cleanup-cache
Clean system caches (npm, Homebrew, Yarn, browsers, Python/ML) to free disk space
Guided feature development with codebase understanding and architecture focus
$ npx -y skills add davila7/claude-code-templates --agent claude-codeHow it fires
How this command gets triggered: by you, by Claude, or both.
/feature-devContext preview
What this command does when you run it.
Guided feature development with codebase understanding and architecture focus
description: Guided feature development with codebase understanding and architecture focus argument-hint: Optional feature description
You are helping a developer implement a new feature. Follow a systematic approach: understand the codebase deeply, identify and ask about all underspecified details, design elegant architectures, implement, test thoroughly, then review.
---
**Goal**: Understand what needs to be built
Initial request: $ARGUMENTS
**Actions**: 1. Create todo list with all phases 2. If feature unclear, ask user for:
3. Summarize understanding and confirm with user
---
**Goal**: Understand relevant existing code and patterns at both high and low levels
**Actions**: 1. Launch 2-3 code-explorer agents in parallel. Each agent should:
**Example agent prompts**:
2. Once the agents return, please read all files identified by agents to build deep understanding 3. Present comprehensive summary of findings and patterns discovered
---
**Goal**: Fill in gaps and resolve all ambiguities before designing
**CRITICAL**: This is one of the most important phases. DO NOT SKIP.
**Actions**: 1. Review the codebase findings and original feature request 2. Identify underspecified aspects: edge cases, error handling, integration points, scope boundaries, design preferences, backward compatibility, performance needs 3. **Present all questions to the user in a clear, organized list** 4. **Wait for answers before proceeding to architecture design**
If the user says "whatever you think is best", provide your recommendation and get explicit confirmation.
---
**Goal**: Design multiple implementation approaches with different trade-offs
**Actions**: 1. Launch 2-3 code-architect agents in parallel with different focuses: minimal changes (smallest change, maximum reuse), clean architecture (maintainability, elegant abstractions), or pragmatic balance (speed + quality) 2. Review all approaches and form your opinion on which fits best for this specific task (consider: small fix vs large feature, urgency, complexity, team context) 3. Present to user: brief summary of each approach, trade-offs comparison, **your recommendation with reasoning**, concrete implementation differences 4. **Ask user which approach they prefer**
---
**Goal**: Build the feature
**DO NOT START WITHOUT USER APPROVAL**
**Actions**: 1. Wait for explicit user approval 2. Read all relevant files identified in previous phases 3. Implement following chosen architecture 4. Follow codebase conventions strictly 5. Write clean, well-documented code 6. Update todos as you progress
---
**Goal**: Ensure comprehensive test coverage and all tests pass
**Actions**: 1. **Generate Tests**: Launch 2 test-generator agents in parallel with different focuses:
Each agent should analyze the new code and provide:
2. **Review Generated Tests**:
3. **Implement Tests**:
4. **Run Tests**: Launch test-runner agent to:
5. **Fix and Iterate**:
6. **Report Coverage**: Summarize test coverage achieved and any gaps
---
**Goal**: Ensure code is simple, DRY, elegant, easy to read, an
Ready-to-use configurations for Anthropic's Claude Code. A comprehensive collection of AI agents, custom commands, settings, hooks, external integrations (MCPs), and project templates to enhance your development workflow.
Repo: davila7/claude-code-templates
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