Count tokens for GPT-4, Claude, Gemini and more. Paste any text or entire documents to see exact token usage before sending to an AI model.
Build structured, high-quality prompts for ChatGPT, Claude, and Gemini. Define role, context, task, format, and constraints in a guided form.
Convert large JSON datasets into clean, token-efficient AI prompts. Perfect for feeding structured data to ChatGPT, Claude, or Gemini without wasting context.
Transform CSV files and large tabular datasets into AI-ready prompts. Control which columns to include, row limits, and output format to stay within token budgets.
Generate professional system prompts for AI assistants, chatbots, and agents. Choose persona, tone, domain, and constraints to produce a production-ready system prompt instantly.
Calculate whether your text fits within any AI model's context window. Compare token usage across GPT-4o, Claude 3.5, Gemini 1.5 Pro, Llama 3, and more.
A strong password is your first line of defense. Use a Password Generator to create long, random passwords with a mix of characters.
AI models sometimes return messy output — malformed JSON, inconsistent markdown, extra explanation text wrapped around a code block, or strange artifacts from hallucination. The AI Output Formatter cleans and structures raw AI responses so they're actually usable. Paste ChatGPT, Claude, or Gemini output and choose a cleanup mode: fix broken JSON, render markdown as HTML, strip unwanted commentary from code outputs, or reformat lists and tables into clean structures. Saves the copy-paste-fix cycle that slows down AI-assisted workflows.
Each formatting mode applies targeted transformations to common AI output patterns. JSON fixer repairs trailing commas, missing quotes, and extra text surrounding JSON blocks. Markdown renderer converts the output to HTML. Artifact stripper removes common hallucination patterns (unfinished tags, repeated phrases, meta-commentary like "Here is the requested output:"). Table formatter normalizes inconsistent spacing in markdown tables.
LLMs generate text probabilistically and are not guaranteed to produce syntactically valid structured output (JSON, XML, CSV) even when instructed to. Common failure modes include trailing commas in JSON, inconsistent quote types, explanatory text before/after code blocks, and incomplete generation. Post-processing formatters fill this reliability gap when strict output validation is needed.
The JSON fixer handles the most common issues: trailing commas, single quotes instead of double quotes, and extra text wrapping a JSON block. Severely malformed JSON (missing braces, deep structural issues) may require manual correction.
Yes — the renderer supports GFM including tables, task lists, strikethrough, and fenced code blocks with syntax highlighting.
All calculations and data processing for this tool are performed locally in your browser. UtilToolkits does not send any of your data to an external server, ensuring your information remains private and secure.
Clean, format, and structure raw AI responses. Strip filler phrases, fix JSON, extract code blocks, and convert to plain text or polished Markdown.