dart-run-static-analysis 是做什么的？
执行 dart analyze 识别警告和错误，并使用 dart fix --apply 自动解决机械性 lint 问题。在开发过程中使用以确保代码质量，并在提交更改前使用。
执行 `dart analyze` 识别警告和错误，并使用 `dart fix --apply` 自动解决机械性 lint 问题。在开发过程中使用以确保代码质量，并在提交更改前使用。
该技能专门用于 Dart 项目的静态代码分析。它通过运行 `dart analyze` 命令来检测代码中的警告和错误，帮助开发者发现潜在问题。此外，`dart fix --apply` 命令能够自动应用修复，解决那些由 Dart lint 规则定义的机械性问题（如格式、命名约定等），从而提升代码质量。该技能适用于任何 Dart 项目（包括 Flutter 项目），旨在简化开发工作流程，在代码提交前自动执行检查与修复，减少手动审查和修改的负担。支持在开发过程中随时调用，以确保代码始终符合 Dart 最佳实践。
npx skills add https://github.com/dart-lang/skills/tree/main/skills/dart-run-static-analysisInstalled? Explore more 研究与数据分析 skills: affaan-m/uspto-database, affaan-m/scholar-evaluation, affaan-m/literature-review · View all 6 →
执行 dart analyze 识别警告和错误，并使用 dart fix --apply 自动解决机械性 lint 问题。在开发过程中使用以确保代码质量，并在提交更改前使用。
This repo contains 8 individual skills — each has its own dedicated page.
Write and organize unit tests for functions, methods, and classes using `package:test`. Use when creating new logic or fixing bugs to ensure code remains correct and regression-free.
Entrypoint structure, exit codes, cross-platform scripts. Use when building command line utilities, scripts, or applications.
Collect coverage using the coverage packge and create an LCOV report
Uses get_runtime_errors and lsp to fetch an active stack trace, locate the failing line, apply a fix, and verify resolution via hot_reload.
Define and generate mock objects for external dependencies using `package:mockito` and `build_runner`. Use when unit testing classes that depend on complex external services like APIs or databases.
Replace the usage of `expect` and similar functions from `package:matcher` to `package:checks` equivalents.
Workflow for fixing package version conflicts. Use this when `pub get` fails due to incompatible package versions.
Use switch expressions and pattern matching where appropriate
USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.
Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback.
Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.
The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.
Agent skill repository discovered by 10x-chat research.
Review backend code for quality, security, maintainability, and best practices based on established checklist rules. Use when the user requests a review, analysis, or improvement of backend files (e.g., `.py`) under the `api/` directory. Do NOT use for frontend files (e.g., `.tsx`, `.ts`, `.js`). Supports pending-change review, code snippets review, and file-focused review.