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software-clean-code-standard软件干净代码标准

Agent Skill

software-clean-code-standard 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

3,515

周安装

151

GitHub Stars

59

下载量

1,232
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

3

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:software-clean-code-standard(软件干净代码标准)
来源仓库:https://github.com/vasilyu1983/ai-agents-public
仓库路径:skills/software-clean-code-standard
安装命令:
npx skills add https://github.com/vasilyu1983/ai-agents-public --skill software-clean-code-standard
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/vasilyu1983/ai-agents-public --skill software-clean-code-standard

简介

software-clean-code-standard 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中快速定位候选结果。

  • 它可结合来源仓库、安装命令和原始 README 继续核验具体用法。
  • 安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。
  • 通过 npx skills add https://github.com/vasilyu1983/ai-agents-public --skill software-clean-code-standard 安装。
  • 适用于研究检索类任务,需配合宿主环境使用。

SKILL.md

Clean Code Standard — Quick Reference

This skill is the authoritative clean code standard for this repository's shared skills. It defines stable rule IDs (CC-*), how to apply them in reviews, and how to extend them safely via language overlays and explicit exceptions.

Modern Best Practices (January 2026): Prefer small, reviewable changes and durable change context. Use RFC 2119 normative language consistently. Treat security-by-design and secure defaults as baseline (OWASP Top 10, NIST SSDF). Build observable systems (OpenTelemetry). For durable links and current tool choices, consult data/sources.json.


Quick Reference

TaskTool/FrameworkCommandWhen to Use
Cite a standardCC-* rule IDN/APR review comments, design discussions, postmortems
Categorize feedbackCC-NAM, CC-ERR, CC-SEC, etc.N/AKeep feedback consistent without "style wars"
Add stack nuanceLanguage overlayN/AWhen the base rule is too generic for a language/framework
Allow an exceptionWaiver recordN/AWhen a rule must be violated with explicit risk
Reuse shared checklistsassets/checklists/N/AWhen you need product-agnostic review/release checklists
Reuse utility patternsreferences/*-utilities.mdN/AWhen extracting shared auth/logging/errors/resilience/testing utilities

When to Use This Skill

  • Defining or enforcing clean code rules across teams and languages.
  • Reviewing code: cite CC-* IDs and avoid restating standards in reviews.
  • Building automation: map linters/CI gates to CC-* IDs.
  • Resolving recurring review debates: align on rule IDs, scope, and exceptions.

When NOT to Use This Skill

Decision Tree: Base Rule vs Overlay vs Exception

Feedback needed: [What kind of guidance is this?]
    ├─ Universal, cross-language rule? → Add/modify `CC-*` in `references/clean-code-standard.md`
    │
    ├─ Language/framework-specific nuance? → Add overlay entry referencing existing `CC-*`
    │
    └─ One-off constraint or temporary tradeoff?
        ├─ Timeboxed? → Add waiver with expiry + tracking issue
        └─ Permanent? → Propose a new rule or revise scope/exception criteria

Navigation

Resources

Templates

Utility Patterns

Related Skills


Optional: AI/Automation

  • Map automation findings to CC-* IDs (linters, SAST, dependency scanning) so humans can review impact, not tooling noise.
  • Keep AI-assisted suggestions advisory; human reviewers approve/deny with rule citations (https://conventionalcomments.org/).

Trend Awareness Protocol

IMPORTANT: When users ask recommendation questions about clean code standards, linters, or code quality tools, you MUST use a web search capability (if available) to check current trends before answering. If web search is unavailable, say so and answer using data/sources.json, clearly flagging that the recommendation may be stale.

Trigger Conditions

  • "What's the best linter for [language]?"
  • "What should I use for [code quality/static analysis]?"
  • "What's the latest in clean code practices?"
  • "Current best practices for [code standards/formatting]?"
  • "Is [ESLint/Prettier/Biome] still relevant in 2026?"
  • "[Biome] vs [ESLint] vs [other]?"
  • "Best static analysis tool for [language]?"

Required Searches

  1. Search: "clean code best practices 2026"
  2. Search: "[specific linter] vs alternatives 2026"
  3. Search: "code quality tools trends 2026"
  4. Search: "[language] linter comparison 2026"

What to Report

After searching, provide:

  • Current landscape: What linters/formatters are popular NOW
  • Emerging trends: New tools, standards, or patterns gaining traction
  • Deprecated/declining: Tools/approaches losing relevance or support
  • Recommendation: Based on fresh data, not just static knowledge

Example Topics (verify with fresh search)

  • JavaScript/TypeScript linters (ESLint, Biome, oxlint)
  • Formatters (Prettier, dprint, Biome)
  • Python quality (Ruff, mypy, pylint)
  • Go linting (golangci-lint, staticcheck)
  • Rust analysis (clippy, cargo-deny)
  • Code quality metrics and reporting tools
  • AI-assisted code review tools

Fact-Checking

  • Use web search/web fetch to verify current external facts, versions, pricing, deadlines, regulations, or platform behavior before final answers.
  • Prefer primary sources; report source links and dates for volatile information.
  • If web access is unavailable, state the limitation and mark guidance as unverified.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

04

需要参考平台分布和安装热度时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Claude Code

29.87%
按下载量换算368

Cursor

20.48%
按下载量换算252

Antigravity

16.89%
按下载量换算208

OpenCode

12.33%
按下载量换算152

Gemini CLI

7.45%
按下载量换算92

Codex

3%
按下载量换算37

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。

来源信息

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