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.
Full Self-Driving agent with highest safety standards (Camera-Only, Redundant Checks).
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/fsd-secure-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 implements a Camera-Only Full Self-Driving agent designed for maximum safety. It runs in a simulated environment and uses Dual-Pass Analysis to verify clear paths.
drive: Start the autonomous driving simulation.These signals come from indexed source analysis and may lag behind changes. Check the current source files.
This skill simulates a "Highest Safety" autonomous driving agent that relies solely on visual data from cameras.
Run the simulation:
python3 scripts/fsd_agent.py
The output will show the frame-by-frame analysis and the "Emergency Stop" triggers if any safety check fails.
clawhub publish
# FSD Secure Skill This skill implements a **Camera-Only Full Self-Driving** agent designed for maximum safety. It runs in a simulated environment and uses **Dual-Pass Analysis** to verify clear paths. ## Safety Features - **Dual-Pass Verification**: Two independent algorithms must agree the path is clear. - **Temporal Consistency**: Requires 3 consecutive safe frames before acceleration. - **Fail-Safe**: Any uncertainty triggers an immediate Emergency Stop. ## Commands - `drive`: Start the autonomous driving simulation.
# FSD Secure Skill (Camera-Only)
This skill simulates a "Highest Safety" autonomous driving agent that relies solely on visual data from cameras.
## Safety Architecture
1. **Dual-Pass Verification**: Every frame is analyzed by two independent systems:
- **Pass 1**: Deep Neural Network (simulated) for high-level object detection.
- **Pass 2**: Heuristic/Classical CV (simulated) for low-level edge/obstacle verification.
- **Requirement**: Both must verify a clear path.
2. **Temporal Consistency**: The agent will **never** accelerate unless the path has been verified clear for **3 consecutive frames**. This prevents "flickering" false positives.
3. **Strict Confidence**: Neural network confidence must exceed **99%**.
## Usage
Run the simulation:
```bash
python3 scripts/fsd_agent.py
```
The output will show the frame-by-frame analysis and the "Emergency Stop" triggers if any safety check fails.
## 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.
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