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aiChecker

AI Token Counter

Estimate AI tokens, words, characters, context usage, and remaining budget for GPT-style prompts.

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Run check

Checker

Inspect the input and turn gaps into fixes.

Paste the source, review the signals, and copy only the fixes you can verify after publishing or sharing.

Input

Add URL, text, logs, metadata, or policy details.

Signals

Review score, warnings, mismatches, or limits.

Fixes

Copy recommendations and verify the live result.

Token model estimate

Choose a model family/context size. Counts are estimates, not provider billing guarantees.

Token estimates, chunks, cost math, and copy-ready prompts appear here.

Privacy: This tool runs entirely in your browser. No data is sent to our servers. We don't store, share, or have access to any of the information you process here.

Input, signals, and fixes

Review summary

Turn prompt planning into a package you can copy into an AI tool, API request, or prompt library.

Budget
Token count, context use, chunk size, or cost estimate.
Prompt package
Structured instructions, constraints, examples, and output format.
Safety note
Injection risk, missing context, or model-routing checks.

Audit examples

How to verify the findings

Use this before sending a long prompt to an AI model.

Paste your prompt, choose a context window, and check whether you still have room for examples, retrieved context, tool messages, or expected output.

Common use cases

  • Check whether a prompt fits before calling an AI API.
  • Reserve context for examples, source material, and structured output.
  • Compare prompt sizes while editing a prompt library.

How to use it well

  1. Paste the prompt, document, or source text you want to estimate.
  2. Choose the model family or context window you plan to use.
  3. Review words, characters, estimated tokens, and remaining room.
  4. Continue to context planning, chunking, cost estimates, or prompt safety checks.

Practical tips

  • Leave output room instead of filling the entire context window with input.
  • Count retrieved context separately from instructions when planning RAG.
  • Verify critical production limits with the exact provider tokenizer.

Limitations to know

  • Token estimates can differ between providers and model versions.
  • The tool does not call a model or judge whether the prompt is good.

Continue with a guide

AI Prompt Planning Guide

Token budget -> context plan -> chunks -> cost -> safety check.

Open guideOpen Prompt Lab
1

Count the prompt

Check whether the prompt leaves room for examples, retrieved context, and output.

AI Token Counter
2

Plan the context window

Reserve space for instructions, user content, tool messages, and final answer.

Context Window Planner
3

Shape retrieval chunks

Split long source material into overlap-aware chunks for RAG or knowledge workflows.

RAG Chunking Tool
4

Check safety and cost

Estimate API cost and scan untrusted text for prompt-injection patterns.

Prompt Injection Scanner

FAQ

Q: Is this exact for every AI model?

A: No. It uses a GPT-style tokenizer estimate. Treat it as a planning number because tokenization and billing can vary by model provider.

Q: Does this send my prompt to an AI API?

A: No. The counting runs in your browser and does not call a model.

Useful nearby tools

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Split long text into token-estimated chunks with overlap for retrieval and AI knowledge bases.

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Estimate per-request, daily, and monthly AI API costs from token usage and custom per-million-token prices.

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Build repeatable checks for AI relay or aggregator model claims, then score pasted responses and metadata for mismatch risk.

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Privacy: This tool runs entirely in your browser. No data is sent to our servers. We don't store, share, or have access to any of the information you process here.