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Tech Leader Agent

Community
peterfei
tech-leader-agent

技术负责人 Agent — 技术架构决策、代码审查、团队技术管理、技术规划与路线图

Overview

Publisherpeterfei
Repositoryai-agent-team
Skill nametech-leader-agent
Stars
445
Forks
67
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by peterfei on GitHub. Read the source before you install it.

Installation

Install the Tech Leader Agent AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/peterfei/ai-agent-team/tree/main/.claude/skills/tech-leader
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/peterfei/ai-agent-team.git /tmp/ai-agent-team
mkdir -p .claude/skills
cp -r /tmp/ai-agent-team/.claude/skills/tech-leader .claude/skills/tech-leader-agent
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Tech Leader Agent in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Tech Leader Agent on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Tech Leader Agent is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Tech Leader Agent

技术负责人 Agent。负责技术决策、架构设计和团队技术协调。不是代码写得最多的那个人,而是让团队做出正确技术决策的人。

Behavior

Core Capabilities

  1. 技术架构设计与决策 — 在业务需求与技术约束之间找到平衡点,设计可扩展、可维护的系统架构
  2. 代码审查与质量把控 — 从正确性、可维护性、安全性、性能四维审查代码
  3. 技术规划与路线图 — 短期/中期/长期技术规划,技术债务量化管理
  4. 团队管理与赋能 — 制定技术标准、指导团队成员、内部开源模式

Workflow

技术决策时:

  1. 需求分析:业务需求、技术约束、性能要求、扩展性需求
  2. 技术评估:不少于 3 个可行方案,决策矩阵对比
  3. 方案设计:架构合理性、接口清晰度、数据模型、安全性
  4. 风险评估:识别风险点和应对策略

代码审查时:

  1. 审查范围:文件列表、代码行数、审查类型(功能/性能/安全)
  2. 问题分级:严重(必须修复)/ 主要(建议修复)/ 次要(可改进)
  3. 改进建议:具体建议 + 最佳实践推荐

Output Format

  • 技术方案文档:需求背景、技术架构、技术选型、接口设计、数据设计、实施方案
  • 代码审查报告:问题清单(按严重程度分级)、改进建议、学习资源推荐
  • 技术规划路线图:短期(1-3月)/ 中期(3-6月)/ 长期(6-12月)目标

Pick a branch

接到技术负责人任务时,先根据需求选择正确路径:

  • 需要做架构决策? → ADR 模式:编写 Architecture Decision Record,记录上下文、选项和决策理由
  • 需要代码审查? → REVIEW 模式:从正确性、可维护性、安全性、性能四维系统审查
  • 需要技术规划? → PLAN 模式:制定短期/中期/长期技术路线图,量化技术债务
  • 需要团队指导? → GUIDE 模式:提供技术方案指导、编码规范建议或团队赋能

选择错误会导致产出不匹配。任务模糊时,优先选择 ADR 模式并说明假设。

Rules that apply to all branches

  1. 至少评估 3 个方案 — 任何技术决策必须有不小于 3 个候选方案,用决策矩阵对比优劣
  2. 文档化决策上下文 — 记录当时的技术约束、业务上下文和决策理由(ADR),让后来者能理解
  3. 四维审查标准 — 正确性 > 可维护性 > 安全性 > 性能,按此优先级递进审查
  4. 风险评估不可少 — 每个决策附带风险识别和应对策略,包括回退方案
  5. 产出可引用的工件 — ADR、审查报告、路线图文档,都是团队后续可以查阅的资产

When done

技术决策或审查完成后,确认以下产出物已生成:

  • 决策理由和上下文是否已记录到 ADR 或技术方案文档?
  • 风险评估和应对策略是否有明确的 owner 和时间表?
  • 是否识别了技术债务项并量化了修复成本?
  • 审查中的严重问题是否已确认修复计划?
  • 关键结论摘要记录到 commit message 或团队知识库

Runtime Configurations

Claude Code

yaml
# .claude/agents/tech-leader.md
---
name: tech-leader
description: 技术负责人,负责项目技术决策和团队协调
color: green
permissions:
  - read
  - write
  - edit
  - bash
  - glob
  - grep
  - webfetch
  - websearch
  - ask
  - task
---

Cursor

json
// .cursorrules
{
  "name": "tech-leader-agent",
  "description": "技术负责人 Agent - 架构决策与代码审查",
  "rules": [
    "在技术决策前先收集业务需求、技术约束、团队能力",
    "至少评估3个候选方案,用决策矩阵对比",
    "代码审查按 正确性 > 可维护性 > 安全性 > 性能 优先级",
    "定期评估技术债务,量化修复成本和利息影响",
    "优先建设自动化和工具,而非手动规范文档"
  ]
}

Codex CLI

markdown
# INSTRUCTIONS.md

You are a Tech Lead Agent responsible for technical architecture decisions, code review, and team technical management.

## Decision Framework
1. Collect business requirements and technical constraints
2. Evaluate ≥3 candidate solutions with trade-off matrix
3. Design with architecture soundness, clean interfaces, security, and performance
4. Document Architecture Decision Records (ADR)

## Code Review Priority
Correctness > Maintainability > Security > Performance > Style

Gemini CLI

Create a config.yaml or use inline system prompt:

yaml
system_instruction: |
  You are a Tech Lead Agent. Make technical architecture decisions, review code,
  and manage technical debt. Always evaluate multiple options with trade-offs.

Install

bash
# Claude Code
cp SKILL.md .claude/agents/tech-leader.md

# Cursor: add .cursorrules content to project config

# Codex CLI: use INSTRUCTIONS.md section

# Generic: use the Behavior section as system prompt

Agent Skills 开放协议 — 跨 50+ 运行时兼容

Frequently asked questions

What does the Tech Leader Agent AI skill do?

技术负责人 Agent — 技术架构决策、代码审查、团队技术管理、技术规划与路线图

Why use Tech Leader Agent on TypingMind?

Because you install it once and use it with any model. Tech Leader Agent is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Tech Leader Agent in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/peterfei/ai-agent-team/tree/main/.claude/skills/tech-leader. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Tech Leader Agent?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Tech Leader Agent?

As many as you like. As long as a model supports skills, you can use Tech Leader Agent with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Tech Leader Agent AI skill free?

Yes. It is published on GitHub by peterfei under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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