Get to Usable AI Output Faster
This AI prompt optimizer clarifies the desired result, preserves your facts and constraints, and shows every change before you test the rewritten prompt in ChatGPT, Claude, Gemini, Cursor Agent, or any LLM.
A Cursor prompt should bound the change
Select Cursor Agent to turn a rough coding request into one reviewable repository job. The Cursor prompt optimizer keeps the requested behavior visible, carries forward known paths and constraints, and makes the completion claim easier to check. It does not inspect the repository or run the task.
Rough Cursor prompt
Add severity filtering to the activity feed.
Reviewable task prompt
What the rewrite protects
- The requested behavior stays the job.
- Unknown paths and commands remain placeholders.
- Unrelated cleanup stays outside the change boundary.
- Tests and command results support the completion claim.
- The final response gives the reviewer a short receipt.
Keep one task separate from standing rules
A Cursor Agent prompt asks for one change. Project Rules and AGENTS.md carry instructions that should survive across tasks. Mixing those jobs can turn a focused request into permanent repository policy.
The Cursor setting preserves named rules and repository evidence already present in your prompt. It will not invent a file tree, promote a temporary preference into a rule, or claim that a passing command replaces code review.
| Instruction job | Best home | What belongs there |
|---|---|---|
| One feature, fix, or refactor | Cursor Agent prompt | The outcome, relevant context, allowed scope, checks, and return receipt for this task. |
| Scoped project convention | .cursor/rules/*.mdc | Instructions selected by path, description, or an explicit rule reference. |
| Portable repository instructions | AGENTS.md | Readable instructions shared with coding agents that support the file. |
| Mandatory safety or quality gate | Tests, hooks, or CI | A deterministic check that should fail when the agent violates the requirement. |
Sources: Cursor Agent prompting and Cursor Rules. .
A rewrite you can inspect before you run it
A short prompt can hide an unsupported claim. This static example shows how the optimizer makes the instructions explicit without changing the job.
Original prompt
Write a launch email for our API tool. Make it exciting and mention it saves lots of time. Keep it short.
Revised prompt with diff
Removed · Added
Write a launch email for [target audience] about our API tool.
Make it exciting and mention it saves lots of time.
Use an energetic tone. Mention time savings only if [approved evidence] supports the claim; otherwise omit it.
Keep it short.
Keep it concise. If a firm length is required, use [confirmed word limit].
Preserved constraints
- The deliverable remains a launch email.
- The subject remains the same API tool.
- The requested energetic tone remains visible.
- Brevity is preserved without inventing a word limit.
- The time-saved claim becomes conditional on approved evidence.
What makes the next result easier to check
A useful prompt enhancer should make the assignment easier for the model to follow and the eventual output easier for you to judge. The rewrite keeps the goal, evidence, constraints, and required format visible.
- Clear outcome
- States the task, audience, and intended result without changing the underlying goal.
- Usable context
- Organizes facts, examples, and inputs so the model can separate evidence from instructions.
- Explicit constraints
- Keeps length, tone, format, variables, code fences, and other requirements visible.
- Reviewable output
- Acts as an inspectable prompt check: additions, removals, reasons, and preserved constraints stay visible. There is no unexplained quality score.
Use the prompt optimizer in three steps
- 1
Paste the working prompt
Start with the prompt you already use, including its variables, examples, and format requirements.
- 2
Choose the target
Use Any LLM for a neutral rewrite or select ChatGPT, Claude, Gemini, or Cursor Agent.
- 3
Review before copying
Check the clean result, inspect the diff, and confirm that the preserved constraints match your intent.
What stays intact
The rewrite is instructed to preserve facts, quoted text, placeholders, variable names, code, language, examples, safety boundaries, and required output formats. Missing facts should remain visible as placeholders instead of being invented.
The optimizer is a drafting aid, not a guarantee that every model will produce the same result. Test the revised prompt against the model and workflow where you plan to use it.
Prompt optimizer questions
What does an AI prompt optimizer change?
It rewrites an existing prompt to make the goal, context, constraints, and requested output easier for a model to follow. The result includes a diff and specific change notes so you can inspect the rewrite before using it.
Does the prompt optimizer run my prompt?
No. It edits the prompt but does not execute the task inside it. You receive one optimized prompt to review and copy into the model or application you choose.
Is this also a prompt enhancer or prompt improver?
Yes. Prompt enhancer and prompt improver describe the same core job here: rewrite an existing prompt without changing its assignment. The optimizer adds a visible diff, change reasons, and preserved constraints, so you can check each edit instead of accepting an unexplained rewrite.
Does BenchLM store my prompt?
No. BenchLM does not save prompt text in its database, logs, or analytics. The request is sent through OpenRouter with zero-data-retention and no-data-collection routing enabled. A salted, one-way hash of the client IP is stored temporarily to enforce anonymous usage limits.
Can I optimize prompts for ChatGPT, Claude, Gemini, and Cursor?
Yes. Choose Any LLM for a model-neutral rewrite, or select ChatGPT / OpenAI, Claude, Gemini, or Cursor Agent. The Cursor setting structures a one-off repository task around the requested behavior, relevant context, change boundary, checks, and completion receipt before you copy it into the agent.
Does Cursor mode read my repository?
No. The Cursor prompt optimizer rewrites only the text you paste. It cannot inspect your files, infer the correct paths, or run commands. Include known paths, symbols, repository rules, and verification commands when they matter; the rewrite should leave unknown details as visible placeholders.
Should a Cursor prompt go in Project Rules or AGENTS.md?
Use the rewritten prompt for one task in Cursor Agent. Put durable repository conventions in scoped .cursor/rules/*.mdc files or AGENTS.md. The optimizer can preserve references to those files, but it does not create, install, or validate persistent rules for your project.
Is the prompt optimizer free?
The tool is free to use without an account. The generator and optimizer share 10 requests every 24 hours for each IP address, with up to 5 requests every 10 minutes.
Continue with your prompt
Know when it’s worth switching models
The model to choose, the cheaper alternative, and the release we would wait on.
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