acceptance-testing
Plan, implement, and execute user acceptance tests (UAT) and end-to-end scenarios to validate requirements against user-visible behavior.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
558 skills found
Plan, implement, and execute user acceptance tests (UAT) and end-to-end scenarios to validate requirements against user-visible behavior.
AI-driven GitHub project management using swarm coordination, automated issue triage, project board synchronization, and intelligent task decomposition for efficient development workflows.
Implement shadcn/ui components: installation, Vite/TanStack Router configuration, CLI command management, and Tailwind CSS integration.
A microworld operating system for LLM-based agent living memory, transforming filesystems into navigable rooms and code into habitable worlds.
Pre-execution security guardrails for AI agents. Validates shell commands and file reads against 400+ security patterns to block destructive operations, credential theft, and unauthorized system access.
Add evlog framework integration: automate wide-event logging across your stack with standardized middleware, build configurations, testing, and documentation.
Architect production-grade LLM applications using LangChain 1.x and LangGraph. Implement stateful AI agents, multi-step workflows, and custom memory systems for complex conversational and automation tasks.
Convert SRT subtitle files into structured Markdown notes with punctuation, paragraph formatting, and automated video screenshot placeholders.
Comprehensive UI testing, visual fidelity analysis, and browser debugging using Chrome DevTools MCP and AI-driven vision models.
Augmented cognition layer that connects conversations to a persistent knowledge tree, enabling long-term memory, recall, and contextual reasoning across projects.
Automatically organize your SpecStory AI coding session history into a structured YYYY/MM directory hierarchy to improve file management and archiving.
Multi-model LLM integration patterns for Claude, GPT, Gemini, and Ollama. Features API handling, prompt engineering, token management, and model-agnostic orchestration.