Agent Instruction Prompt Formatter
Formats fuzzy agent instructions into a structured prompt with objective, available tools, constraints, success criteria, and failure handling.
Converts a stream-of-consciousness prompt into a structured one with Task, Context, Constraints, Requirements, and Output Format sections.
Most prompts start life as a brain dump. You know what you want but write it out as one long run-on thought — a mix of goals, assumptions, constraints, and output preferences all jammed together. AI models can usually extract enough to produce something, but structured input produces much better output. This formatter takes whatever you have and reorganises it without changing what you actually asked for.
Write out what you want without filtering
Don't try to structure it. Just write out your goal, assumptions, constraints, and output preferences in whatever order they come to mind.
Paste your text into the formatter
Open in Prompt Formatter and paste your brain dump. The formatter will identify the intent and pull out the relevant sections.
Review the structured output
Check that Task, Constraints, and Requirements match what you intended. The formatter doesn't invent content — if something is missing, add it directly.
Use the clean prompt
Copy the structured result and use it as your prompt. Structured input produces more predictable output from AI models.
A missing Role, Context, or Output Format heading means your brain dump had nothing to put under it. One of the formatter's rules is to omit any section entirely when the input has no corresponding content, rather than leave an empty header. If you want that section present, add the detail to your messy text before you paste it in ChatGPT, Claude, or Gemini.
Constraints and preferences land in the Requirements section as a bullet list, while Goal stays a single sentence about what to accomplish. So 'keep it under 200 words' or 'no jargon' becomes a Requirements bullet, not part of Goal. The formatter sorts your existing words into these buckets; it won't invent a rule you didn't write down.
The formatter emits a fixed set of headings (Role, Goal, Context, Requirements, Output Format), so it won't produce custom labels like 'Legal Standard' or 'API Schema' on its own. Rename them yourself in the structured output it returns, then run that edited prompt in the assistant you choose. It reorganizes your words under those five headings and stops there.
Formats fuzzy agent instructions into a structured prompt with objective, available tools, constraints, success criteria, and failure handling.
Turns scattered technical instructions into a coding prompt with a clear task, code context, constraints, and expected output.
Formats scattered bug observations — logs, guesses, reproduction steps, expected vs actual — into a structured debugging prompt.
Convert scattered bug notes, Slack messages, or user complaints into structured engineering tasks with reproduction steps, severity, and root cause hypothesis.
A reusable AI agent task template with variables for objective, context, available tools, constraints, success criteria, failure handling, and output format.
A set of before-and-after examples showing exactly what prompt cleanup removes — and what it deliberately leaves alone.
Turn a messy, stream-of-consciousness prompt into a clean, structured one.
You cram the goal, context, constraints, format, and an example into one run-on prompt, and the AI misses half of it. Here's how to structure a prompt into sections: sort each instruction into Goal, Context, Task, Constraints, Output, and Non-goals — no rewriting, so the gaps show.