Skill UI

This skill provides a comprehensive guide to deploying a Software-Defined Perimeter (SDP) using the CSA v2.0 specification. It implements core zero trust principles by establishing a dynamic, identity-centric network boundary. The deployment covers Single Packet Authorization (SPA) and mutual TLS (mTLS) to ensure that resources are invisible and inaccessible until a user is fully authenticated and authorized.

This tool detects, inventories, and analyzes undocumented or abandoned API endpoints (Shadow APIs). By comparing live network traffic logs against official OpenAPI specifications, it helps security teams identify hidden attack vectors, gaps in API governance, and unmonitored entry points, significantly improving the security posture of complex systems.

This guide details how to implement robust API schema validation using OpenAPI Specification (OAS) and JSON Schema. It enforces strict input/output contracts, preventing critical vulnerabilities such as injection attacks (SQLi, XSS), data leakage, and mass assignment by validating data types and structure at the API gateway or development level.

This guide details how to implement comprehensive API security testing using the 42Crunch platform. It performs static audits of OpenAPI specifications (API Audit) and dynamic vulnerability scanning (Conformance Scan) against live APIs. Supports integration into CI/CD pipelines to proactively discover OWASP API Top 10 vulnerabilities, enabling a Shift-Left security approach.

This guide details how to implement Kubernetes Pod Security Standards (PSS) using the Pod Security Admission (PSA) controller. PSS defines three mandatory security levels—Privileged, Baseline, and Restricted—for container workloads. It is essential for enhancing security posture, ensuring compliance, and migrating away from deprecated PodSecurityPolicy (PSP) controls by applying namespace labels and defining compliant pod specifications.

Use RESTler to automate stateful security testing of REST APIs. It processes OpenAPI specifications to generate fuzzing grammars, allowing users to discover complex bugs, such as injection vulnerabilities, resource leaks, and unhandled exceptions (500 errors), by executing diverse sequences of API calls. Essential for robust CI/CD regression testing and proactive API security assessments.

An autonomous factory for generating production-ready, cross-platform AI agent skills. It accepts raw, unstructured human input—such as transcripts, PDFs, screenshots, vague ideas, or code snippets—and reverse-engineers the complete workflow logic. It bridges the gap between human intent and functional agent specifications, allowing users to automate complex processes without writing code.

This guide enforces the 'spec-first' principle in software development, treating the specification as a non-negotiable contract. It outlines a rigorous, multi-stage workflow detailing mandatory sections (Functional/Non-Functional Requirements, Acceptance Criteria, API Contracts, Data Models) and bounded autonomy rules. Users learn how to define the system 'must do' before writing a single line of code, thereby minimizing rework and eliminating scope creep.

This tool assesses whether coding agents adhere to defined skills, rules, or agent definitions. It automatically generates scenarios with varying prompt strictness, executes the agent, and generates a comprehensive report detailing the compliance rate of tool calls against predefined workflow specifications using advanced LLM classification.

A comprehensive multi-agent feedback loop inspired by Generative Adversarial Networks (GANs), designed to build complex, production-ready applications. It separates generation from evaluation, using a 'ruthlessly strict' evaluator (QA) to drive continuous iteration. This process ensures high design quality, robust functionality, and originality, overcoming the limitations of single-agent self-critique. Ideal for full-stack feature development and complex product specification implementation.

This skill provides a comprehensive workflow to transform raw data into professional visual charts. It intelligently analyzes data features (e.g., trends, comparisons, flows) to select the optimal chart type (line, bar, pie, etc.). Users provide data and specifications, and the skill generates a high-quality, detailed chart image using a structured JavaScript process.

A structured methodology for initiating complex software projects or features. Instead of writing code immediately, this process mandates creating a detailed, shared specification (Spec) first. It guides users through four phases (Specify, Plan, Tasks, Implement) to clarify ambiguous requirements, define system boundaries, and establish measurable success criteria before any implementation begins.