Skill UI

gget is a versatile CLI and Python package designed for rapid, reproducible bioinformatics searches across major genomic reference databases (e.g., Ensembl, UniProt). It allows users to quickly query gene metadata, perform initial BLAST/BLAT style alignments, and explore associated pathways, cancer, or disease modules. It is ideal for initial data exploration and generating reproducible evidence logs before building complex, full-scale local pipelines.

Qiskit is a leading open-source quantum computing framework designed for building, optimizing, and executing quantum circuits. It provides comprehensive tools to run on local simulators or major cloud quantum backends, including IBM Quantum, IonQ, and Amazon Braket. Use it to develop algorithms in chemistry, machine learning, and optimization.

This skill serves as a deterministic internal downloader for image URLs extracted from comprehensive web search results. It receives normalized media slots and search output via stdin, utilizing Python HTTP APIs to download direct image links. The process includes validating MIME types and saving files accurately into the configured local project directory, ensuring reliable asset retrieval without relying on sandboxed shell tools.

Build a local multimedia webpage project from a user topic, audience, language, style, and media preferences by framing requirements, researching, planning, acquiring media, generating files, packaging, validating, repairing, and delivering usage guidance.

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.

This diagnostic skill audits the entire local setup of Claude Code against several known, complex cache and cost bugs (CC#40524, B4, B5). It checks critical components including version compatibility, sentinel placeholders, session resuming logic, and attribution headers. Use this tool to ensure your development environment is optimized, stable, and minimizes unexpected operational costs and functional regressions.

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.

A specialized skill for analyzing client-side persistence mechanisms, including cookies, localStorage, sessionStorage, IndexedDB, and Service Workers. It is crucial for security testing and CTF environments where application behavior or critical decision branches are determined by stored session state, cached data, or local client-side variables. Use this to trace the smallest stateful sequence leading to a decisive outcome.

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.

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.

This tool de-identifies sensitive free-text columns (e.g., names, dates, identifiers) in local structured datasets (CSV, JSONL, Parquet) using advanced OpenMed models. It ensures strict privacy by generating a completely redacted dataset and a separate PHI-free aggregate summary, allowing for secure data sharing and analysis without compromising source privacy or logging sensitive values.

A powerful, on-device tool for removing, masking, or replacing sensitive Protected Health Information (PHI/PII) from clinical free text. It ensures patient privacy by running fully locally, supporting methods like masking, hashing, and date shifting. Essential for preparing medical records for safe sharing, storage, or analysis, adhering to standards like HIPAA and GDPR.