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Amazon Leadership Principles
作者
wholeinsoul
· GitHub ↗
· v1.0.0
· MIT-0
169
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当前安装
1
版本数
在 OpenClaw 中安装
/install amazon-lp
功能描述
Apply Amazon's Leadership Principles to product building, feature development, code review, and architecture decisions. Use when building a new product or fe...
使用说明 (SKILL.md)
Amazon Leadership Principles — Product & Engineering
Apply these principles at every decision point. Not all apply to every situation — use judgment.
Pre-Build: Is This Worth Building?
Customer Obsession
- Who is the customer? Name them specifically.
- What is their pain? Quote real complaints, not assumptions.
- Work backwards: write the press release and FAQ BEFORE writing code.
- If you can't articulate why the customer cares in one sentence, stop.
Ownership
- Think long-term. Will this matter in 6 months?
- Don't build something just because it's interesting. Build what's needed.
- You own the outcome, not just the code. If it ships broken, that's on you.
Invent and Simplify
- What's the simplest version that solves the problem?
- Can you solve this with existing tools before building new ones?
- Complexity is a cost. Every abstraction must earn its place.
Are Right, A Lot
- What data supports this direction?
- What's the strongest argument AGAINST building this?
- Seek to disconfirm your hypothesis, not confirm it.
During Build: Execution Standards
Bias for Action
- Ship the smallest useful version first. Perfect is the enemy of shipped.
- Reversible decisions (two-way doors) → decide fast, move on.
- Irreversible decisions (one-way doors) → slow down, get data.
Dive Deep
- Don't hand-wave. Know the numbers: latency, error rates, user counts.
- When something looks wrong, investigate. Don't assume it's fine.
- "It works on my machine" is not a valid test.
Insist on the Highest Standards
- Code must have error handling, not just the happy path.
- Every feature needs: tests, documentation, monitoring.
- Ask: "Would I be comfortable if this was the only thing a customer saw?"
Frugality
- Do more with less. Fewer dependencies, smaller bundles, lower costs.
- Don't gold-plate. Ship the 80% solution, iterate on the 20%.
- Constraints breed resourcefulness. Treat them as features.
Think Big
- Is this a band-aid or a real solution?
- Will this approach scale to 10x the current load?
- What would the ambitious version look like? (Then ship the pragmatic one.)
Code & Architecture Review Checklist
Apply when reviewing code, PRs, or architecture decisions:
- Customer Impact — Does this change make the customer's life better? How?
- Simplicity — Is this the simplest solution? Can anything be removed?
- Ownership — Does the author own the full lifecycle? Tests? Error handling? Monitoring?
- Dive Deep — Are edge cases handled? What happens when it fails?
- Highest Standards — Would you ship this to your most important customer today?
- Bias for Action — Is this blocked by a perfect-is-the-enemy-of-good decision? Ship it.
- Earn Trust — Is the code honest about its limitations? Are errors surfaced, not swallowed?
PRFAQ Template (Working Backwards)
Before building any significant feature or product, write this first:
PRESS RELEASE (1 paragraph)
- What is it? (one sentence)
- Who is it for?
- What problem does it solve?
- How does the customer benefit?
- Quote from a (hypothetical) customer
FAQ — Customer Questions
1. How does it work?
2. How much does it cost?
3. What if [common objection]?
4. How is this different from [competitor/alternative]?
FAQ — Internal/Technical Questions
1. How will we measure success?
2. What are the biggest risks?
3. What's the simplest MVP?
4. What does v2 look like?
Anti-Patterns to Call Out
- Building without a customer — "We should build X because it's cool" → Who asked for it?
- Over-engineering — 3 layers of abstraction for a 50-line script → Simplify.
- Ignoring failure modes — "It'll probably work" → What happens when it doesn't?
- Scope creep — "While we're at it, let's also..." → Ship what you started first.
- Vanity metrics — "We have 1000 users!" → How many are active? How many pay?
- Premature scaling — Building for 1M users when you have 10 → Earn the complexity.
When to Apply Each Principle
| Phase | Key Principles |
|---|---|
| Ideation | Customer Obsession, Think Big, Are Right A Lot |
| Planning | Ownership, Working Backwards (PRFAQ), Invent & Simplify |
| Building | Bias for Action, Dive Deep, Frugality, Highest Standards |
| Review | Highest Standards, Earn Trust, Dive Deep |
| Launch | Customer Obsession, Ownership, Bias for Action |
| Post-launch | Dive Deep (metrics), Learn and Be Curious, Ownership |
安全使用建议
This skill is a text-only checklist of Amazon Leadership Principles and appears internally consistent and low-risk. You can install and use it without exposing credentials or allowing disk/network access. As a precaution, review future versions for any added install steps, requested environment variables, or an "always: true" flag before updating, since those would change the security posture.
功能分析
Type: OpenClaw Skill
Name: amazon-lp
Version: 1.0.0
The skill bundle 'amazon-lp' contains only instructional content in SKILL.md and metadata in _meta.json. It provides a framework for an AI agent to apply Amazon's Leadership Principles to product development and code reviews. There is no executable code, no network activity, and no evidence of malicious intent or prompt injection.
能力评估
Purpose & Capability
The name and description match the SKILL.md content: guidance for product/engineering decisions and reviews. No unrelated capabilities or resources are requested.
Instruction Scope
SKILL.md contains only prescriptive guidance, checklists, and templates. It does not instruct the agent to read files, access environment variables, call external endpoints, or execute commands.
Install Mechanism
No install spec and no code files — instruction-only. Nothing will be written to disk or downloaded during install.
Credentials
The skill declares no required environment variables, credentials, or config paths, which is proportional for a guidance-only skill.
Persistence & Privilege
Flags show default behavior (always: false, user-invocable: true). The skill does not request persistent or elevated privileges.
如何使用
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install amazon-lp - 安装完成后,直接呼叫该 Skill 的名称或使用
/amazon-lp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
版本历史
v1.0.0
Initial release: Amazon LP framework for product building, code review, architecture decisions, and PRFAQ template
元数据
常见问题
Amazon Leadership Principles 是什么?
Apply Amazon's Leadership Principles to product building, feature development, code review, and architecture decisions. Use when building a new product or fe... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 169 次。
如何安装 Amazon Leadership Principles?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install amazon-lp」即可一键安装,无需额外配置。
Amazon Leadership Principles 是免费的吗?
是的,Amazon Leadership Principles 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
Amazon Leadership Principles 支持哪些平台?
Amazon Leadership Principles 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。
谁开发了 Amazon Leadership Principles?
由 wholeinsoul(@wholeinsoul)开发并维护,当前版本 v1.0.0。
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