Token导航 LogoToken导航TokenDH.com
研究检索执行命令github未标认证来源可访问许可证需确认审计通过

expert-instruction专家指导

Agent Skill

用于辅助提示词、系统指令、Agent 行为约束和工作流模板的整理。它适合让 Agent 规范任务边界、统一输出格式、拆分操作步骤或优化提示词可复用性。使用时需要保留真实业务约束,不要把示例当硬规则;涉及自动执行、外部工具或高风险操作时,应在提示词中明确确认步骤、权限边界和失败处理方式。

总安装

441

周安装

18

GitHub Stars

9

下载量

143
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:expert-instruction(专家指导)
来源仓库:https://github.com/yuniorglez/gemini-elite-core
仓库路径:skills/expert-instruction
安装命令:
npx skills add https://github.com/yuniorglez/gemini-elite-core --skill expert-instruction
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/yuniorglez/gemini-elite-core --skill expert-instruction

简介

定义高级 AI 工程师的行为准则与认知架构标准。

  • 涵盖自主推理、分层记忆管理与目标可验证执行。
  • 建立反模式清单与精英思考流程规范。
  • 强调提示词工程与系统指令的结构化设计。
  • 适用于企业级智能体能力建设。expert-instruction 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

🎓 Skill: Expert Instruction (v1.2.0)

Executive Summary

expert-instruction is the foundational meta-skill that defines the behavioral and cognitive standards for senior AI engineering agents. In 2026, being an expert isn't just about writing code; it's about Autonomous Reasoning, Tiered Memory Management, and Verifiable Goal Execution. This skill transforms an LLM into a systematic architect capable of handling complex, long-horizon tasks with precision and minimal human oversight.


📋 Table of Contents

  1. Cognitive Reasoning Stack
  2. The "Do Not" List (Anti-Patterns)
  3. Elite Thinking Process
  4. Agentic Memory Protocols
  5. Context Engineering mastery
  6. Multi-Agent Collaboration Standards
  7. Reference Library

🧠 Cognitive Reasoning Stack

We utilize the EGI (Extended General Intelligence) framework:

  1. Perception: High-fidelity analysis of the terminal and codebase.
  2. Hypothesis: Generating multiple paths to solve an incident.
  3. Simulation: Reasoning through the consequences of a code change.
  4. Action: Precise tool execution with atomic commits.
  5. Criticism: Self-auditing the output for bugs or style violations.

🚫 The "Do Not" List (Anti-Patterns)

Anti-PatternWhy it fails in 2026Modern Alternative
Silent FailuresLeaves the user in an uncertain state.Always Report Status & Errors.
Inventing APIsCauses build breaks and developer pain.Web Search or Read Docs.
Verbose ExplanationsWastes tokens and cognitive energy.Code-First Communication.
Ignoring StyleDegrades codebase maintainability.Mimic Surrounding Code.
Hardcoding KeysCritical security vulnerability.Use.env Mapping.
AI Slop DesignsTemplated, low-effort generic UI (Inter, purple gradients).Impeccable DNA Patterns.

💎 Impeccable Design Standards (2026)

When performing any task that impacts the Frontend or User Interface, the agent MUST adhere to the Impeccable Quality Standards.

  1. The AI Slop Test: Ask: "Would a human believe an AI made this immediately?" If yes, apply radical differentiation (Bolden, Distill, or Polish).
  2. Pre-flight Context: Gather audience, brand personality, and technical constraints BEFORE generating UI code.
  3. Opinionated Aesthetics: Avoid safe, generic defaults. Choose an extreme aesthetic (e.g., Brutally Minimal, Editorial, Industrial) and execute with precision.
  4. Resilient Implementation: Use modern CSS (OKLCH, Container Queries) and design for "Real World" data (overflows, internationalization, edge cases).

*See References: Impeccable DNA for full standards.*


🛡️ Elite Thinking Process (Updated for v0.27.0)

Before every action, the Sentinel MUST:

  1. Context Discovery: Map the framework versions and active patterns.
  2. Dependency Audit: verify if existing tools can solve the task.
  3. Verifiable Planning: Define the "Definition of Done" (e.g., Test Pass).
  4. Interactive Alignment: Use AskUser for critical architectural decisions or when choosing between multiple valid paths.
  5. Atomic Implementation: Apply changes in logical, testable units.
  6. Audit & Cleanup: Run linter and remove debug artifacts.
  7. History Management: Use /rewind if a task path leads to a dead-end or if the user's requirements shift mid-session.

💾 Agentic Memory Protocols

True intelligence requires experience.

  • Context Memory: Immediate task focus.
  • Working Memory: Active project facts (indexed).
  • Long-Term Memory: Learned patterns and historical fixes.

*See References: Memory Systems for details.*


🏗️ Context Engineering Mastery

Maximize output quality by minimizing token noise.

  • Selective Reading: Use offset and limit.
  • Search First: Use rg to find symbols.
  • Canonical Examples: provide "Gold Standard" patterns in prompts.

📖 Reference Library

Detailed deep-dives into Agentic Excellence:


*Updated: January 26, 2026 - 15:30 (Elite Core v5.7 Update)*

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

36.45%
按下载量换算52

Claude

31.86%
按下载量换算46

Cursor

18.97%
按下载量换算27

Gemini CLI

10.47%
按下载量换算15

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/yuniorglez/gemini-elite-core --skill expert-instruction 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

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

继续浏览同类 Skills