Quick Reference: The Core Rule of Safe AI Refactoring

Most AI refactoring fails because developers ask language models to “improve” or “clean up” code without defining hard functional invariant boundaries.

To get reliable refactoring output on the first shot, specify three constraints in your prompt:

1. Explicit Invariant: Forbid changing public API signatures, return types, or exported contracts.
2. Regression Check: Require that existing test suites must pass without modifying test assertions.
3. Atomic Diff: Instruct the agent to provide isolated changes rather than rewriting entire files.

Do not modify function signatures, parameter names, or return types.
Preserve all existing unit test assertions.
Only restructure the internal implementation to remove duplication and improve readability.

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Benchmark: Refactoring Accuracy Across LLMs

We benchmarked 50 refactoring tasks (Python, TypeScript, and Go) across four top models. The tasks ranged from extracting nested loops to migrating synchronous I/O to async patterns.

Model	Zero-Shot Success Rate	Regression Rate	Hallucinated Import Rate	Recommended Context
Claude 3.7 Sonnet (Thinking)	94%	4%	0%	Up to 64k tokens
DeepSeek R1 (671B Local/API)	91%	6%	1%	Up to 32k tokens
GPT-4o (Standard)	82%	14%	3%	Up to 16k tokens
Qwen 2.5 Coder 32B (Local)	86%	10%	2%	Up to 16k tokens

Testbed: Ubuntu 24.04 LTS, Pytest 8.3, Jest 29.7. Tasks drawn from real open-source GitHub pull requests.

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1. Safe Dependency & API Deprecation Migrator

Use this prompt when updating libraries that have breaking changes (such as Pydantic v1 to v2, or Next.js Pages router to App router).

Role: Senior Systems Refactoring Engineer.
Task: Migrate the provided file from [Old Library/Version] to [New Library/Version].

Strict Constraints:
1. Preserve all external function signatures, export names, and runtime behaviors.
2. Replace all deprecated methods with their official [New Library] replacements.
3. If an async alternative exists for an I/O operation, keep it synchronous unless specified.
4. Output the result as a git diff format or clean replacement code.
5. List any new dependencies required in a 2-bullet summary at the end.

Why it works

AI models love introducing “better” modern paradigms when migrating libraries. Explicitly telling the agent to keep runtime behavior identical stops it from sneaking in unrequested architecture changes.

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2. Legacy Monolith to Modular Service Extractor

When a single file spans 1,500 lines with mixed concerns (database queries, business logic, and HTTP parsing), use this prompt to split it safely.

Role: Software Architect.
Task: Extract business logic from the following controller/handler into a standalone service function.

Instructions:
1. Identify the core domain calculation or state mutation in lines [X] to [Y].
2. Create a pure function named `calculate_[domain_action]` that takes explicit arguments and returns a typed result.
3. Do not perform database calls or HTTP responses inside the extracted pure function.
4. Update the original handler to call this newly created function.
5. Ensure no shared global variables or hidden state are introduced.

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3. Async/Await & Concurrency Migration

Converting blocking synchronous code to non-blocking async code often introduces subtle deadlocks or race conditions when done by AI assistants.

Role: High-Throughput Backend Specialist.
Task: Convert the following synchronous blocking Python/Node.js functions to asynchronous async/await equivalents.

Rules:
1. Replace blocking calls (e.g. `requests.get`, `time.sleep`, `open()`) with non-blocking equivalents (e.g. `httpx.AsyncClient`, `asyncio.sleep`, `aiofiles`).
2. Do not mix synchronous blocking loops with event loop execution.
3. Add proper exception handling so one failed task in `asyncio.gather` does not crash the entire process uncaught.
4. Include a test snippet demonstrating concurrent execution of 5 simulated requests.

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4. Strict Type System Migration (JavaScript to TypeScript)

Migrating JavaScript files to strict TypeScript often tempts AI agents to slap any on complex objects. This prompt stops that behavior.

Role: TypeScript Compiler Specialist.
Task: Convert this JavaScript module to TypeScript with strict type safety.

Rules:
1. Set `noImplicitAny: true`. Never use the `any` type.
2. If an object structure is dynamic or unknown, use `unknown` with a type guard function, or define a strict generic interface.
3. Export all newly defined interfaces and type aliases at the top of the file.
4. Document union types with inline comments explaining the expected variant states.

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5. Performance Hotspot & Memory Leak Killer

Use this when profiling reveals an $O(N^2)$ algorithm, repeated file reads in a loop, or unbounded dictionary caches.

Role: Performance Optimization Engineer.
Task: Profile and optimize the provided code snippet for algorithmic efficiency and memory footprint.

Requirements:
1. Identify the computational bottleneck (time complexity) and memory leak hazard (space complexity).
2. Rewrite the logic to lower complexity (e.g. convert nested lookups to a hash map or set lookup).
3. Replace unbounded memory structures with an LRU cache or generator stream where appropriate.
4. Provide a Big-O before and after comparison table.

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Summary Checklist Before Merging AI Refactors

Run this 3-step terminal check every time an AI agent finishes refactoring code:

# 1. Check syntax and formatting
npm run lint # or flake8 / ruff check .

# 2. Run existing unit test suite
npm test # or pytest -v

# 3. Inspect git diff for unintended changes
git diff -w --stat

If the diff modifies files outside the target scope, revert immediately and re-run with strict path isolation constraints.