Skill UI

This SDK provides comprehensive, production-ready patterns for interacting with the OpenEvidence clinical evidence API. It enables developers to efficiently query medical literature, retrieve clinical guidelines, and generate evidence-based recommendations. Key features include a singleton client for consistent authentication, robust error wrappers (handling retries, invalid keys), and structured data models designed to ensure audit compliance and detailed citation provenance in complex healthcare applications.

This skill guides implementing robust code signing for software artifacts (binaries, packages, containers). It ensures integrity and authenticity throughout the entire software supply chain. Learn to use traditional methods like GPG and modern, keyless approaches like Sigstore (cosign) to establish trust chains, verify provenance, and meet compliance standards (e.g., SLSA).

This guide details implementing robust container image provenance verification using Cosign, a Sigstore tool. It covers key-based and keyless (OIDC) signing methods, enabling secure supply chain practices. Users can sign images, attach critical attestations (such as SBOMs and vulnerability scans), and enforce verification in CI/CD pipelines and Kubernetes environments to ensure high integrity and trust.

Harbor is an open-source container registry designed for robust security and compliance. This guide details the comprehensive workflow for securing your container ecosystem by implementing advanced features such as vulnerability scanning (Trivy), image signing (Notary/Cosign), Role-Based Access Control (RBAC), and content trust policies. Learn how to enforce image provenance and maintain strict access control in Kubernetes environments.

This comprehensive guide outlines the end-to-end security lifecycle for Kubernetes applications deployed via Helm. It covers critical topics such as chart provenance verification (GPG signing), template scanning (using tools like kubesec and checkov), enforcing strict security contexts, managing secrets securely (ExternalSecrets), and defining robust RBAC rules for CI/CD pipelines.

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 guide details how to implement secure, keyless software signing using the Sigstore ecosystem components (Cosign, Fulcio, Rekor). It establishes cryptographic provenance for container images and binaries by binding identity via OIDC, ensuring verifiable integrity and tamper-proofing throughout the CI/CD supply chain.

This skill provides robust mechanisms to verify the integrity of AI agent plugins, tools, and dependencies. It generates deterministic SHA-256 manifests (INTEGRITY.json) for all components, allowing users to detect unauthorized modifications, track provenance, and ensure that deployed assets match their published versions. Use this during CI/CD pipelines, code review, and pre-production promotion to secure the entire agent ecosystem.

Utilize advanced media intelligence to analyze audio, image, video, and text for synthetic manipulation and AI-generated content. This skill detects deepfakes, traces the original AI synthesis source, applies and detects watermarks, verifies speaker identity, and provides comprehensive media provenance analysis, ensuring media authenticity claims are rigorously supported.

A comprehensive guide for advanced geospatial data processing using GeoPandas. This skill targets professional workflows involving planar vector data, emphasizing rigorous data provenance, coordinate reference system (CRS) management, and complex spatial operations. It details necessary safety contracts, correctness gates, and best practices for handling sensitive geographic information in reproducible Python environments.

This skill is designed to create editable, macro-free scientific posters in PowerPoint (.pptx) format for academic and conference use. It enforces rigorous content auditing, requiring authors to provide all assets and data locally. Use it when absolute control over physical dimensions, print readiness, provenance, and security (e.g., no macros or external APIs) is mandatory.

This guide provides comprehensive, version-aware documentation for using PufferLib in reinforcement learning pipelines. It details best practices for adapting Gymnasium/PettingZoo environments, managing different PufferLib versions (3.0.0 vs 4.0 source), and executing safe, reproducible training and evaluation routines. Key focus areas include environment contract validation, sandboxing native builds, and maintaining data provenance.