artifact-tracking
AI-optimized artifact tracking system for token-efficient project orchestration, phase management, and automated task delegation using YAML-Markdown hybrid formats.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
185 skills found
AI-optimized artifact tracking system for token-efficient project orchestration, phase management, and automated task delegation using YAML-Markdown hybrid formats.
Automates the synchronization of new infographic templates by updating project documentation, gallery mappings, and AI playground prompts.
End-to-end GitHub repository maintenance agent. Automates triage, PR review, issue analysis, and maintenance reporting to ensure long-term repository health, stability, and growth.
Interactive tool for generating Business, Model, Architecture, and Design (BMAD) planning documentation for feature development.
Captures session learnings into Reusable Intelligence Infrastructure (RII). Converts one-time bug fixes and pattern discoveries into permanent agent-executable knowledge to prevent recurrence and accelerate future development.
Sync Granola meeting transcripts to your local Knowledge folder, integrated into your morning planning workflow.
Generate diverse landing page narrative angles, define target audiences, and specify required evidence for conversion-focused marketing workflows.
A framework for collecting, analyzing, and prioritizing user feedback across multiple channels to drive product strategy and feature development.
Automated toolkit for creating, maintaining, and enhancing CLAUDE.md files to ensure your project's AI-assisted development guidelines are always accurate, modular, and best-practice compliant.
Package entire code repositories into single, AI-optimized files. Ideal for providing codebase context to LLMs like Claude, ChatGPT, and Gemini for analysis, security audits, and bug investigations.
Manage PR review workflows, resolve threads, and handle discussion comments using specialized erk exec commands.
Implements an autonomous, critical self-verification layer for AI agents to validate code quality, security, and requirement alignment before task completion.