Skill UI

This skill acts as a comprehensive map for developing clinical and biomedical NLP pipelines using OpenMed. OpenMed is a local-first Python library that performs named-entity recognition (NER), protected health information (PHI) de-identification, and FHIR export, all running fully on-device without cloud calls. Use this guide when starting a new clinical text project, needing to select the appropriate capability (e.g., zero-shot NER, auditing, or FHIR conversion), or requiring an entry point for the core OpenMed features.

A powerful post-deployment monitoring tool designed for continuous quality assurance in CI/CD pipelines. It captures a performance baseline before deployment and then continuously monitors live applications after deployment. It alerts on critical failures (e.g., 5xx errors), performance regressions, and unexpected changes, ensuring that new releases maintain production stability.

Automates the entire Continuous Integration (CI) workflow, crucial before opening a Pull Request (PR). It systematically runs local unit tests for multiple languages (Python, Node, Rust), performs type checking, pushes the current branch to the remote repository, and finally provides the direct URL and status check for the CI platform (GitHub Actions/GitLab). This single command replaces multiple manual steps.

This script automates the Git push process, ensuring safety checks (e.g., preventing direct pushes to main branches) and verifying uncommitted changes. Upon successful push, it dynamically generates and displays direct tracking links for CI pipelines on major platforms like GitLab and GitHub Actions, providing immediate status updates for development teams.

Quickly retrieve and display the current Continuous Integration/Continuous Deployment (CI/CD) pipeline status for the active branch or a specific Pull/Merge Request. This tool supports major Git platforms including GitLab CI and GitHub Actions, providing developers with an immediate snapshot of build and test results.

This tool provides a unified interface to run test suites for various programming stacks (Python, Node.js, Rust) within a CI/CD pipeline. It automatically detects the project's environment (by checking lock files or config) and executes the appropriate testing framework (e.g., pytest, vitest, cargo test), ensuring consistent code quality checks regardless of the underlying language. Ideal for pre-commit or CI/CD integration.

This utility guides users in creating standardized and descriptive commit messages for staged changes using the Conventional Commits specification. It enforces structure, defining types (feat, fix, chore, etc.), scopes, and detailed body/footer requirements, ensuring a clear and maintainable project history.

This skill specializes in analyzing built frontend artifacts, going beyond static source code. It reconstructs the dynamic JavaScript structure, tracks chunk loading paths, and interprets source maps and build manifests to recover hidden routes, APIs, and runtime behaviors. Essential for deep security analysis and understanding execution flow from deployed bundles.

A specialized downstream skill for complex CTF challenges, focusing on cryptographic analysis, steganography, and mobile system forensics. It guides the user through recovering complex data chains, such as decoding blobs, tracing cryptographic transforms (keys, IVs, nonces), inspecting hidden media payloads, and analyzing mobile trust boundaries (e.g., APK/IPA signing logic, local storage, SSL pinning). This skill is designed to be used only after a main sandbox orchestrator has established the operational context.

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.

This advanced skill specializes in analyzing complex mail-related abuse scenarios, including OAuth consent flows, forwarding rule exploitation, shared mailbox access, and transport rule manipulation. It is used in forensic investigations to trace message artifacts, identify persistence mechanisms, and prove privilege escalation or data exfiltration following a compromise.

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.