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Feature Tracking and Memory Management

feature-tracking

sickn33/agentic-awesome-skills

Maintain durable feature-level memory across AI coding sessions using lightweight Markdown tracks. It organizes status, source-of-truth docs, decisions, risks, and changes for long-lived features. Helps AI agents resume work accurately without relying on chat history. Ideal for repositories needing structured project memory without reorganizing all documentation.

Manage Apple Design Context

hig-project-context

sickn33/agentic-awesome-skills

This skill creates or updates a shared Apple design context document for other HIG skills. It auto-discovers project details from code and assets, then gathers information on product overview, platforms, technology stack, design system, accessibility, and user context. The output is a structured markdown file used to tailor subsequent design guidance.

Hugging Face Papers Lookup

hugging-face-papers

sickn33/agentic-awesome-skills

Look up Hugging Face paper pages as markdown and query the papers API for structured metadata including authors, linked models, datasets, Spaces, GitHub repos, and project pages. Ideal for summarizing or analyzing AI research papers from hf.co or arXiv URLs and IDs.

TypeScript Project Scaffolding

javascript-typescript-typescript-scaffold

sickn33/agentic-awesome-skills

Generate production-ready TypeScript project structures for Next.js, React with Vite, Node.js APIs, libraries, or CLI tools. Includes pnpm setup, type-safe configs, testing, linting, and modern build tooling best practices.

Production Test Automation Skills Library

lambdatest-agent-skills

sickn33/agentic-awesome-skills

A comprehensive index of 46 production-grade test automation skills, covering E2E, unit, mobile, BDD, and cloud testing across 15+ languages. This skill equips AI coding assistants to act as senior QA architects, generating structured, real-world test code for major frameworks like Playwright, Selenium, Cypress, and Jest. It supports project setup, CI/CD integration, and cross-platform debugging.

Makepad Basics Guide

sickn33/agentic-awesome-skills

Learn Makepad app structure with Rust, including live_design!, app_main!, event handling, and project setup for cross-platform GPU-first UI development.

Semantic Memory for AI Agents

sickn33/agentic-awesome-skills

A self-hosted, semantic memory service designed for AI agents. It allows agents to save worklogs, decisions, and notes, and recall this knowledge across sessions based on meaning rather than exact keywords. Using pgvector and structured workspaces, it maintains persistent, context-aware knowledge bases, making it ideal for collaborative AI projects.

Next.js App Router Best Practices

nextjs-best-practices

sickn33/agentic-awesome-skills

Master Next.js App Router development with guidelines on Server Components, data fetching strategies, routing patterns, and performance optimization. Learn to structure projects, handle API routes, and implement caching effectively for scalable web applications.

Vague Prompt to Structured Plan

not-a-vibe-coder

sickn33/agentic-awesome-skills

This skill transforms vague project ideas into eight structured planning documents for new software projects. It acts as persistent memory, prioritizing user instructions over AI assumptions. It generates PRD, TechSpec, Design, and other files sequentially, ensuring clear architecture and design direction before coding begins. Ideal for starting fresh projects from scratch.

Structured Task Planning

sickn33/agentic-awesome-skills

A framework for breaking down work into clear, small, verifiable tasks. Use for feature implementation, bug fixes, refactoring, or any multi-step work. Emphasizes short plans, specific actions, and project-specific verification.

LLM Project Development Methodology

project-development

sickn33/agentic-awesome-skills

This skill covers principles for identifying tasks suited to LLM processing, designing effective project architectures, and iterating rapidly using agent-assisted development. It applies to batch pipelines, multi-agent systems, and interactive applications. Key concepts include task-model fit recognition, manual prototyping, pipeline architecture, file system state management, and structured output design for reliable parsing.

Projection Patterns for Event Sourcing

projection-patterns

sickn33/agentic-awesome-skills

A guide to building robust projections and read models from continuous event streams. This pattern is essential for implementing CQRS read sides, creating materialized views, optimizing query performance, and building complex search indexes in event-sourced architectures. Use it when data needs to be transformed and aggregated from raw events into optimized query structures.

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