11 tools
Data Format Tools for LLM Prompts
Convert payloads into the cheapest shape the model reads just as well.
The same records serialised six ways produce wildly different token counts. On flat tabular data the spread between cheapest and dearest is routinely three to one, and almost everyone sends the most expensive one because it is what their serialiser produces by default.
Every converter here shows the token change, because a format decision you cannot price is a format decision you cannot justify.
- JSON Formatter for PromptsFormat or minify a JSON payload, and see what the indentation costs.
- JSON Minifier for LLM PayloadsStrip every byte of formatting from a payload before you send it.
- JSON Validator with Token ReportCheck a payload parses, and see what it will cost before you send it.
- JSON String Escaper for PromptsEmbed a multi-line prompt inside a JSON field without breaking it.
- JSON to CSV for Cheaper PromptsConvert records to CSV and stop paying for the same keys hundreds of times.
- CSV to JSON ConverterTurn a spreadsheet export into records an API or a dataset can use.
- Agent Config JSON to YAMLConvert an agent or tool definition into readable YAML.
- Agent Config YAML to JSONTurn a YAML agent definition into the JSON an API expects.
- Markdown to Plain Text for PromptsStrip formatting the model does not need and you are paying for.
- Transcript Cleaner for LLM InputRemove timestamps, filler words and repetition before you pay for them.
- Code Comment Stripper for PromptsSend the code, not the commentary, when the commentary is not the question.
Which one you need
If something is failing to parse, start with the validator rather than the repairer. Knowing what is wrong is usually faster than automatically fixing something you have not diagnosed.
The conversion tools exist for the moment you change provider and discover that tool schemas, message shapes and result formats are all different. That conversion is where most migrations lose their time.
The minifiers matter more than they look on high-volume work. Pretty-printed JSON is roughly 2.2 characters per token against 4 for English prose, so the whitespace you cannot see is a real recurring line on the bill.
Format choice is itself a cost decision: the same data as CSV, JSON and YAML produces meaningfully different token counts, and at volume the difference is not a rounding error.
Questions
Which data format uses the fewest tokens?
For tabular data, CSV generally, because JSON repeats every key on every row. The gap widens with row count — at a thousand rows the repeated keys can be most of the payload. Measure with your own data rather than trusting the general rule.
Why does my JSON keep failing to parse?
Usually a markdown fence around it, a conversational preamble before it, or a trailing comma. Use the API’s schema enforcement rather than asking for JSON in the prompt, and keep a repair path anyway — enforcement is a strong constraint, not a guarantee.