investigate-dependencies
Conduct thorough dependency audits to identify redundant code, unused features, and improper usage patterns. Ensures project modularity by leveraging existing dependencies instead of reinventing functionality.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
269 skills found
Conduct thorough dependency audits to identify redundant code, unused features, and improper usage patterns. Ensures project modularity by leveraging existing dependencies instead of reinventing functionality.
A modular Rust-based fuzzing library for creating custom fuzzers, advanced mutation strategies, and research-grade vulnerability testing.
Architectural planning and scaling for spectre-build, covering GUI, server layers, multi-model support, and industrial pipeline orchestration.
Test-driven development (TDD) workflow for Spring Boot applications using JUnit 5, Mockito, MockMvc, and Testcontainers.
Upstash Vector DB setup, semantic search, namespaces, and embedding models. Ideal for building high-performance vector search features in Next.js 16/Vercel projects.
React and Vite performance optimization guidelines. Use when writing, reviewing, or optimizing React components built with Vite.
Comprehensive UI testing, visual fidelity analysis, and browser debugging using Chrome DevTools MCP and AI-driven vision models.
Evaluate Deca agent prompts and behavioral consistency through automated test runners, manual LLM judgment, and structured reporting.
Development guide for lemline-core, the stateless Serverless Workflow engine. Manage workflow execution, node navigation, state transitions, JQ expression evaluation, error handling, and parallel fork logic.
Expert-level guidance for ffuf web fuzzing, enabling automated discovery of hidden directories, files, parameters, and vulnerabilities during penetration testing.
AI-driven web testability assessment using 10 core principles. Evaluates observability, controllability, and stability via Playwright and Vibium to identify testing bottlenecks and improve quality readiness.
A meta-skill for building robust AI agent skills using a TDD approach: define failure (RED), implement the skill (GREEN), and plug rationalization loopholes (REFACTOR).