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.

Cosign is a powerful Sigstore tool designed to secure container images and OCI artifacts. It allows users to sign and verify image provenance using both traditional key-based methods and modern, keyless OIDC workflows. This skill covers generating signatures, attaching critical metadata like SBOM and SLSA attestations, and implementing admission controls for robust supply chain security.

This comprehensive guide details best practices for securing Helm chart deployments within Kubernetes. It covers critical security measures including verifying chart signatures and provenance, scanning templates for configuration misconfigurations, enforcing Pod Security Contexts via values.yaml, managing sensitive data using external secret stores, and scoping RBAC roles for CI/CD pipelines. Essential for maintaining supply chain integrity and meeting compliance standards.

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.

Analyze, validate, convert, and transform materials structures and computed data using pymatgen APIs, including symmetry, phase diagrams, and bounded Materials Project queries with provenance.

This skill enables reproducible retrieval of facts from public scientific, regulatory, and financial databases. It catalogs 80 databases with documented API access patterns, allowing users to query authoritative sources with explicit endpoints, filters, and pagination. The skill ensures data provenance, handles rate limits, and verifies counts to guarantee completeness. It is designed for biomedical, genomic, and chemical data retrieval where accuracy matters more than general knowledge inference.

This tool functions as a post-task epilogue, designed to audit and record the entire research journey. It scans the conversation history at the end of a coding or research session to extract critical research artifacts, including decisions, experiments, dead ends, claims, heuristics, and major pivots. It systematically writes this provenance data into the structured `ara/` directory, ensuring a faithful and auditable trace of how the project truly evolved.

MockHunter is an advanced skill designed to audit live web pages, providing a comprehensive reality check on visible data. It analyzes every element to determine its true source: whether it is REAL (from the database), MOCK (simulated data), LLM-generated, HARDCODED, BROKEN (broken endpoints), or UNKNOWN. Ideal for auditing AI-generated UIs or reviewing proof-of-concept MVPs before customer sign-off.

Provides high-level strategic guidance for founders and Chief Data Officers (CDOs) in startups. This skill covers critical decisions such as AI training data rights and consent provenance, selecting optimal data architectures (warehouse, lakehouse, data mesh), valuing customer data as a strategic asset for M&A or fundraising, and planning data team organizational evolution. It focuses exclusively on strategic decision-making, not tactical engineering.

This skill facilitates the systematic triage and closure of open promises or commitments within a project context. It guides the user to reliably close these commitments using verifiable, real-world outcomes via the acc_act(runtime="outcome") command. It emphasizes maintaining rigorous provenance discipline, ensuring that status updates are based only on external or runtime validated results, thereby maximizing data integrity and accountability.

Tool to embed C2PA (Content Provenance) manifests into AI-generated multimedia assets (image, video, audio, PDF). This mechanism adds a machine-readable provenance trail detailing the generator, prompt, and review history. Essential for complying with global regulations like the EU AI Act Article 50, ensuring verifiable digital authenticity, and building brand trust.

A comprehensive guide for preparing scholarly manuscripts involving spatial data. It outlines best practices for documenting data provenance (sources, projections, processing chains), ensuring reproducibility, and adhering to critical ethical standards such as geoprivacy and human-subjects protection. Essential for maintaining research integrity in academic publishing.