「code quality」の検索結果

Build or update a professional-grade design system in Figma from a codebase. Use when the user wants to create variables/tokens, build component libraries, create individual components with proper variant sets and variable bindings, set up theming (light/dark modes), document foundations, or reconcile gaps between code and Figma. Also use when the user asks to create or generate any component in Figma — even a single one — since components require proper variable foundations, variant states, and design token bindings to be production-quality. This skill teaches WHAT to build and in WHAT ORDER — it complements the `figma-use` skill which teaches HOW to call the Plugin API. Both skills should be loaded together.

日本語の概要は準備中です。原文の説明を表示しています。

This skill should be used when the user wants to "run an evaluation", "evaluate my agent", "evaluate my ADK agent", "write an eval dataset", "analyze eval failures", "compare eval results", "optimize agent", or needs guidance on the Gemini platform eval methodology and the Quality Flywheel. Covers eval metrics, dataset schema, LLM-as-judge scoring, and common failure causes. Applies to any agents-cli project, whatever framework the agent is written in. Do NOT use for agent API code patterns (ADK: use google-agents-cli-adk-code), deployment (use google-agents-cli-deploy), or project scaffolding (use google-agents-cli-scaffold).

日本語の概要は準備中です。原文の説明を表示しています。

Analyze assertion quality, depth, variety, and false confidence in existing tests. ALWAYS USE when asked about weak, shallow, trivial, always-true, self-referential, assertion-free, presence/truthiness-only, or insufficiently diverse assertions, including MSTest, Jest, pytest, and Go. DO NOT USE for direct fixes: writing-mstest-tests owns supplied MSTest assertions; code-testing owns new cases. Use test-gap-analysis when asked whether tests would catch a production change, and test-anti-patterns for general severity-ranked audits.

日本語の概要は準備中です。原文の説明を表示しています。

Perform comprehensive exploratory data analysis on scientific data files across 200+ file formats. This skill should be used when analyzing any scientific data file to understand its structure, content, quality, and characteristics. Automatically detects file type and generates detailed markdown reports with format-specific analysis, quality metrics, and downstream analysis recommendations. Covers chemistry, bioinformatics, microscopy, spectroscopy, proteomics, metabolomics, and general scientific data formats.

日本語の概要は準備中です。原文の説明を表示しています。

This skill should be used when establishing comprehensive QA testing processes for any software project. Use when creating test strategies, writing test cases following Google Testing Standards, executing test plans, tracking bugs with P0-P4 classification, calculating quality metrics, or generating progress reports. Includes autonomous execution capability via master prompts and complete documentation templates for third-party QA team handoffs. Implements OWASP security testing and achieves 90% coverage targets.

日本語の概要は準備中です。原文の説明を表示しています。

Systematic audit and review by Referee 2. Two modes — "deck" reviews slide presentations for rhetoric, visual quality, and compile cleanliness; "code" performs cross-language replication and econometric audit of empirical pipelines. Use when reviewing slides, auditing code, or verifying replication.

日本語の概要は準備中です。原文の説明を表示しています。

Expert multi-AI code review with inline PR comments — use for thorough quality and security analysis

日本語の概要は準備中です。原文の説明を表示しています。

Review of a PR, branch, or your own uncommitted work across eight dimensions — security, correctness, test coverage, API/compatibility, usability, documentation, code quality, performance. Sizes the diff, reviews inline or fans out reviewers off a shared brief, verifies findings against code, reports a grouped list with a shape verdict, fixes on approval. Use for "review this PR", "/pr-review 3011", or a pre-flight self-review before submitting; add "thorough" for adversarial verification.

日本語の概要は準備中です。原文の説明を表示しています。

Perform comprehensive exploratory data analysis on scientific data files across 200+ file formats. This skill should be used when analyzing any scientific data file to understand its structure, content, quality, and characteristics. Automatically detects file type and generates detailed markdown reports with format-specific analysis, quality metrics, and downstream analysis recommendations. Covers chemistry, bioinformatics, microscopy, spectroscopy, proteomics, metabolomics, and general scientific data formats.

日本語の概要は準備中です。原文の説明を表示しています。

Evaluate scientific claims and evidence quality. Use for assessing experimental design validity, identifying biases and confounders, applying evidence grading frameworks (GRADE, Cochrane Risk of Bias), or teaching critical analysis. Best for understanding evidence quality, identifying flaws. For formal peer review writing use peer-review.

