space-autonomy-quantum

Autonomous space navigation agent using optical quantum kernels for terrain classification.

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Best use case

space-autonomy-quantum is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Autonomous space navigation agent using optical quantum kernels for terrain classification.

Teams using space-autonomy-quantum should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/space-autonomy-skill/SKILL.md --create-dirs "https://raw.githubusercontent.com/openclaw/skills/main/skills/aadipapp/space-autonomy-skill/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/space-autonomy-skill/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How space-autonomy-quantum Compares

Feature / Agentspace-autonomy-quantumStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Autonomous space navigation agent using optical quantum kernels for terrain classification.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

# Space Autonomy Quantum Skill

This skill simulates an autonomous agent for space exploration that uses **Optical Quantum Kernels** to classify terrain.
It emphasizes **highest safety** by implementing strict confidence thresholds. If the quantum classifier is uncertain, the agent triggers a failsafe "SAFE MODE".

## Features
- **Quantum Perception**: Uses simulated optical quantum interference to recognize terrain features.
- **Safety Failsafe**: Automatically halts if classification confidence is below 0.8.
- **Autonomous Decision Making**: Decides to "Navigate" or "Avoid" based on quantum kernel results.

## Commands

- `navigate`: Process a sensor reading and decide on an action.

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