Spend fewer tokens on every prompt

Strip the bloat
from your LLM prompts

Drop redundancy, hedging, and contradictions — keep only the essential intent. Fewer tokens in, the same result out, across every major model.

PlainCleanStructuredCleanCaveMan

Works with

OpenAIGeminiAnthropicMistralSarvamGroq

Same intent. Fraction of the tokens.

Real examples cleaned with PlainClean — meaning untouched, filler gone.

Before233 tokens

A placement command center for final-year students that combines application tracking, interview preparation, and daily execution into one continuous workflow. Students paste a job link, and the system automatically extracts the company, role, requirements, and deadlines, then builds a live application pipeline from *applied* to *offer/reject*. Instead of static trackers, it continuously tells students what deserves attention today — upcoming deadlines, stalled applications, weak interview areas, missing resume keywords, or companies likely to respond soon. On the preparation side, students practice through realistic voice-based mock interviews tailored to specific companies and roles. The interviewer interrupts, changes direction, asks follow-ups, pressures unclear answers, and scores performance across communication, confidence, technical depth, and structure. Every session feeds into a long-term improvement profile so preparation becomes adaptive instead of repetitive. The key insight is that placements are not a set of disconnected tools — they're a single stressful, high-frequency journey lasting several months. Students repeatedly switch between applying, tracking, preparing, revising resumes, and managing anxiety. Bringing all of those loops into one product creates daily engagement and stronger retention than standalone resume builders, trackers, or mock interview apps.

After97 tokens

A placement command center for final-year students combines application tracking, interview prep, and daily execution. Students paste a job link, and the system extracts company, role, requirements, and deadlines, building a live pipeline. It highlights what needs attention: deadlines, stalled apps, weak interview areas, or missing keywords. Students practice with voice-based mock interviews tailored to companies and roles, with adaptive preparation and scoring. This creates daily engagement and stronger retention by bringing all placement loops into one product.

58%fewer tokens

How it works

Three steps, a few seconds.

01

Paste your prompt

Drop in any bloated prompt — system instructions, agent steps, or a one-off question.

02

Pick a mode + model

Choose PlainClean, StructuredClean, or CaveMan, and the target model you're optimizing for.

03

Get the lean version

See the cleaned prompt with a live token count and exactly how much you saved.

Three ways to clean

Pick the level of compression that fits where the prompt is going.

PlainClean

Natural language, minus the fat

Removes redundancy, hedging, and contradictions while keeping the prompt readable and natural.

“Could you please maybe help me write…” → “Write…”

StructuredClean

Strip, then convert to JSON / XML

Best for developers passing prompts through pipelines, agents, or APIs. Outputs clean structured data.

Free text → { "task": "…", "constraints": […] }

CaveMan

Raw intent, action-first

Drops articles, filler, and pleasantries. Short broken sentences on one line — models still understand it perfectly.

“Write Python function. Return average. Input list.”

Built for real prompting

Everything you need to ship leaner prompts, nothing you don't.

Every major provider

Anthropic, OpenAI, Gemini, Mistral, Groq, and Sarvam — switch models without changing your workflow.

Live token counting

See exact token counts as you go, weighted to the target model you're optimizing for.

Structured output

Convert prose prompts into clean JSON or XML, ready to drop straight into pipelines and agents.

Prompt history

Signed-in users get their cleans saved, searchable, and one click away from reuse.

Simple pricing

Start free. Upgrade only when you need the heavy models and bigger prompts.

Guest

$0no account
  • 4 cleans per day
  • Standard models
  • All three modes
  • Live token counting
Try it now

Free

$0with an account
  • 4 cleans per day
  • 2,000 character prompts
  • Saved prompt history
  • Standard models
Create account
Most popular

Pro

$7.99250 credits
  • 250 cleans per top-up
  • 10,000 character prompts
  • Premium models (GPT-5.5, Claude, Sarvam 105B)
  • Priority processing
Go Pro

No prompts sold. No hidden fees. Cancel anytime.

Questions, answered

Redundant phrasing, hedging, pleasantries, and contradictions — the words that cost tokens without changing what the model does. The core intent and any real constraints stay intact.

Start cutting tokens today

No sign-up needed to try it. Four free cleans a day, every day.

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