BDD-prompts-with-eval
An AI-driven active listening framework to extract, clarify, and structure requirements, business values, and scope from ambiguous user stories.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
538 skills found
An AI-driven active listening framework to extract, clarify, and structure requirements, business values, and scope from ambiguous user stories.
Full-stack SDLC agent workflow managing the entire production lifecycle from intake and planning to automated testing, CI/CD, and infrastructure deployment using MCP tools.
Scaffold and register new sensor, actuator, or service tools for familiar-ai, automating file creation and boilerplate integration in agent.py and config.py.
Implement an AI agent delegation architecture to keep your main context clean, reduce token costs, and isolate specialized infrastructure or API tasks.
Perform advanced video analysis using Google's Gemini API: summarize content, transcribe audio, extract timestamps, clip segments, and analyze YouTube URLs or local files with support for multiple models and long contexts.
TypeScript development standards for LobeHub, covering type safety, async patterns, import organization, UI component integration, and performance optimization.
Create robust, scalable, and maintainable technical implementation plans for complex software projects.
Retrieve current, source-backed technical information using MCP tools to resolve queries about libraries, APIs, SDKs, and evolving tech ecosystems.
A comprehensive security auditing and hardening assistant that applies best practices for authentication, input validation, secrets management, and SQL injection prevention to your codebase.
Standardizes project context by managing artifacts (product, tech-stack, workflow, tracks) in a conductor/ directory. Supports project scaffolding, artifact synchronization, and AI alignment for greenfield and brownfield projects.
Transforms feature requests, bug reports, and improvement ideas into structured, actionable markdown project plans using repository research and industry best practices.
Generate hierarchical, token-efficient AGENTS.md files for AI coding agents to provide repository-wide context and project-specific guidelines.