日本語の概要は準備中です。原文の説明を表示しています。

Builds, styles, and polishes web UI and UX. Use for any frontend, page, component, styling, layout, animation, or visual-quality task, or when asked to make an interface look or feel a certain way.

日本語の概要は準備中です。原文の説明を表示しています。

Review source files changed during a phase for bugs, security issues, and code quality problems

日本語の概要は準備中です。原文の説明を表示しています。

Evaluate Expo skills in this repo end-to-end - trigger accuracy, generated code quality, and runtime screenshots on iOS simulator and Android emulator via Expo Go (web optional). Use when the user wants to eval an Expo skill, test that a skill produces working code, benchmark a skill with device screenshots, or verify a skill's output renders correctly.

日本語の概要は準備中です。原文の説明を表示しています。

Optimize Anima code generation performance with caching, parallelism, and output tuning. Use when reducing generation latency, optimizing batch component generation, or improving generated code quality for production use. Trigger with: "anima performance", "anima slow", "anima optimization", "anima caching".

日本語の概要は準備中です。原文の説明を表示しています。

Guided journey from a shipped app that works but feels rough to a product that fits the job, flows without friction, reads clearly, and persuades honestly. Orchestrates nine skills phase by phase - jobs-to-be-done, ux-heuristics, design-everyday-things, refactoring-ui, microinteractions, made-to-stick, influence-psychology, high-perf-browser, steve-jobs-design-review - asking the user questions at every decision point and recording results in the project docs/ folder (CUSTOMER.md, DESIGN.md, POSITIONING.md, IMPROVE-APP-PLAN.md) so the journey resumes across sessions. Use when the user wants to fix a clunky product, cut UX friction, sharpen in-app copy, or says 'the app works but feels rough'. Not for code, tests, or hardening - use improve-code-quality (fresh prototype) or remove-technical-debt (aged); no app yet, create-app; needs growth loops, grow-app; marketing-site friction, improve-website; one leaking flow, conversion-optimization. For one framework in isolation, invoke that skill directly.

日本語の概要は準備中です。原文の説明を表示しています。

Code review behavioral standards. Reference during code review to ensure consistent quality checks from a QA perspective.

日本語の概要は準備中です。原文の説明を表示しています。

使用 Plankton 实现编写时代码质量强制执行 —— 通过钩子在每次文件编辑时进行自动格式化、代码检查，并由 Claude 驱动自动修复。

日本語の概要は準備中です。原文の説明を表示しています。

Find bugs, security vulnerabilities, and code quality issues in local branch changes. Use when asked to review changes, find bugs, security review, or audit code on the current branch.

日本語の概要は準備中です。原文の説明を表示しています。

Structured code quality assessment with Conventional Comments format, scaled review depth, and soft-gating verdicts preserving user autonomy.

日本語の概要は準備中です。原文の説明を表示しています。

6-agent parallel code review orchestration covering architecture, security, performance, testing, quality, and documentation dimensions with weighted scoring.

日本語の概要は準備中です。原文の説明を表示しています。

Multi-dimensional code assessment across security, quality, performance, and maintainability with confidence-gated reporting (>=80%) and Router Contract generation.

日本語の概要は準備中です。原文の説明を表示しています。

Guides the red-green-refactor TDD workflow: write a failing test first, implement the minimum code to make it pass, then refactor while keeping tests green. Use when a user asks to practice TDD, write tests first, follow red-green-refactor, do test-driven development, write failing tests before code, or phrases like 'make the test pass', 'test coverage', or 'unit tests before implementation'.

日本語の概要は準備中です。原文の説明を表示しています。

Build and ship Unity 6.3 LTS players: build settings and scenes, player/quality settings, the IL2CPP vs Mono scripting backend, managed code stripping, scripted BuildPipeline.BuildPlayer, and CI/headless builds. Use when configuring or automating a build, choosing a scripting backend, shrinking build size, or when the user mentions Unity build, player settings, IL2CPP, code stripping, or Addressables.

日本語の概要は準備中です。原文の説明を表示しています。

Reviews skill quality with evidence-based design rubrics and read-only batch inventories. Use for self-review, external skill or repository audits, and authorized auto-PR improvements. Separates design quality from measured task benefit and host compatibility.

日本語の概要は準備中です。原文の説明を表示しています。