Skill UI

This specialized skill is designed for in-depth security and forensic analysis of Windows secrets protected by DPAPI. It maps the entire lifecycle of encrypted credentials, tracing the flow from the initial protected blob or masterkey through the context unwrapping (e.g., user logon, machine context, domain backup keys) to the specific service that finally accepts the plaintext secret. Use this to prove the decisive access edge in a complex compromise scenario.

A specialized skill for detecting discrepancies (drift) between declared API contracts (such as GraphQL schemas, OpenAPI specs, and RPC manifests) and the actual behavior of live backend handlers. It is used to identify hidden operations, contract mismatches, or vulnerabilities resulting from schema evolution, versioning skew, or implementation gaps. Must be used after initial sandbox assumptions are established.

This specialized skill is designed for deep forensic analysis in complex Windows environments, crucial for CTF and red teaming. It traces identity flows, including Active Directory (AD) origins, Kerberos ticket lifecycles, and OAuth authorization claims. Use it to correlate host artifacts (LSA, DPAPI, Sysmon) with identity evidence to map complete lateral movement and privilege escalation chains.

This specialized skill is designed for advanced forensic analysis and penetration testing within Windows environments. It focuses on extracting and proving the replayability of credentials, tickets, and secrets stored in LSASS memory, Kerberos ticket caches, DPAPI, and SSP artifacts. Use it to establish the minimal, actionable chain (host artifact -> extracted material -> accepted privilege) that proves a decisive edge for privilege escalation.

A specialized, downstream skill designed for forensic analysis within a confined sandbox environment, particularly for CTF challenges. It guides the user to inspect the full stack behavior, including API interactions, server routing, browser state (cookies, local storage), and asynchronous worker processes. Use this skill to trace complex, end-to-end request flows, debug authentication/session leaks, or diagnose discrepancies between frontend UI and backend enforcement.

Creates task-oriented technical documentation with progressive disclosure for READMEs, API docs, architecture docs, and markdown. Also generates formal security reports (reverse engineering, penetration testing, CTF, malware/APT analysis) in the user's project directory with Evidence-Finding-Path chain.

This skill facilitates the ingestion of unstructured clinical notes and reports from FHIR R4 EHR APIs (e.g., Epic, Cerner). It handles complex tasks including paginating large search results, decoding base64 attachments (PDF, text), and extracting narrative content. The extracted text is then passed to the OpenMed pipeline for HIPAA-compliant de-identification and subsequent NLP analysis, enabling structured data insights from raw clinical records.

This extension provides comprehensive management for external access using the standard Kubernetes Gateway API and Traefik as the underlying proxy. It supports multi-tenant scoping across cluster, workspace, and namespace levels, enabling robust, modern API gateway configuration within the KubeSphere ecosystem.

A comprehensive tool designed to help developers compare multiple technical approaches for solving a single problem. It systematically identifies and analyzes the trade-offs, complexity, performance, and learning curves associated with different design patterns (e.g., state management, data fetching, API design). Ideal for architectural reviews and making informed, robust technology stack decisions.

This skill resolves entities extracted by OpenMed (e.g., Disease, Drug) to standardized Concept Unique Identifiers (CUIs) within the UMLS Metathesaurus. It is essential for cross-vocabulary normalization, allowing users to unify concepts (like SNOMED CT, ICD-10, RxNorm) to a single canonical CUI. Crucially, the process relies entirely on the user's own UTS API key, ensuring that the Metathesaurus content is never bundled or cached.

This skill implements an advanced reference pattern for integrating with Monitoring Control Platform (MCP) servers. It ensures accurate data retrieval by first reading a domain-specific 'gotchas' reference file, mitigating query failures caused by complex server behaviors, pagination limits, or subtle API quirks. It analyzes issue data, groups errors by root cause, and generates a structured, actionable markdown report for improved system health visibility.

This skill standardizes free-text medication mentions extracted by OpenMed to RxNorm RxCUIs using the public RxNav API. It resolves complex relationships between brand names, generic ingredients, strengths, and dose forms, providing a stable, canonical code. Ideal for clinical interoperability, data analytics, de-duplication, and building US Core Medication resources.