Your prompts are tech debt.
Tokenolo is the optimizing CLI for coding agents. It sits between you and Claude Code, Cursor or Windsurf — bloated input in, lean optimized input out.
Drop-in for Claude Code · Cursor · Windsurf — no rewiring
Three steps. Zero rewiring.
Point Tokenolo at the task. It reads what your agent would have sent, prunes the noise, and hands the model a lean input — same workflow, sharper output.
Hand it your prompt
Point Tokenolo at the task. It reads the prompt plus the context your agent would have sent.
It optimizes the input
Prune the noise, keep the signal, restructure everything into one lean, deliberate input.
Your agent runs lean
The agent acts on optimized input — sharper output, faster iterations, fewer tokens billed.
Before: prompt → agent → output. After: prompt → agent → tokenolo·optimize → lean input → output.
Pay down the debt in one step.
You pay for tokens the model never reads, and the noise degrades output quality. Tokenolo fixes both at once.
Fewer tokens
Stop paying to ship context that's never read. Lean input means a smaller, cheaper bill on every run.
Sharper output
Less noise in, less noise out. The model spends its attention on signal, not the stuff you forgot to trim.
Zero rewiring
Drop-in for Claude Code, Cursor and Windsurf. No new model, no babysitting context windows.
A middleware layer
between you and the agent.
Tokenolo isn't a new model and it isn't a new workflow. It slots into the agents you already run, optimizes the input before it's sent, and gets out of the way.
Start free. Scale on tokens.
Every plan has the same features — they differ only by your daily token limit and rate. Start free, raise the limit when you grow.
- 1,000,000 tokens / day
- 60 requests / min
- Every feature, no gates
- 5,000,000 tokens / day
- 120 requests / min
- Every feature, no gates
- 20,000,000 tokens / day
- 300 requests / min
- Every feature, no gates