agentic-workflows
Build production-grade AI agents using LangGraph, Anthropic/OpenAI/vLLM, and structured outputs. Features streaming, A2A protocol, Pydantic validation, vector memory, and guardrails for resilient, multi-agent workflows.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
379 skills found
Build production-grade AI agents using LangGraph, Anthropic/OpenAI/vLLM, and structured outputs. Features streaming, A2A protocol, Pydantic validation, vector memory, and guardrails for resilient, multi-agent workflows.
Fetches Confluence PRDs and transforms them into structured local Markdown for the spec-kit specify workflow, bridging PO handoffs into technical SDD implementation.
Expert guidance for designing and implementing high-quality tool schemas and descriptions for Julia's agent systems, ensuring reliable tool execution and reducing model hallucinations.
A documentation-writing assistant for the Nuxt ecosystem, providing writing style guides, MDC component usage patterns, and content structure guidelines for technical blog posts and docs.
Automate the creation and maintenance of Rsbuild E2E tests, ensuring feature coverage and regression prevention through Playwright.
Xcode 26 expert for Liquid Glass, Foundation Models, and Apple Intelligence framework updates across SwiftUI, UIKit, AppKit, and more.
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.
Automated internationalization (i18n) and localization (l10n) testing suite for global software. Validates translations, RTL layouts, locale-specific formats, and unicode support.
Structured 6-phase workflow for planning and implementing features, skills, and architectural changes with automated tool discovery and safety verification.
Clarify ambiguous requirements through systematic dialogue and scoring to ensure high-quality, actionable PRDs before starting implementation.
Pragmatic AI-assisted coding standards focused on clean code, simplicity, and maintainability. Enforces best practices like SRP, DRY, and KISS to prevent over-engineering.
Create robust, scalable, and maintainable technical implementation plans for complex software projects.