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Review code for security flaws, bugs, performance problems, maintainability, and test quality. Produce structured feedback with issue locations, likely impact, suggested fixes, positive observations, and a recommendation on whether changes are ready to merge.
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Review MSBuild project files and build definitions for correctness and maintainability. Get prioritized findings with concrete recommendations, distinguishing confirmed defects from conditional risks and valid exceptions such as F# source ordering or required imports.
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Identify and report code smells indicating poor design or maintainability issues in Python code, including duplicate code, magic numbers, hardcoded values, God classes, feature envy, inappropriate intimacy, data clumps, primitive obsession, and long parameter lists. Use when conducting code quality audits, preparing for refactoring, improving codebase maintainability, or performing design reviews. Produces markdown reports with severity ratings, locations, descriptions, and specific refactoring recommendations with before/after examples. Triggers when users ask to find code smells, identify design issues, suggest refactorings, improve code quality, or detect maintainability problems.
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通过CodeScene MCP评估代码结构的可维护性，比较修改前后的评分，并在提交或创建PR前检查AI所做的改动是否降低了代码质量。
Review Verdaccio code changes for security, package manager compatibility, performance, and maintainability. Verify concerns against surrounding code and relevant tests, then report actionable issues with their location, trigger, impact, and supporting evidence.
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Review code for readability, maintainability, security, and performance. Receive an overview, issues grouped by severity, concrete improvements with code examples, and positive feedback on parts of the implementation that work well.
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Analyze .NET test suites for repeated setup, assertions, and copied test methods. Get a report with file locations, before-and-after refactoring examples, priorities, and readability trade-offs, without changing the source files.
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Run an extremely strict maintainability review for abstraction quality, giant files, and spaghetti-condition growth. Use for a thermo-nuclear code quality review, thermonuclear review, deep code quality audit, or especially harsh maintainability review.
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AI DevKit · Analyze and simplify existing implementations to reduce complexity, improve maintainability, and enhance scalability. Use when users ask to simplify code, reduce complexity, refactor for readability, clean up implementations, improve maintainability, reduce technical debt, or make code easier to understand.
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Collect and assess quality metrics for Simulink models using the metric.Engine API. Use when evaluating model design quality (maintainability, complexity, architecture) or testing completeness (unit testing, SIL, PIL, coverage, pass rates) after edits or test runs. Covers metric discovery, collection, report generation, and diagnostics. Triggers on: "collect metrics", "quality metrics", "metric.Engine", "testing metrics", "maintainability metrics", "SIL metrics", "PIL metrics", "what metrics are available", "assess quality", "coverage metrics", "generate metric report", "diagnose metric errors".
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Use free built-in .NET maintainability analyzers and code metrics configuration to find overly complex methods and coupled code. USE FOR: the team wants to find overly complex methods; cyclomatic complexity thresholds are needed in CI; maintainability metrics or coupling thresholds need to be configured. DO NOT USE FOR: formatting-only work; generic analyzer setup with no complexity policy change. INVOKES: inspect the repository context, edit targeted files, and run relevant build, test, lint, or validation commands when changes are made.
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Detects duplicate boilerplate, copy-paste tests, and structural maintainability issues across .NET test suites. Use when the user asks to reduce repetition, consolidate similar test methods, convert copy-paste tests to data-driven parameterized tests, suggest a better test structure, or identify refactoring opportunities. Identifies repeated construction, assertion patterns, copy-paste methods convertible to DataRow/Theory/TestCase, redundant setup/teardown, and shared infrastructure. Produces an analysis report with concrete before/after suggestions. Works with MSTest, xUnit, NUnit, and TUnit. DO NOT USE FOR: writing new tests (use writing-mstest-tests), reviewing test quality or anti-patterns (use test-anti-patterns), or deep mock auditing (use exp-mock-usage-analysis).
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Run an extremely strict maintainability review for abstraction quality, giant files, and spaghetti-condition growth. Use for a thermo-nuclear code quality review, thermonuclear review, deep code quality audit, or especially harsh maintainability review.
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Run an extremely strict maintainability review for abstraction quality, giant files, and spaghetti-condition growth. Use for a thermo-nuclear code quality review, thermonuclear review, deep code quality audit, or especially harsh maintainability review.
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Measures cyclomatic complexity, cognitive complexity, and function length across codebases to identify maintenance hotspots. Use when someone asks about code complexity, function length analysis, maintainability metrics, or needs to find the most complex parts of their codebase. Trigger words: complexity, cyclomatic, cognitive complexity, long functions, hotspots, maintainability index, code metrics.
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Review code architecture for maintainability, catch structural issues before they become debtUse when "Reviewing pull requests with structural changes, Planning refactoring work, Evaluating new feature architecture, Assessing technical debt, Before major releases, When code feels "hard to change", architecture, code-review, refactoring, design-patterns, technical-debt, dependencies, maintainability" mentioned.
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Review touched code for maintainability smells such as duplication, awkward indirection, suspicious clones, dead code, poor naming, and Boy Scout cleanup opportunities. Use when a broad review needs a dedicated maintainability pass or when the user asks for code-smell review specifically.
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Use free built-in .NET maintainability analyzers and code metrics configuration to find overly complex methods and coupled code. Use when a repo needs cyclomatic complexity checks, maintainability thresholds, or complexity-driven refactoring gates.
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Run an extremely strict maintainability review for abstraction quality, giant files, and spaghetti-condition growth. Use for a thermo-nuclear code quality review, thermonuclear review, deep code quality audit, or especially harsh maintainability review.
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Run an extremely strict maintainability review for abstraction quality, giant files, and spaghetti-condition growth. Use for a thermo-nuclear code quality review, thermonuclear review, deep code quality audit, or especially harsh maintainability review.
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Knowledge base from NASA-STD-8729.1A — NASA's R&M (Reliability and Maintainability) standard covering spaceflight and support systems (Revision A, 2017-06-13). Use for NASA's objectives-driven R&M framework — the R&M objectives hierarchy (one Top Objective decomposed into four sub-objectives, paired with tailorable strategies), how R&M requirements are established inside the SMA Plan required by NPR 7120.5, the SMA Technical Authority concurrence/independent-evaluation governance, milestone vs. readiness review gates, the reliability/maintainability/availability vocabulary (Ai vs. Ao, the failure causal chain, risk as a triplet), and the R&M Evidentiary Methods catalogue (FMEA/FMECA, FTA, RBDA, RCM, LORA, plus the space-environment and parts-pedigree analyses). Scoped to NASA spaceflight and support systems and to assurance planning: it is an objectives-and-strategies standard, so it deliberately does NOT prescribe step-by-step analysis procedures (those live in the referenced NASA Preferred Reliability Practices) and is thin on facility R&M, detailed math/derivations, and non-NASA or commercial life cycles.
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Checks common code quality and maintainability risks.
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Use when working with Codeclimate — code Climate quality management. Covers maintainability analysis, test coverage tracking, issue detection, GPA scoring, and repository configuration. Use when managing Code Climate projects, reviewing maintainability ratings, tracking test coverage trends, or configuring analysis engines.
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Run an extremely strict maintainability review for abstraction quality, giant files, and spaghetti-condition growth. Use for a thermo-nuclear code quality review, thermonuclear review, deep code quality audit, or especially harsh maintainability review.
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