Setup loaded. Click Generate Refactor Prompt.

Coding Workflows

Refactor Prompt Builder

"Refactor this code" invites hidden behavior changes. Pick a goal, a risk level, and a code context — and get a refactoring contract: behavior preservation requirements, seven always-on safety rules, goal-specific warnings, and an assumptions discipline where uncertainty becomes a question, never a silent decision. Runs entirely in your browser.

What should change, and toward what? E.g. "Decompose the 400-line ProcessOrder method into small, named steps."

Refactoring Goal

Each goal is a different transformation philosophy with its own priorities, warnings, and validation focus.

Risk Level

Risk sizes the change set — even Aggressive keeps behavior preservation and all seven safety rules.

Code Context

Legacy assumes unseen consumers; AI-Generated hunts repetition and over-abstraction.

Language

With the Modernization goal, the language sets a concrete modernization scope — features, not vibes.

Validation Strategy

Strict demands before/after verification, behavior comparison, regression and integration checks.

Hard limits the refactor must respect — "Public API must not change", "Database schema is frozen".

Paste it and the prompt carries it verbatim in a fenced block — or leave empty for a paste-here placeholder.

Refactor Preview (live — the contract's shape, not the output)

            

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Workflow Playbooks

Playbooks that use this tool

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Coding Workflows · 5 steps

AI Code Review Workflow

A complete AI-assisted review pass — not one prompt — that ends with ranked findings, tests guarding behavior, and a refactor plan when one is warranted.

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Coding Workflows · 5 steps

AI Debugging Workflow

The order that actually finds bugs instead of guessing at them — so you end with a verified fix, not a plausible one that quietly returns next week.

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How it works

State the refactoring objective, pick the goal — Readability, Maintainability, Performance, Modernization, Simplification, or Architecture Cleanup — and set the risk level and code context. Each goal is a different transformation philosophy with its own priorities, known failure modes, and validation focus; contexts like Legacy or AI-Generated add real duties, and with the Modernization goal the language select sets a concrete modernization scope. Optionally paste the code (carried verbatim in a fenced block) and add hard constraints like "public API must not change". The live Refactor Preview shows the contract's shape before you commit. Click Generate Refactor Prompt for the full refactoring contract: behavior preservation requirements and seven safety rules that apply at every risk level, goal-specific transformation guidance, a validation strategy, and an assumptions discipline where uncertain behavior becomes a question — never a silent decision. Nothing leaves your browser.

Use cases

  • Turning "refactor this code" into a behavior-preserving contract
  • Refactoring legacy code with consumers you cannot see
  • Modernizing C#, JavaScript, or Python with a concrete feature scope
  • Cleaning up AI-generated code: repetition, over-abstraction, dead weight

Pro tips

  • State constraints explicitly — "public API must not change", "database schema is frozen". The contract preserves public contracts by default, but a named constraint beats an implied one.
  • Use Conservative for code you can't fully verify: it instructs the model to skip any transformation whose safety can't be established and list it as a suggestion instead. The skipped-list is often more valuable than the changes.
  • Aggressive sizes the change, not the safety — behavior preservation and all seven safety rules stay on. If you actually want behavior to change, that's not a refactor; say so explicitly in a separate instruction.
  • Read the ASSUMPTIONS section of the model's answer first. A refactor that depends on an UNVERIFIED assumption is a regression waiting for the input that breaks it.

FAQ

Does this tool refactor my code?

No — it builds the contract. The output is a prompt that instructs an AI how to refactor safely: what to preserve, what to watch for, how to validate, and what to do with uncertainty. The flagship is the Behavior Preservation Contract — observable behavior, business rules, outputs, side effects, and integrations all survive unless you explicitly say otherwise.

Why is "refactor this code" dangerous as a prompt?

Because the failure mode is silent. An unconstrained refactor invites hidden behavior changes, business rule regressions, removed functionality that looked redundant, and invented requirements — and the diff looks like an improvement. The contract counters each one by name: do not remove functionality, do not invent requirements, do not rewrite unrelated code, flag uncertain behavior instead of deciding it.

How is this different from the Code Review Prompt Generator?

Different verbs. Review JUDGES — it asks "what is wrong?" and produces findings. Refactor CHANGES — it asks "how should it be changed?" and produces a controlled transformation. They chain naturally: a review finding like "this method does four jobs" becomes this tool's objective. And in this category: Debugging investigates failures, Test Case validates behavior, Code Explanation teaches it — Refactor transforms it.

What does the risk level actually change?

The size of the allowed change set — never the safety rules. Conservative demands the smallest change set, prefers many independently safe steps, and skips anything unverifiable. Balanced allows moderate restructuring in reviewable groups. Aggressive allows larger restructuring — but its own rules say it plainly: aggressive applies to the size of the change, not its safety. No behavioral assumptions, no feature invention, at any level.

What does the AI-Generated Code context do?

It targets the failure modes typical of generated code: repetition (generated code duplicates logic instead of extracting it), over-abstraction (wrappers and interfaces that make no decision), and unneeded complexity (defensive checks for impossible states). It also adds a subtle rule: generated code can look right while being subtly wrong — so a discovered bug gets flagged, never silently preserved as behavior.

Can I use the Performance goal to optimize SQL queries?

No — the Performance goal is generic code performance: repeated work, allocations, algorithm choice. Its own guidance states that SQL query optimization (indexes, execution plans, query rewrites) is out of scope. That space belongs to the SQL Optimization Prompt tool, where dialect, schema, and execution-plan context get first-class treatment.

The code looks buggy — will the refactor fix the bug?

No, and that's deliberate. A refactor preserves behavior, including behavior that looks wrong — "fixing" it mid-refactor is how business rules get broken. The contract instructs the model to flag suspicious behavior as a question instead. If it really is a bug, diagnose it with the Debugging Prompt Generator first, fix it, then refactor clean code.