Skill UI

This specialized skill is designed for Digital Forensics and Incident Response (DFIR) scenarios. It correlates evidence from multiple disparate sources—including EVTX, PCAP, registry, memory, and filesystem artifacts—to build a comprehensive, ordered, and replayable forensic timeline. Use it when the goal is to map the full sequence of attacker actions, establishing initial access, lateral movement, and persistence chains based on cross-source evidence correlation.

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 skill is designed for deep security and behavioral analysis within the Kubernetes control plane. It specializes in tracing complex interactions, including RBAC edge cases, service-account trust paths, admission webhook behavior, resource mutation, and cluster-level state drift. Use it when diagnosing why live workloads differ from manifest declarations, or when investigating cluster-wide permission issues.

This specialized skill is designed to trace and prove the complete flow of OAuth or OIDC authentication, acting as a downstream specialization after an orchestrator has established sandbox assumptions. It meticulously tracks the entire journey—from initial redirect and parameter handling (state, nonce, PKCE) through token exchange, claim mapping, and ultimately to the point where an identity or privilege is accepted by the backend service. Use this when the critical task is proving the security and mechanics of the authentication chain.

This advanced skill is designed for security research and CTF environments to trace subtle divergences in request handling across multiple network hops (proxies, gateways, backend servers). It focuses on identifying vulnerabilities stemming from differential interpretation of headers, path normalization, transfer framing (CL/TE), and host derivation, crucial for detecting request smuggling and parsing inconsistencies.

This specialized skill is used to trace complex network requests through multi-layered infrastructure, such as reverse proxies, container boundaries, and various header manipulations. It is essential for determining which specific node, proxy rule, or derived header ultimately serves a live request within a sandboxed environment. Use it when analyzing VHost routing, path rewrites, or X-Forwarded headers to pinpoint the decisive backend.

A specialized downstream skill for deep analysis of complex web rendering pipelines. Use this to trace vulnerabilities or logical flaws residing in Server-Side Rendering (SSR), template data, route loaders, or client-server hydration boundaries. It compares template-level gating against backend handler enforcement to pinpoint the decisive weak point in the render chain.

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.

A comprehensive guide for conducting authorized database security assessments across various platforms (PostgreSQL, MySQL, MSSQL, Mongo, Redis). Covers critical areas including exposure analysis, authentication, authorization checks, misconfiguration review, and attack chain validation, ensuring non-destructive testing practices are followed.

This skill de-identifies sensitive PII from clinical notes across numerous languages, including Spanish, German, French, and Arabic. It automatically selects language-specific PII models, national ID regex patterns, and generates locale-aware fake surrogates. Designed for global healthcare datasets, it runs entirely on-device, ensuring maximum privacy and linguistic accuracy for diverse international clinical records.

A specialized tool designed to detect, suggest, and evaluate Gang of Four (GoF) design patterns within TypeScript and JavaScript codebases. It analyzes code structure, identifies code smells, and provides stack-aware refactoring recommendations, supporting frameworks like React, Angular, NestJS, and Vue.

This expert, interactive assistant provides comprehensive troubleshooting for complex issues encountered with Claude Code. It systematically scans the user's environment, checks global and project configurations, and cross-references symptoms against a deep knowledge base to pinpoint root causes and provide actionable, step-by-step solutions. Ideal for resolving integration errors, permission issues, or unexpected behavior.