Dev Prompt Optimizer
A simpler interface for turning vague coding requests into useful prompts. Pick the language, fill only the fields that matter for that stack, and generate a prompt that is more accurate and easier to use.
Simple Prompt Builder
Best for errors, broken behavior, failing builds, or incorrect output.
Best for typed frontend and backend work where correctness and reusable types matter.
Keep this short. Just enough stack detail to avoid the AI guessing wrong.
Keep the prompt compact but complete. Remove filler and repetition.
Prompt efficiency snapshot
Higher means the prompt is clearer, more targeted, and more likely to produce a useful answer.
Estimated compression against all source context you entered, not just the first field.
Detected stack context
Token Saving Details
Estimated input tokens
Estimated output tokens
0% fewer tokens
Optimized prompt result
Why this is easier
The form now asks only for the details that matter for the selected language and stack.
Users can focus on the request, current behavior, expected behavior, and relevant code instead of filling generic fields.
Why the prompt is better
The generated prompt now preserves stack choices and adds language-specific rules automatically.
It also removes filler, avoids repeated context, and keeps only the details that improve answer quality.
Good input examples
React: component state bug + expected UI behavior + relevant component snippet.
Python: traceback + current output + expected output + function snippet.
SQL: current query + wrong result or slow timing + desired result.
How to Use
- 1Choose the task type and language. Pick `Write new code`, `Fix bug`, `Refactor`, or another task first, then select the programming language so the form adapts to that stack.
- 2Fill the language-specific fields. Add the framework, runtime, database, styling, tests, or deployment details that matter for that language. The page hides irrelevant fields automatically.
- 3Describe the issue or request clearly. Add the main request, current behavior, expected behavior, and the relevant code snippet so the tool can compress the prompt without losing important meaning.
- 4Generate, review, and copy. Click `Generate compressed prompt`, review the token saving and optimization tips, then copy the final prompt into ChatGPT, Claude, Gemini, Cursor, or another coding AI tool.
Frequently Asked Questions
Practical Guide
How to use Dev Prompt Optimizer well
Dev Prompt Optimizer is designed for developers who want compact, stack-aware prompts for coding assistants and open-weight models. The tool is most useful when you treat the generated result as a structured draft: clear enough to save time, but still something you review, adapt, and ground in your own situation before using publicly.
A strong AI-assisted workflow starts with context. Instead of entering a one-line request, describe the audience, goal, constraints, format, and any examples the model should respect. That gives the generator enough signal to produce something specific rather than a polished but generic answer.
Best use cases
- Writing prompts for bug fixes, feature implementation, refactors, tests, security review, or migration work.
- Compressing messy technical context into a focused request with language, framework, runtime, and verification steps.
- Creating coding prompts that reduce hallucinated APIs and encourage smaller, safer implementation changes.
Inputs to prepare
- The task type, programming language, framework, runtime, package manager, and test framework if relevant.
- Current behavior, expected behavior, exact error messages, and the smallest useful code snippet.
- Constraints around accessibility, responsiveness, security, performance, testing, or deployment.
Review before using
- Run the generated code or suggested patch locally before trusting it.
- Check file paths, dependency names, API signatures, and edge cases against your actual project.
- Keep secrets, private source code, customer data, and proprietary logs out of prompts unless your workflow permits it.
Limitations and responsible use
Generated output can miss context, misread intent, or sound more certain than the facts allow.
High-stakes legal, medical, financial, safety, or compliance work should be reviewed by a qualified person.
The best results come from adding real context, not from generating the same generic prompt repeatedly.