Skill UI

Guides Rube MCP users through Supportivekoala automation via Composio, emphasizing tool discovery, connection checks, schema compliance, and multi-step execution for reliable workflow orchestration.

This skill outlines security best practices for the TwinMind AI meeting assistant. It covers crucial aspects like on-device audio processing, encrypted cloud backups, and managing microphone permissions. Use it when setting up new TwinMind instances or managing AI operations to ensure data privacy, compliance, and robust security for sensitive meeting data.

A comprehensive guide to managing training data and model artifacts securely on cloud GPU instances (e.g., Vast.ai). It covers best practices for data transfer (SCP, compressed, cloud staging), implementing AES-256 encryption, managing checkpoints to S3, and performing secure cleanup before instance destruction, ensuring compliance and data integrity.

Automates Verifiedemail workflows through Composio's Rube MCP, guiding tool discovery, connection verification, and multi-tool execution while enforcing schema compliance and session reuse for reliable automation.

This skill thoroughly inspects and validates Vertex AI Agent Engine deployments. It assesses critical components such as the Code Execution Sandbox, Memory Bank, A2A protocol compliance, security posture, and performance metrics. The tool generates weighted production-readiness scores (0-100%) and provides detailed, actionable recommendations to ensure the deployment is robust, secure, and ready for production use.

Guide for automating Webscraping AI workflows through Composio’s Webscraping AI toolkit using Rube MCP, covering connection checks, tool discovery, execution patterns, and schema compliance best practices.

This methodology converts verbose, natural language system instructions into an atomic, structured-label format (e.g., trigger:, action:). By structuring rules, it bypasses the limitations of natural language processing, ensuring LLMs allocate full attention to every constraint, thereby maximizing compliance, improving reliability, and reducing token usage.

Audit, validate, and enhance GEO structured data by detecting existing JSON-LD/microdata/RDFa, checking schema.org compliance, and generating ready-to-use JSON-LD to boost AI discoverability.

Trivy is a comprehensive open-source vulnerability scanner used for detecting vulnerabilities, misconfigurations, secrets, and license violations across OS packages, language dependencies, and container images. It integrates seamlessly into CI/CD pipelines for robust security testing and compliance.

This skill systematically probes an AI model's core behavioral patterns across six critical dimensions, including reasoning, refusal, formatting, and grounding. It generates a comprehensive, styled HTML report with radar charts and actionable insights, allowing users to understand a model's true capabilities, compare different models, or perform compliance and red-team assessments without needing an external API key.

AKF is the native metadata format specifically designed for tracking AI-generated or AI-modified content. It allows users to stamp files (including DOCX, PDF, images, and code) with detailed trust scores, source provenance, and compliance metadata. This tool is essential for professional workflows requiring strict auditing, compliance assurance, and verifiable data lineage, especially concerning regulations like the EU AI Act, HIPAA, and SOX.

This tool automates the end-to-end workflow for GDPR Data Subject Access Requests (DSAR). It handles identity verification, discovers PII across structured and unstructured data sources using NER and regex, maps data to Article 15 requirements, and generates auditable compliance reports, ensuring adherence to ICO/EDPB guidelines and scaling compliance efforts.