Skill UI

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.

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.

A comprehensive white-box security auditing workflow designed for proprietary source code. It integrates static analysis security testing (SAST) tools like Semgrep and CodeQL to detect common vulnerabilities (e.g., injection, IDOR, crypto misuse), followed by mandatory manual threat modeling and verification steps. Applicable for PR reviews and pre-deployment security checks.

This tool provides a preferred, end-to-end method for modifying code in real-world repositories. It simulates a professional development workflow: cloning the target repository, running changes on a dedicated task branch, and critically, verifying the implementation through an independent red $\to$ green $\to$ regression test loop. It is designed for fixing GitHub issues, implementing new features, or adding functions to existing codebases, ensuring the structural integrity and correctness of the changes.

A specialized downstream skill for CTF-sandbox workflows. Used to analyze complex security challenges driven by AI agent interactions, prompt injection, or infrastructure vulnerabilities. Focuses on tracing control chains involving untrusted input, tool side effects, deployment drift, container runtime issues, and CI/CD supply chain provenance. Ideal for rigorous vulnerability assessment in modern, distributed systems.

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 skill for analyzing the discrepancy between static Kubernetes/Compose manifests and the actual live operational state of a container runtime. It traces complex dependencies, such as secrets consumption, sidecar/init container modifications, network routing, and mounted volume paths. Use this when the core challenge involves proving how the live execution path differs from the documented intent, forming a minimal, verifiable evidence chain.

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 analyzing and reproducing complex, timing-dependent bugs in concurrent systems. Use this to investigate race windows, ordering bugs, lock gaps, stale reads, or state inconsistencies where the final outcome depends critically on request timing or asynchronous execution order. Essential for deep security auditing and debugging of distributed transactions.

This advanced skill specializes in tracing the complete provenance of software artifacts across the entire development lifecycle. It is designed for deep security analysis of CI/CD pipelines, identifying dependency drift, build tampering, package origin, and determining the final artifact consumed at runtime. Use it when investigating integrity vulnerabilities in complex release flows.

This local developer tool inspects dependency manifests (requirements.txt, pyproject.toml, package.json) for surface-level issues like standard-library shadowing, unpinned dependencies, and conflicts. It provides plain-language explanations and suggested fixes, helping developers debug dependency rot before deeper installation attempts.

This skill deploys the OpenMed Model Context Protocol (MCP) server, exposing critical clinical NLP tools such as NER, PII extraction, and de-identification. It enables AI coding agents and chat clients to interact with OpenMed's capabilities via simple tool calls, running locally on-device to ensure user data privacy and security. Supports both stdio and Streamable HTTP deployment modes.