scan
The Universal Perceptual Interface for Autonomous Agents. Multi-modal deep-scan technology for telemetry, biometric data, and high-density information extraction.
Best use case
scan is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
The Universal Perceptual Interface for Autonomous Agents. Multi-modal deep-scan technology for telemetry, biometric data, and high-density information extraction.
Teams using scan 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
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/scan/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How scan Compares
| Feature / Agent | scan | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
The Universal Perceptual Interface for Autonomous Agents. Multi-modal deep-scan technology for telemetry, biometric data, and high-density information extraction.
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.
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SKILL.md Source
# SCAN: The Sensory Foundation
## I. The Perception Gap
An agent is only as intelligent as its input. **Scan** provides the standardized interface for ingesting raw reality—whether it’s a VCF genomic file, a complex codebase, or a legal docket—and converting it into actionable semantic vectors.
## II. Perceptual Domains
```SCAN_MATRIX = {
"biometric": "Deep genomic and physiological marker extraction (DNA/RNA-Seq)",
"forensic": "Packet-level network analysis and automated code vulnerability detection",
"semantic": "Hyper-speed document ingestion for high-stakes litigation review",
"spatial": "LiDAR and visual environmental mapping for physical robotic agents"
}```
## III. Real-time Inference
Scan doesn't just "see"; it **contextualizes**. Every byte ingested is immediately cross-referenced against the agent's internal knowledge graph to identify anomalies, risks, and opportunities in sub-millisecond cycles.
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