quality-metrics
Automate quality observability with DORA metrics, defect density tracking, and intelligent quality gate configuration for continuous delivery pipelines.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
129 skills found
Automate quality observability with DORA metrics, defect density tracking, and intelligent quality gate configuration for continuous delivery pipelines.
Persistent state management and workflow analytics using DuckDB for task dependency tracking, historical metrics, and context checkpointing.
Expert guidance for building production-ready Swift database client libraries, covering wire protocols, connection pooling, state machines, and NIO integration.
Manage project SSOT, memory, and cross-tool search. Guardian of decisions.md and patterns.md for Claude Code. Use for context retention, memory synchronization, and decision tracking.
Implementation patterns for MERIDIAN autonomous AI agents using Claude API, including BaseAgent lifecycle, structured tool use, token budget enforcement, and cron scheduling.
Streamline technical documentation for BattleScope features, maintaining consistency across API, frontend, and architecture layers.
Master professional state management in React Native using Redux Toolkit, Zustand, and TanStack Query, including data persistence with AsyncStorage.
Analyze product performance using KPI frameworks, cohort analysis, and funnel metrics to drive growth, retention, and feature adoption.
Real-time e-commerce price comparison and coupon hunting across major Chinese platforms like Taobao, JD, Pinduoduo, and more.
Automate your daily Milan news digest with this Python-based briefing tool. Supports weather, strikes, world/AI/Italian news, and event scraping, featuring deduplication, RSS/API pipeline management, and AI-agent ready scheduling.
Official n8n workflow automation support for building, debugging, and scaling complex business processes and AI-powered integrations.
Diagnose, isolate, and mitigate LLM context failures like lost-in-middle, poisoning, distraction, and context clash to improve agent reliability.