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claude-code-workflowClaude 代码工作流

Agent Skill

claude-code-workflow 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

212

周安装

9

GitHub Stars

7

下载量

74
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

2

许可证

unknown

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:claude-code-workflow(Claude 代码工作流)
来源仓库:https://github.com/ilude/claude-code-config
仓库路径:skills/claude-code-workflow
安装命令:
npx skills add https://github.com/ilude/claude-code-config --skill claude-code-workflow
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。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/ilude/claude-code-config --skill claude-code-workflow

简介

claude-code-workflow 定义高效 AI 辅助开发的任务价值矩阵与实践准则。

  • 区分高价值任务如脚手架生成、重构、文档更新,与低优先级如简单 bug 修复。
  • 提供结构化决策框架,帮助判断何时值得投入多轮交互与复杂工具链。
  • 建议结合具体项目阶段调整权重,避免在探索期过度追求流程规范性。
  • 适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

SKILL.md

The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT", "SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this document are to be interpreted as described in RFC 2119.

Claude Code Workflow

Guidelines for effective AI-assisted development with Claude Code.

Task Value Matrix

ValueTask TypeExample
HighBoilerplate generationCRUD endpoints, test scaffolding
HighRefactoringExtract function, rename across files
HighDocumentationDocstrings, README updates
MediumBug investigationError analysis, log interpretation
MediumCode reviewPattern suggestions, security review
LowNovel architectureRequires deep domain knowledge
LowAmbiguous requirementsNeeds human clarification

Workflow Patterns

Explore-Plan-Code-Commit (EPCC)

The RECOMMENDED workflow for most development tasks:

  1. Explore: Use Glob, Grep, Read to understand existing code

- MUST understand context before making changes - SHOULD identify related files and dependencies - MAY use subagents for parallel exploration

  1. Plan: Outline changes before implementation

- SHOULD create TodoWrite items for multi-step tasks - MUST validate plan covers edge cases

  1. Code: Implement changes incrementally

- MUST run tests after each significant change - SHOULD use Edit over Write for existing files - SHALL NOT introduce breaking changes without tests

  1. Commit: Create logical, atomic commits

- MUST follow semantic commit conventions - SHALL NOT commit secrets or credentials

Test-Driven Development with AI

1. Write failing test → 2. Implement minimum to pass → 3. Refactor → 4. Repeat
  • MUST run tests between each step
  • SHOULD use targeted test execution during development

Spike-Then-Implement

For uncertain implementations: Create throwaway spike, validate, delete, implement properly with tests.


Context Management

Efficient Prompting

MUST: Provide specific file paths, include error messages verbatim, state expected vs actual behavior

SHOULD: Reference previous context, specify output format, include constraints upfront

SHOULD NOT: Repeat information in context, include unnecessary background, ask multiple unrelated questions

Conversation Structure

[Initial Context] → [Specific Task] → [Iterative Refinement]
  • SHOULD front-load critical information
  • MUST NOT bury important constraints at end of message

Context Window Optimization

  • SHOULD use subagents for isolated subtasks
  • MUST NOT paste entire files when snippets suffice

Subagent vs Direct Tool Usage

Use Subagents (Task tool) When:

  • Parallel independent operations (multiple searches, test runs)
  • Isolated subtasks not needing main conversation context
  • Complex multi-step work (refactoring across many files)
  • Risk isolation (exploratory changes that might fail)

Use Direct Tools When:

  • Sequential dependencies (each step depends on previous)
  • Context continuity needed (building on recent conversation)
  • Simple operations (single file read/edit)
  • Immediate feedback required (interactive debugging)
ScenarioRecommendation
Search 5+ files for patternSubagent
Edit single fileDirect
Run tests + fix failuresSubagent
Explore unfamiliar codebaseSubagent
Implement planned changesDirect

Model Selection

Opus (Complex Reasoning)

SHOULD use for: Architecture decisions, complex debugging, multi-file refactoring, novel problem solving, security-sensitive code review

Sonnet (Standard Tasks)

