ad-compliance-reviewer
Review ads and campaign setup for policy compliance on Meta (Facebook/Instagram), Google Ads, TikTok Ads, YouTube Ads, Amazon Ads, and DSP/programmatic.
Autonomous space navigation agent using optical quantum kernels for terrain classification.
Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.
SkillHub CLI
skillhub install aadipapp/space-autonomy-skillInspect the source and compatibility requirements, then follow its installation steps.
Give your agent the source link and ask it to inspect instructions and dependencies before explaining the installation steps.
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".
navigate: Process a sensor reading and decide on an action.These signals come from indexed source analysis and may lag behind changes. Check the current source files.
This skill simulates an autonomous agent for diverse space environments. It relies on Optical Quantum Kernels to classify terrain based on sensor data.
Space is unforgiving. This agent implements a "Highest Safety" protocol:
0.85, the agent immediately triggers SAFE MODE.The agent compares real-time sensor inputs against a "Knowledge Base" (Safe Ground, Rocks, Voids) using a simulated optical quantum computer.
Simulate a sensor reading (vector of 3 values):
python3 scripts/quantum_nav.py "0.1,0.12,0.1"
# Expected: Action: PROCEED
python3 scripts/quantum_nav.py "0.8,0.9,0.7"
# Expected: Action: AVOID / HALT
python3 scripts/quantum_nav.py "0.5,0.5,0.5"
# Expected: >>> TRIGGERING FAILSAFE: SAFE MODE <<<
clawhub publish
# 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.
# Space Autonomy Quantum Skill This skill simulates an autonomous agent for diverse space environments. It relies on **Optical Quantum Kernels** to classify terrain based on sensor data. ## Safety First Space is unforgiving. This agent implements a **"Highest Safety"** protocol: 1. **Failsafe Threshold**: If the quantum classifier's confidence is below `0.85`, the agent immediately triggers **SAFE MODE**. 2. **Redundancy**: Every classification is computed 3 times and averaged to mitigate quantum/optical noise. 3. **Default to Halt**: If a hazard is detected OR if the terrain is unknown, the agent stops. ## How it Works The agent compares real-time sensor inputs against a "Knowledge Base" (Safe Ground, Rocks, Voids) using a simulated optical quantum computer. - **High Kernel Value** -> High Similarity -> Confident Classification. - **Low Kernel Value** -> Low Similarity -> Unknown Terrain -> Safe Mode. ## Usage Simulate a sensor reading (vector of 3 values): # Case 1: Clear, safe terrain (matches 'SAFE_FLAT') ```bash python3 scripts/quantum_nav.py "0.1,0.12,0.1" # Expected: Action: PROCEED ``` # Case 2: Hazardous Rock (matches 'HAZARD_ROCK') ```bash python3 scripts/quantum_nav.py "0.8,0.9,0.7" # Expected: Action: AVOID / HALT ``` # Case 3: Unknown/Ambiguous Signal ```bash python3 scripts/quantum_nav.py "0.5,0.5,0.5" # Expected: >>> TRIGGERING FAILSAFE: SAFE MODE <<< ``` ## Publishing ```bash clawhub publish ```
Review ads and campaign setup for policy compliance on Meta (Facebook/Instagram), Google Ads, TikTok Ads, YouTube Ads, Amazon Ads, and DSP/programmatic.
MCP Engineering — Complete Model Context Protocol System
Incident Postmortem Generator
Complete SEO content creation system for AI agents. Research keywords, analyze competitors, write optimized articles, and track rankings — all through natural conversation. No APIs required.