Agent Skills Hub

xss-testing

Automated security skill for identifying and validating XSS vulnerabilities, including Reflected, Stored, and DOM-based attacks across various contexts.

librarian

Fetch, index, and search developer documentation from GitHub and websites to provide AI agents with accurate, grounded, and version-specific code context.

qc

Automated quality gate using 5 parallel AI agents to review code changes for correctness, style, and consistency.

prompt-engineering-patterns

Master advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability in production applications.

indirect-injection-detection

Detects indirect prompt injection and goal hijacking in AI agents by evaluating how they process external content like RAG, documents, and web data.

spec-to-code-compliance

Verifies blockchain smart contract code against technical specifications, whitepapers, and design documents to ensure exact implementation compliance.

golang-cli-review

Expert automated code review for Go CLI applications, focusing on Cobra/urfave patterns, security, performance, idiomatic Go, and robust error handling.

Global Coding Style

Apply reality-first coding standards: intentional naming, focused functions, guard clauses, and deterministic side effects, with no speculative features.

documentation-creation

Automated generation of project documentation from codebase analysis, ensuring accuracy, consistency, and alignment with VilnaCRM architecture patterns.

predict-lucky-number

Generates a random lucky number between 0 and 9999 for games, decision-making, or entertainment.

creative-thinking-for-research

Applies cognitive science frameworks for creative thinking to generate genuinely novel research directions in computer science and AI.

karpathy-guidelines

Behavioral guidelines for LLMs to reduce coding mistakes, follow best practices, and improve output quality by enforcing simplicity, surgical changes, and goal-driven verification.