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pex-lo-skill-creatorpex lo 技能创建器

Agent Skill

pex-lo-skill-creator 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

349

周安装

14

GitHub Stars

公开资料未说明

下载量

113
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

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:pex-lo-skill-creator(pex lo 技能创建器)
来源仓库:https://github.com/zpankz/mcp-skillset
仓库路径:skills/pex-lo-skill-creator
安装命令:
npx skills add zpankz/mcp-skillset --skill "pex-lo-skill-creator"
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。

AgentSkills.tonpx skills
npx skills add zpankz/mcp-skillset --skill "pex-lo-skill-creator"

简介

pex-lo-skill-creator 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。

  • 适用于发现并安装 AI 代理技能的通用工具场景。
  • 通过 npx skills add zpankz/mcp-skillset --skill "pex-lo-skill-creator" 安装,需结合原始 README 确认具体用法。
  • 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。
  • 可参考来源仓库 https://github.com/zpankz/mcp-skillset/tree/main/skills/pex-lo-skill-creator 获取更多细节。

SKILL.md

name
pex-lo-skill-creator
description
|
version
1.0.0
category
First-Principles Biophysical Critical Care Medical Reasoning To Emergent Systems Thinking
tags
author
mcp-skillset
license
MIT
created
2026-01-15
last_updated
2026-01-15

pex-lo-skill-creator

Overview

This skill provides guidance for first-principles biophysical critical care medical reasoning to emergent systems thinking tasks using modern best practices and proven patterns.

When to Use This Skill

Use this skill when:

  • Working with first-principles biophysical critical care medical reasoning to emergent systems thinking projects
  • Implementing first-principles biophysical critical care medical reasoning to emergent systems thinking-related features
  • Following best practices for first-principles biophysical critical care medical reasoning to emergent systems thinking

Core Principles

1. Follow Industry Standards

Always adhere to established conventions and best practices

# Example: Follow naming conventions and structure
# Adapt this to your specific domain and language

2. Prioritize Code Quality

Write clean, maintainable, and well-documented code

  • Use consistent formatting and style
  • Add meaningful comments for complex logic
  • Follow SOLID principles where applicable

3. Test-Driven Approach

Write tests to validate functionality

  • Unit tests for individual components
  • Integration tests for system interactions
  • End-to-end tests for critical workflows

Best Practices

Structure and Organization

  • Organize code into logical modules and components
  • Use clear and descriptive naming conventions
  • Keep files focused on single responsibilities
  • Limit file size to maintain readability (< 500 lines)

Error Handling

  • Implement comprehensive error handling
  • Use specific exception types
  • Provide actionable error messages
  • Log errors with appropriate context

Performance Considerations

  • Optimize for readability first, performance second
  • Profile before optimizing
  • Use appropriate data structures and algorithms
  • Consider memory usage for large datasets

Security

  • Validate all inputs
  • Sanitize outputs to prevent injection
  • Use secure defaults
  • Keep dependencies updated

Common Patterns

Pattern 1: Configuration Management

# Separate configuration from code
# Use environment variables for sensitive data
# Provide sensible defaults

Pattern 2: Dependency Injection

# Inject dependencies rather than hardcoding
# Makes code testable and flexible
# Reduces coupling between components

Pattern 3: Error Recovery

# Implement graceful degradation
# Use retry logic with exponential backoff
# Provide fallback mechanisms where appropriate

Anti-Patterns

❌ Avoid: Hardcoded Values

Don't hardcode configuration, credentials, or magic numbers

# BAD: Hardcoded values
API_TOKEN = "hardcoded-value-bad"  # Never do this!
max_retries = 3

Instead: Use configuration management

# GOOD: Configuration-driven
API_TOKEN = os.getenv("API_TOKEN")  # Get from environment
max_retries = config.get("max_retries", 3)

❌ Avoid: Silent Failures

Don't catch exceptions without logging or handling

# BAD: Silent failure
try:
    risky_operation()
except Exception:
    pass

Instead: Explicit error handling

# GOOD: Explicit handling
try:
    risky_operation()
except SpecificError as e:
    logger.error(f"Operation failed: {e}")
    raise

❌ Avoid: Premature Optimization

Don't optimize without measurements

Instead: Profile first, then optimize

  • Measure performance with realistic workloads
  • Identify actual bottlenecks
  • Optimize the critical paths only
  • Validate improvements with benchmarks

Testing Strategy

Unit Tests

  • Test individual functions and classes
  • Mock external dependencies
  • Cover edge cases and error conditions
  • Aim for >80% code coverage

Integration Tests

  • Test component interactions
  • Use test databases or services
  • Validate data flow across boundaries
  • Test error propagation

Best Practices for Tests

  • Make tests independent and repeatable
  • Use descriptive test names
  • Follow AAA pattern: Arrange, Act, Assert
  • Keep tests simple and focused

Debugging Techniques

Common Issues and Solutions

Issue: Unexpected behavior in production

Solution:

  1. Enable detailed logging
  2. Reproduce in staging environment
  3. Use debugger to inspect state
  4. Add assertions to catch assumptions

Issue: Performance degradation

Solution:

  1. Profile the application
  2. Identify bottlenecks with metrics
  3. Optimize critical paths
  4. Monitor improvements with benchmarks

Related Skills

  • test-driven-development: Write tests before implementation
  • systematic-debugging: Debug issues methodically
  • code-review: Review code for quality and correctness

References

  • Industry documentation and best practices
  • Official framework/library documentation
  • Community resources and guides
  • Code examples and patterns

Version History

  • 1.0.0 (2026-01-15): Initial version

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

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

OpenCode

30.76%
按下载量换算35

Claude Code

23.27%
按下载量换算26

windsurf

18.96%
按下载量换算21

Codex

13.16%
按下载量换算15

kiro-cli

7.74%
按下载量换算9

mcpjam

3.79%
按下载量换算4

安全审计

暂无安全审计结果可展示。

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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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