“maintainability”的搜索结果

按统一标准检查变量和函数命名、代码可读性、数据更新方式及错误处理，用于新项目开发、代码审查和重构，帮助团队统一便于维护的写法。

• 制定新项目的编码规范
• 审查代码可读性
• 整理重复逻辑和深层条件分支

从价值、成本和影响三个方面审查Archify的问题、拉取请求和代码，结合实现后的维护负担，依据证据判断是否应立即处理，并比较其他解决方法。

• 确定已报告问题的优先级
• 检查拉取请求的成本与影响
• 评估代码的可维护性

以只读方式分析代码的可读性、复杂度、重复与可维护性，生成包含质量评分、重点问题位置、改进建议、良好实现示例及技术债务处理工时估算的报告。

• 检查认证模块的代码质量
• 查找重复代码和过长方法
• 梳理技术债务并估算改进工时

Review system architecture and major design changes for scalability, resilience, and maintainability. Identify risks, compare design tradeoffs, and document recommendations and next steps across services, APIs, data storage, security, and deployment.

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• Reviewing microservice boundaries
• Assessing a move to event-driven architecture
• Comparing serverless and container deployment

Review code for security, performance, quality, and maintainability. Get findings organized by severity, with file locations, explanations of impact, and example fixes, plus code metrics and complexity comparisons for refactoring reviews.

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• Reviewing a pull request before merging
• Checking code for security risks
• Finding performance improvement opportunities

Improve existing code structure while preserving its behavior, using Martin Fowler's refactoring approach. Assess tests, identify structural problems, agree on a phased plan, and make small, tested changes with reversible commits and before-and-after comparisons.

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• Splitting long functions into clearer responsibilities
• Removing duplicate or unused code
• Planning gradual improvements to legacy code

Improve existing code structure while preserving its behavior. Review dependencies and tests, identify maintainability problems such as duplication or long functions, and plan small changes with testing, reversible commits, and a final comparison of results.

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• Splitting long functions into smaller, clearer functions
• Removing duplicated logic and unused code
• Planning improvements to hard-to-maintain legacy code

Refactor JavaScript using ES6+ features to make code easier to read and maintain. Covers asynchronous operations with async/await, modules, and functional patterns that transform data without changing the original values.

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• Refactoring legacy JavaScript
• Migrating callbacks to async/await
• Building data transformation pipelines

Review a Power BI data model’s tables, relationships, storage choices, performance, maintainability, and security. Use the findings to identify design issues and build a prioritized improvement plan with concrete recommendations and implementation guidance.

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• Reviewing a Power BI model before production release
• Investigating slow queries and oversized models
• Checking table relationships and storage choices

Review DAX formulas, the expressions used for calculations in Power BI, and propose clearer, more maintainable alternatives. Identify repeated calculations, costly filtering, and error-handling issues, then explain changes and recommend ways to test them.

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• Reviewing slow calculations in Power BI reports
• Making complex DAX formulas easier to read
• Improving division and blank-value handling

Review C#/.NET code for design patterns, separation of responsibilities, and common implementation issues. Receive actionable recommendations covering maintainability, testing, performance, and security without changing the code.

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• Review design patterns in C#/.NET code
• Check separation of responsibilities before refactoring
• Identify dependencies that make testing difficult

Run Gemini CLI to review code, assess technical plans, and analyze large collections of files. Choose a model and execution settings for the task, then capture findings about security, maintainability, architecture, or technical debt.

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• Reviewing security and quality across multiple files
• Checking architecture plans for missing components
• Analyzing the structure of a large codebase

Review code changes for security, performance, correctness, and maintainability. Get findings tied to files and lines, severity ratings, practical suggestions with code examples, and a recommendation to approve, request changes, or discuss further.

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• Reviewing a pull request before merging
• Checking authentication and injection risks
• Finding excessive database queries and resource leaks

Review recent code changes for duplication, maintainability, and wasted work, then apply straightforward improvements. The workflow combines three parallel reviews, prioritizes small, low-risk fixes, and checks the edited code with relevant tests or project checks.

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• Cleaning up code after implementation
• Polishing changes before opening a pull request
• Reducing duplication in recent changes

Review code changes from three critical perspectives: production failures, maintainability, and security. Get a consolidated report that ranks findings by severity and provides merge guidance, helping examine assumptions that an ordinary self-review may overlook.

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• Reviewing a pull request before merging
• Getting a second opinion on AI-written code
• Checking authentication or data access code

Review code changes and files for bugs, security risks, performance problems, design issues, and test coverage. Receive a structured report with prioritized findings, concrete improvement examples, positive feedback, and an overall review verdict.

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• Reviewing a pull request
• Auditing code quality and security
• Finding refactoring opportunities

Review code changes for security, performance, correctness, and maintainability. Get findings tied to files and lines, severity ratings, practical suggestions with code examples, and a recommendation to approve, request changes, or discuss further.

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• Reviewing a pull request before merging
• Checking authentication and injection risks
• Finding excessive database queries and resource leaks

Writes and reviews Lean 4 proofs, machine-checked arguments for mathematics or specifications. Follows Mathlib conventions to organize definitions and lemmas, fill proof gaps, refactor lengthy proofs, and establish automated checks for unproved claims and style.

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• Formalizing mathematics or specifications in Lean 4
• Filling sorry placeholders in proofs
• Splitting long proofs into reusable lemmas

Get independent code reviews of uncommitted changes, branch differences, or individual commits using Codex or Antigravity. Receive findings with severity, locations, impact, and suggested corrections, and compare where the two reviewers agree or differ.

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• Reviewing uncommitted changes for bugs
• Comparing Codex and Antigravity on the same branch diff
• Reviewing a specific commit for security issues

Improve CircleCI build and test pipelines by identifying slow or unreliable jobs, then adjusting caching, data sharing between jobs, triggers, and parallel execution. Receive incremental configuration changes with expected effects, validation criteria, and rollback guidance.

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• Reduce long CI build and test times
• Improve dependency cache reuse
• Remove duplicate jobs and unnecessary runs

Audit Claude, Codex, or Pi configuration, instruction conflicts, hooks, and MCP connections to external tools. It also checks safeguards for maintaining AI-assisted projects and returns prioritized findings with evidence and concrete corrective or diagnostic steps.

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• Investigate agent settings or instructions that seem ineffective
• Audit hooks, MCP connections, and permission boundaries
• Check verification gaps and stale project guidance

Review code for readability, security weaknesses, performance bottlenecks, test quality, and ease of maintenance. Receive findings grouped by importance, with explanations and concrete suggestions that reflect the project's context and constraints.

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• Reviewing code quality before merging changes
• Checking security and sensitive data handling
• Finding slow queries and unnecessary API calls

Guide code changes in iPolloWork by reusing existing implementations, limiting new files and dependencies, and keeping responsibilities clear. Review runtime costs, run focused checks, and audit the final changes for duplication and maintainability issues.

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• Checking for reusable code before implementing a feature
• Removing duplicate implementations during refactoring
• Reviewing the need for new files and dependencies

Review SwiftUI projects for outdated APIs, data flow, layout, accessibility, and performance issues. Get findings organized by file, with brief before-and-after code examples and a prioritized summary of the changes that matter most.

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• Reviewing an existing SwiftUI app
• Checking for deprecated APIs
• Checking accessibility and adaptive layouts