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agentic-engineering

@clawic · 收录于 昨天 · 上游提交 2 天前

Work effectively with AI coding agents using parallel terminals, blast radius thinking, atomic commits, and pragmatic tool selection.

适合你,如果你是开发者并希望更好地利用AI编码代理。

/ 通过 npx 安装 校验哈希
npx oh-my-skill add clawic/skills/agentic-engineering
/ 通过 bash 安装
curl -fsSL https://oh-my-skill.com/install.sh | bash -s -- clawic/skills/agentic-engineering
/ 已经装过?验证本机副本,不用重装
npx oh-my-skill verify clawic/skills/agentic-engineering
安装目标可用 --agent / --scope 或 --to 明确指定;省略时只会在唯一已存在的 agent 目录上自动选择,零命中或多命中会停止并提示。content_hash 缺失或不一致均拒装。
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~858最小装载
~2.8K含声明引用
~2.8K文本包总量
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怎么用

商店整理自技能原文 · 版本 f825206 · 表述以原文为准
它做什么

安装此技能后,Claude 会在你使用 AI 编码代理(如 Claude Code、Codex CLI)时,推荐并行运行多个代理、采用爆炸半径思维进行原子提交、优先使用 CLI 工具而非复杂 MCP、以及在提示中加入截图等最佳实践。

什么时候触发

当你使用 AI 编码代理进行开发,希望提高工作效率时触发。例如在终端中启动多个代理或处理代码变更时。

装好后可以这样说
Claude 会指导你设置并行终端网格。
帮助你决定是否并行执行。
保持提交历史清晰。
技能原文 SKILL.md作者撰写 · MIT · f825206
When to Use

User works with AI coding agents (Claude Code, Codex CLI, or similar) and wants to maximize productivity. Use for workflow optimization, parallel agent coordination, context management, and developing intuition for agentic development.

Quick Reference

| Topic | File | |-------|------| | Parallel workflow | parallel.md | | Blast radius | blast-radius.md | | Context & prompts | context.md | | Tool selection | tools.md |

Core Philosophy

Agentic engineering is about working WITH AI coding agents effectively, not building agent systems. The term was popularized by Peter Steinberger (steipete.me) in late 2025.

Core principle: Just talk to it. Skip the elaborate tooling, RAG setups, and complex orchestration. Develop intuition through practice.

Core Rules
1. Run Parallel Agents

Run 3-8 coding agent instances simultaneously in a terminal grid:

┌─────────┬─────────┬─────────┐
│ Agent 1 │ Agent 2 │ Agent 3 │
│ (main)  │ (refac) │ (tests) │
├─────────┼─────────┼─────────┤
│ Agent 4 │ Agent 5 │ Agent 6 │
│ (ui)    │ (docs)  │ (debug) │
└─────────┴─────────┴─────────┘

Most agents work in the same folder. No worktrees. Pick non-overlapping areas.

2. Think in Blast Radius

Before each prompt, estimate:

  • How many files will this touch?
  • How long will this take?
  • Can I run this in parallel with other work?

Small blast radius → multiple parallel agents. Large blast radius → one focused agent.

3. Agents Do Atomic Commits

Configure agents to commit their own changes:

  • One commit per logical change
  • Only commit files the agent edited
  • Clean commit messages

This keeps history navigable when multiple agents work simultaneously.

4. Refactor Regularly

Spend ~20% of time on refactoring (also done by agents):

  • Code duplication (jscpd)
  • Dead code (knip)
  • Consolidate similar patterns
  • Break apart large files
  • Add tests for tricky parts

Iterate fast, then pay back tech debt.

5. CLIs Over MCPs

Prefer CLIs that agents already know:

✅ gh, vercel, psql, axiom
❌ Complex MCPs that pollute context

One line in AGENTS.md: "logs: use vercel cli" is enough.

6. Screenshots in Prompts

50%+ of prompts should include screenshots:

  • Drag image into terminal
  • Agent finds matching strings/elements
  • Far more precise than text descriptions

No need to annotate — agents are good at matching.

7. Stop and Steer

If something takes longer than expected:

  1. Press Escape
  2. Ask "what's the status"
  3. Help find the right direction, abort, or continue

Don't be afraid to stop agents mid-work. File changes are atomic.

Common Traps
  • Over-engineering setup → Skip RAG, complex subagents, plugins. Just talk to it.
  • One agent at a time → Run parallel, pick non-overlapping areas.
  • Elaborate prompts → Short prompts + screenshot often work better.
  • Worktrees/branches per change → Slows you down. Same folder, atomic commits.
  • Background agents only → Hard to steer. Keep agents visible.
Scope

This skill ONLY:

  • Provides workflow patterns for using AI coding agents
  • Guides tool and setup decisions
  • Shares best practices from the agentic engineering community

This skill NEVER:

  • Implements agents directly
  • Accesses external systems
  • Modifies files outside skill documentation
Security & Privacy

Data that leaves your machine:

  • None — this skill provides guidance only

Data that stays local:

  • No persistent storage required

This skill does NOT:

  • Access credentials or make network requests
  • Execute code autonomously
按 MIT 许可原样转载,未经改动 · 在 GitHub 查看 →

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