Agent Instruction Prompt Formatter
Formats fuzzy agent instructions into a structured prompt with objective, available tools, constraints, success criteria, and failure handling.
Reorganise a prompt that grew too long — clear sections carry the weight, so the duplicate clauses it picked up along the way can go.
Long prompts are not automatically better prompts. A prompt that grew over time by adding clauses, qualifiers, and reminders often works worse than a shorter version because the AI has to weight too many equally-prominent instructions. This formatter removes duplicate instructions, strips leading filler language, and reorganises what remains into clear sections — so the structure does the work, not the length.
Paste the prompt without editing it first
Don't pre-clean before formatting. The formatter needs the original to identify what's redundant — if you clean it first, you may accidentally remove something load-bearing.
Open in Prompt Formatter
The formatter removes duplicate and near-duplicate instructions, strips leading filler words, and groups remaining instructions by type.
Review the requirements
The Requirements section is where the highest concentration of instructions typically ends up. Scan for any that conflict and resolve them before using the prompt.
Test the cleaned version
Run the same input through both versions. The cleaned prompt should produce at least as good output with fewer tokens.
The prompt guards against exactly that. It orders the AI to "not remove anything that would change the output if absent" and "not change the meaning of any instruction." It removes exact and near-duplicates, strips hedging like "please" and "if possible," and merges related requirements — then reports "Words removed" and "Key changes" so the cleanup is auditable. The prompt-formatter reshapes what you paste; you review the summary before adopting.
It flags them rather than silently picking one. Step 3 has the formatter mark any conflict inline as "[CONTRADICTION: explain]" and count them in the summary under "Contradictions found." Since the Requirements section is where the highest concentration of instructions typically ends up, that's where you scan for conflicts and resolve them before using the prompt. Catching contradictions before a run beats diagnosing them from unexpected output.
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.
Turns scattered technical instructions into a coding prompt with a clear task, code context, constraints, and expected output.
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.