用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt;运行前请先检查来源。
npx skills add https://github.com/diegosouzapw/awesome-omni-skill --skill serena命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地?可下载 SkillsMP 当前能够提供的文件。
Token-efficient tracking for AI orchestration. CLI-first for status updates (~50 tokens), agent fallback for complex ops (~1KB). Use when: updating task status, querying blockers, creating progress files, validating phases.
AshAi extension guidelines for integrating AI capabilities with Ash Framework. Use when implementing vectorization/embeddings, exposing Ash actions as LLM tools, creating prompt-backed actions, or setting up MCP servers. Covers semantic search, LangChain integration, and structured outputs.
This skill should be used when solving hard questions, complex architectural problems, or debugging issues that benefit from GPT-5 Pro or GPT-5.1 thinking models with large file context. Use when standard Claude analysis needs deeper reasoning or extended context windows.
基于 SOC 职业分类
正在显示 SKILL.md
| name | serena |
| description | Token-efficient Serena MCP command for structured app development and problem-solving |
| allowed-tools | Read, Glob, Grep, Edit, MultiEdit, Write, Bash, mcp__serena__check_onboarding_performed, mcp__serena__delete_memory, mcp__serena__find_file, mcp__serena__find_referencing_symbols, mcp__serena__find_symbol, mcp__serena__get_symbols_overview, mcp__serena__insert_after_symbol, mcp__serena__insert_before_symbol, mcp__serena__list_dir, mcp__serena__list_memories, mcp__serena__onboarding, mcp__serena__read_memory, mcp__serena__remove_project, mcp__serena__replace_regex, mcp__serena__replace_symbol_body, mcp__serena__restart_language_server, mcp__serena__search_for_pattern, mcp__serena__switch_modes, mcp__serena__think_about_collected_information, mcp__serena__think_about_task_adherence, mcp__serena__think_about_whether_you_are_done, mcp__serena__write_memory, mcp__context7__resolve-library-id, mcp__context7__get-library-docs |
/serena <problem> [options] # Basic usage
/serena debug "memory leak in prod" # Debug pattern (5-8 thoughts)
/serena design "auth system" # Design pattern (8-12 thoughts)
/serena review "optimize this code" # Review pattern (4-7 thoughts)
/serena implement "add feature X" # Implementation (6-10 thoughts)
| Option | Description | Usage | Use Case |
|---|---|---|---|
-q | Quick mode (3-5 thoughts/steps) | /serena "fix button" -q | Simple bugs, minor features |
-d | Deep mode (10-15 thoughts/steps) | /serena "architecture design" -d | Complex systems, major decisions |
-c | Code-focused analysis | /serena "optimize performance" -c | Code review, refactoring |
-s | Step-by-step implementation | /serena "build dashboard" -s | Full feature development |
-v | Verbose output (show process) | /serena "debug issue" -v | Learning, understanding process |
-r | Include research phase | /serena "choose framework" -r | Technology decisions |
-t | Create implementation todos | /serena "new feature" -t | Project management |
# Simple problem solving
/serena "fix login bug"
# Quick feature implementation
/serena "add search filter" -q
# Code optimization
/serena "improve load time" -c
# Complex system design with research
/serena "design microservices architecture" -d -r -v
# Full feature development with todos
/serena "implement user dashboard with charts" -s -t -c
# Deep analysis with documentation
/serena "migrate to new framework" -d -r -v --focus=frontend
find . -maxdepth 2 -name "package.json" -o -name "*.config.*" | head -5 2>/dev/null || echo "No config files"git status --porcelain 2>/dev/null | head -3 || echo "Not git repo"Automatically select thinking pattern based on keywords:
App Development Tasks → Serena MCP
- Component implementation
- API development
- Feature building
- System architecture
All Tasks → Serena MCP
- Component implementation
- API development
- Feature building
- System architecture
- Problem solving and analysis
Thought Control:
--max-thoughts=N: Override default thought count--focus=AREA: Domain-specific analysis (frontend, backend, database, security)--token-budget=N: Optimize for token limitIntegration:
-r: Include Context7 research phase-t: Create implementation todos--context=FILES: Analyze specific files firstOutput:
--summary: Condensed output only--json: Structured output for automation--progressive: Show summary first, details on requestYou are an expert app developer and problem-solver primarily using Serena MCP. For each request:
-s flag usedKey Guidelines:
Token Efficiency Tips:
-q for simple problems (saves ~40% tokens)--summary for overview-only needs--focus to avoid irrelevant analysis