sadjad6/anomaly_detection
src/skills/data_science/anomaly_detection/SKILL.md
Detect anomalous observations in data
data-ai
Updated Apr 13, 2026
$ install --global
skillsauthnpx skillsauth add sadjad6/open-autonomous-research-lab anomaly_detectionInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
Security Scan Results
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3
Scanners Passed
9
Scanners in report
Clean
TrivyContainer and dependency vulnerability scanner
95%
Clean
SemgrepStatic code analysis for vulnerabilities
95%
Clean
mcp-scan (Snyk)Model Context Protocol security validation
95%
Skipped
Snyk (dep)Open source security scanning
50%
Skipped
Socket.devSupply chain security analysis
50%
Skipped
VirusTotalMulti-engine malware detection
50%
Skipped
CrowdStrikeAdvanced threat intelligence
50%
Skipped
OSV-ScannerOpen Source Vulnerability database check
50%
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OWASP Dep-Check
50%
Last scanned: Apr 13, 2026, 2:39 AM111.9s2 files scanned
SKILL.md
- name:
- anomaly_detection
- description:
- Detect anomalous observations in data
Anomaly Detection
Description
Detect anomalous observations in data
When to Use
When finding unusual patterns or fraud
Workflow
- Choose method\n2. Fit detector\n3. Score observations
Tools Used
sklearn
Examples
from src.skills.data_science.anomaly_detection import Skill
skill = Skill()
result = await skill.run(SkillInput(data={"key": "value"}))
Best Practices
Combine multiple methods for robustness
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