RECOMMENDED for: Routine code changes, test writing, documentation, code review, bug fixes with clear scope

Haiku (Quick Operations)

MAY use for: Simple queries, syntax checking, format conversions, quick lookups, commit message generation

IF deep reasoning OR high-stakes: USE Opus
ELSE IF routine development: USE Sonnet
ELSE IF simple/quick: USE Haiku

Quality Assurance

Automated Validation

MUST: Test execution after changes, linting/formatting, type checking, security scanning

SHOULD: Coverage thresholds, performance benchmarks, integration tests

Human Review Checkpoints

REQUIRED: Security-sensitive changes, production deployments, architecture modifications, public API changes

RECOMMENDED: Complex business logic, performance-critical code, external integrations


Prompt Engineering for Code Tasks

Specificity Patterns

Effective: "Refactor UserService in src/services/user.py to use dependency injection for database connection"

Ineffective: "Clean up the user code"

Constraint Specification

MUST specify: Language/framework versions, performance requirements, backward compatibility, error handling

Prompt Templates

Bug Fix:

File: [path] | Error: [exact message]
Expected: [behavior] | Actual: [behavior]
Relevant code: [snippet]

Feature:

Goal: [one sentence]
Criteria: [list] | Location: [file] | Constraints: [limits]

Session Context Management

Integration with Context Files

CURRENT.md - Active task state (SHOULD update when switching tasks, MUST reflect current focus)

STATUS.md - Project progress (SHOULD update at session end, MUST include blockers/next steps)

Session Lifecycle

[Start] → [Load CURRENT.md] → [Work + TodoWrite] → [End] → [Update STATUS.md]

Context Preservation

  • MUST save context before long breaks
  • SHOULD use /snapshot for complex multi-session work
  • MAY use /pickup to resume efficiently

Skill Activation Optimization

Triggering Skills Efficiently

  • MUST use specific keywords in descriptions
  • SHOULD include file patterns for automatic activation
  • MAY use manual invocation for specialized skills

Skill Composition

Skills SHOULD be: Single-purpose, composable, self-contained

Skills MUST NOT: Conflict with others, duplicate core rules, exceed context budget

PatternTrigger
File-based*.py, Dockerfile, package.json
Directory-based.claude/, tests/, src/
Content-basedKeywords in conversation
Command-based/skill-name invocation

Anti-Patterns to Avoid

Conversation Anti-Patterns

Anti-PatternBetter Approach
Context dumpingProvide focused, relevant context
Vague requestsSpecific, measurable goals
Premature optimizationMVP first, optimize with data
Ignoring errorsAddress errors immediately

Tool Usage Anti-Patterns

Anti-PatternBetter Approach
Bash for file opsUse Read/Edit/Write tools
Write over EditPrefer Edit for existing files
Single-threaded searchParallel subagent searches
Skipping ReadAlways Read before Edit

Workflow Anti-Patterns

Anti-PatternBetter Approach
Coding without testsTDD or test-after minimum
Giant commitsAtomic, logical commits
Ignoring TodoWriteUpdate status in real-time

Prompting Anti-Patterns

Anti-PatternBetter Approach
"Make it better"Define specific improvements
Assuming knowledgeProvide relevant background
Ignoring constraintsState constraints upfront

Quick Reference

Effective Session

  1. Start with clear goal
  2. Load context (CURRENT.md)
  3. Use EPCC workflow
  4. Update TodoWrite in real-time
  5. Run tests frequently
  6. Save context before ending

Model Selection

  • Opus: Architecture, security, complex bugs
  • Sonnet: Daily development, tests, docs
  • Haiku: Quick queries, formatting

Tool Selection

  • Read: View file content
  • Edit: Modify existing files
  • Write: Create new files (rare)
  • Glob: Find files by pattern
  • Grep: Search file contents
  • Task: Parallel/isolated work
  • Bash: System operations only

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

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

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

Codex

35.67%
按下载量换算26

Claude

32.43%
按下载量换算24

Cursor

19.1%
按下载量换算14

Gemini CLI

8.95%
按下载量换算7

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

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。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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