Agentic Engineering
/install agentic-engineering-ecc
Agentic Engineering
Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing. Adapted from everything-claude-code by @affaan-m (MIT).
Quick Start
- Define completion criteria — write acceptance criteria and success metrics before execution
- Create baseline evals — write capability and regression tests that capture current state
- Decompose work — break into 15-minute units, each independently verifiable with a single dominant risk
- Route models by complexity — Haiku for narrow tasks, Sonnet for implementation, Opus for architecture
- Run post-implementation evals — measure deltas, confirm no regressions
Key Concepts
- Eval-first execution: Run tests before coding; measure against known baseline; catch regressions early
- 15-minute unit rule: Each task should have one clear risk, one verifiable outcome, be completable in ~15 minutes
- Model tier matching: Complexity determines model — don't overpay for simple tasks, don't underpay for hard ones
- Review focus: Prioritize invariants, error boundaries, security, coupling — not style (automation handles that)
- Session strategy: Continue for coupled units; reset after major phase transitions; compact at milestones
Common Usage
Setting up eval-first for a feature:
1. Define acceptance criteria (user-facing behavior)
2. Write capability eval (can the system do the required task?)
3. Write regression eval (does existing functionality still work?)
4. Execute feature implementation with model routing
5. Re-run evals, compare deltas
6. Document any new risks discovered during review
Model routing example:
- Haiku: boilerplate generation, narrow edits, classification
- Sonnet: feature implementation, small refactors, test writing
- Opus: multi-file changes, root-cause analysis, architecture decisions
Cost discipline: Track per task: model tier, token estimate, retries, wall-clock time, success/failure. Escalate model tier only when lower tier fails with clear reasoning gap, not on uncertainty.
References
references/eval-patterns.md— detailed eval-first loop patternsreferences/decomposition-rules.md— 15-minute unit principle and task breakdown examplesreferences/review-checklist.md— what to focus on in code review (invariants, boundaries, security, coupling)
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install agentic-engineering-ecc - 安装完成后,直接呼叫该 Skill 的名称或使用
/agentic-engineering-ecc触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
Agentic Engineering 是什么?
Workflow pattern for AI-assisted engineering using eval-first execution, task decomposition, and cost-aware model routing. Trigger phrases: agentic engineeri... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 137 次。
如何安装 Agentic Engineering?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install agentic-engineering-ecc」即可一键安装,无需额外配置。
Agentic Engineering 是免费的吗?
是的,Agentic Engineering 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
Agentic Engineering 支持哪些平台?
Agentic Engineering 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(linux, darwin, win32)。
谁开发了 Agentic Engineering?
由 Deonte Cooper(@djc00p)开发并维护,当前版本 v1.0.0。