — while every answer still contained the correct fix. Code, commands, file paths and error messages are never touched.
It installs in one command across 30+ agents (Claude Code, Codex, Gemini, Cursor, Windsurf, Cline, Copilot and more), toggles with /caveman, and has light, full and ultra modes. It is on 85,000+ GitHub stars. Interestingly, a March 2026 paper found that forcing brief answers actually improved accuracy by up to 26 points on some benchmarks — shorter is not always worse.
Rust Token Killer vs Caveman: Head-to-Head
Here is the key insight most comparisons miss: RTK and Caveman shrink tokens in different places. RTK shrinks what your tools feed back to the agent; Caveman shrinks what the agent writes back to you.
| Rust Token Killer (RTK) | Caveman | |
|---|---|---|
| What it is | A filter between your agent & the shell | A rules/skill file for the agent |
| What it shrinks | Shell command output the agent reads | The agent’s own replies |
| Savings (my tests) | ~82.9% on command output | ~69% output tokens (~37% cost) |
| How it works | Strips padding & duplicates from commands | Tells the agent to reply short & blunt |
| Latency | ~14 ms | None — just shorter replies |
| Install | One command (Linux/macOS) | One command (30+ agents) |
| Keeps intact | Full output saved to a file if needed | Code, commands, paths, error messages |
| Best for | Command-heavy coding (git, builds) | Chatty agents & long replies |
Which Should You Use?
Because they solve different problems, this is not really a versus — it is a ‘both’.
- Use RTK if your work is command-heavy — lots of
git diff, builds, logs and test output flooding the context. - Use Caveman if your agent is chatty — long, padded replies eating your output budget.
- Use both for the biggest saving: RTK trims the tool output going in, Caveman trims the replies coming out.
I never frame it as one versus the other — I run both, since each removes a different kind of wasted token.
Better Together: The Token Minimizer Stack
RTK and Caveman are two parts of a bigger free stack I run to get far more out of a subscription like Fable 5:
- Ponytail — makes the agent think like a lazy senior developer, so it writes less code.
- RTK — shrinks what commands return.
- Headroom — compresses the whole context.
- Caveman — shortens the agent’s replies.
Stacked across every agent you use — Claude, OpenClaw, Hermes, anti-gravity — the savings compound, because you are cutting tokens on input, output and context all at once.
My Real Test Results
Every test was run twice — once normally, once through the tool — on the same machine, same command, and I measured the characters that came back (that text is exactly what the AI has to read and what you pay for).
| Tool | What I measured | Result |
|---|---|---|
| RTK | Average across all command tests | 82.9% fewer characters |
| RTK | git diff output | 373,000 → 29,000 chars (92% less) |
| Caveman | Fable 5, 5-prompt test | ~69% fewer output tokens, ~37% cheaper |
| Both | Answer correctness | Unchanged — same fixes, same results |
The headline: you are not trading quality for savings. Both kept the answers correct — they just cut the fluff.
Set the Whole Stack Up in Minutes
I test every new model and tool like this daily and build the best ones straight into my Agent OS. You can get the full system inside the AI Profit Boardroom, or start free with my AI course and community (plus 1,000+ AI agents). Prefer a steer first? Grab a free strategy session.
The full token-minimizer playbook — RTK, Ponytail, Headroom and Caveman — is set up ready to go inside my Agent OS, so you can run more on the same plan without wiring each tool up yourself. Related reading: my Tencent HY3 review.
FAQ
What is the difference between Rust Token Killer and Caveman?
RTK filters the shell command output your agent reads (input-side), while Caveman shortens the agent’s own replies (output-side). Different token sources, so they complement each other.
Which saves more tokens, RTK or Caveman?
In my tests RTK saved ~82.9% on command output and Caveman ~69% on output tokens — but they save on different things, so stacking both saves the most overall.
Can I use RTK and Caveman together?
Yes — that is the recommended setup. Add Ponytail and Headroom too for the full token-minimizer stack.
Are RTK and Caveman free?
Yes, both are free and open source. RTK installs in one command on Linux/macOS; Caveman installs across 30+ agents in one command.
Do these tools lose information or quality?
No — in my tests answers stayed correct. RTK saves the full unshortened output to a file if needed, and Caveman never touches code, commands, paths or error messages.
Do they work with Claude and Fable 5?
Yes — both work with Claude, Fable 5 and most coding agents, which is exactly where they help most when you are watching your token budget.
The Bottom Line
RTK vs Caveman is a false choice — RTK shrinks tool output, Caveman shrinks replies. Run them together (with Ponytail and Headroom) and every plan stretches much further.