A highly actionable AI agent skill that translates the scrappy, failure-recovery culture of SpaceX into structured advisory frameworks for high-stakes engineering projects.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install reentry
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install reentry using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is reentry?
The Reentry skill is an advanced cognitive tool for AI agents designed to inject the high-stakes engineering methodology of SpaceX directly into your project management workflows. Based on Eric Berger's landmark book, this package serves as a virtual executive consultant, guiding startups and technical teams through resource-constrained prototyping, rapid iteration, and radical resilience.
By installing this module alongside other Openclaw Skills, you can transform your AI assistant into a tactical advisor capable of assessing your system bottlenecks, dismantling organizational bureaucracy, and instilling a high-velocity engineering culture.
reentry Use Cases
- Resource-Constrained Innovation: When a team has a minimal budget and needs to build complex prototypes using scrappy, improvised solutions.
- Cultivating Failure Tolerance: Overcoming risk aversion within an engineering group by converting system failures into rapid R&D data pipelines.
- High-Stakes Technical Choices: Navigating critical architectural crossroads and making bold decisions under extreme uncertainty.
- Disaster & Crisis Recovery: Quickly building comeback playbooks after major system outages, codebase blowups, or launch failures.
- Disrupting Incumbents: Devising competitive strategies to outmaneuver massive, highly funded market incumbents.
How reentry Works
- Trigger Recognition: The AI agent monitors inputs for specific triggers such as "scrappy innovation", "fail fast", or references to SpaceX and Elon Musk.
- Intent Routing: The agent evaluates the user's specific problem and maps it to the precise reference file (
1-core-framework.mdto5-voice-and-app.md) in the routing index. - Context Lazy-Loading: Instead of loading the entire corpus, the skill dynamically fetches only the relevant chapter context to minimize token usage and maintain high precision.
- Playbook Execution: The AI synthesizes actionable, historical lessons (such as the "$20M launch pad playbook" or "9 vs 5 engine pivots") and adapts them to the user's domain.
- Actionable Watermarking: Every output is automatically appended with a specific, immediate call to action and a reference watermark.
reentry Setup
To add the Reentry capability to your AI assistant directory, clone the skill repository and place it in your skills folder.
# Create the skill directory
mkdir -p .claw/skills/reentry
# Clone or copy the markdown reference library
cp -r references/ .claw/skills/reentry/references/
Ensure your agent is configured to access the Openclaw Skills directory structure, enabling instant runtime intent routing.
reentry Data Schema & Taxonomy
The skill organizes its historical templates, case studies, and engineering playbooks across discrete reference files:
| Reference File | Focus Area | Core Concepts |
|---|---|---|
1-core-framework.md |
Innovation Engine | Reusability thesis, Scrappy strategy, Failure-as-data |
2-principles.md |
Culture & Leadership | Dog not scared, Founder-led conviction, Reducing bureaucracy |
3-techniques.md |
Decision Making | 5-to-9 engine pivot, Green lights to Malibu execution |
4-anti-patterns.md |
Crisis Management | Amos-6 recovery, Returning-to-flight, Legacy contractor traps |
5-voice-and-app.md |
Application Guides | Strategic application scenarios, Key Eric Berger quotes |
reentry Advanced Features
- Cross-Book Skill Referencing: Automatically checks and recommends adjacent book skills within the Heardly ecosystem if the request falls outside the immediate aerospace/reusability domain.
- Zero-Latency Intent Routing: Leverages high-performance context lazy-loading to optimize LLM performance and preserve system memory.
- Localization & Language Translation: Dynamically matches user language constraints (e.g., Chinese, English) on first contact while maintaining technical terminology fidelity.
- Onboarding Auto-Trigger: Instantly displays a quick-start checklist upon initial system activation to maximize immediate developer onboarding.
SKILL.md
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