AI & LLM tools

Developer tools for building with large language models: exact token counting, context-window and API cost planning, prompt linting, JSONL dataset checks, RAG chunking, structured-output validation, function-calling and MCP tool schemas, and prompt redaction. Everything runs locally — your prompts and datasets never leave the browser.

12 tools in this category · 6 sub-categories

Datasets & JSONL

JSONL Validator

Validate JSONL and fine-tuning datasets line by line.

JSONL Formatter

Pretty-print, minify, sort and deduplicate JSON Lines files.

JSONL ↔ JSON Converter

Convert JSON Lines to a JSON array and back again.

Privacy & Safety

AI PII & Secret Redactor

Strip emails, keys, tokens and personal data before prompting an LLM.

Prompt Engineering

Prompt Linter

Audit prompts for vague wording, missing formats and leaked secrets.

RAG & Context

RAG Text Chunker

Split documents into token-sized overlapping chunks for embedding.

Schemas & Tools

LLM Structured Output Validator

Check that a model's JSON reply matches your JSON Schema.

AI Tool Schema Builder

Build function-calling schemas for OpenAI, Claude, Gemini, MCP and the AI SDK.

MCP Tool Schema Validator

Validate Model Context Protocol tool definitions before you ship them.

Tokens & Cost

AI Token Counter

Count exact LLM tokens for GPT, Claude and Gemini prompts.

LLM Context Window Calculator

See if your system, context and user messages fit the model window.

LLM API Cost Calculator

Estimate GPT, Claude and Gemini API spend per call and per month.