Confidence Check
Pre-implementation confidence assessment tool for developers. Ensures 90%+ readiness via duplicate checks, architecture compliance, official docs verification, and root cause analysis.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
169 skills found
Pre-implementation confidence assessment tool for developers. Ensures 90%+ readiness via duplicate checks, architecture compliance, official docs verification, and root cause analysis.
Universal CLI tool to convert and synchronize AI agent skills between Claude Code and Gemini CLI extensions.
Diagnose, isolate, and mitigate LLM context failures like lost-in-middle, poisoning, distraction, and context clash to improve agent reliability.
Orchestrates multi-agent iterative refinement for high-quality OpenClaw skill development, ensuring rigorous testing and lifecycle management.
Holistic, multi-dimensional code review skill providing prioritized, actionable feedback on correctness, security, performance, design, and accessibility.
A professional code quality suite for software engineers, implementing SOLID principles, design patterns, refactoring techniques, and technical debt management to ensure clean, maintainable, and production-ready code.
Execute the implementation planning workflow, generate technical design artifacts, and structure research tasks for Spec Kit projects.
Guides agent memory system implementation, compares frameworks (Mem0, Zep, Letta, LangMem, Cognee), and designs persistence architectures for cross-session knowledge retention.
Validates Skill, Agent, and Command syntax using validate_skills.py, logs errors, and manages the automated QC workflow for agent development.
Implementation patterns for MERIDIAN autonomous AI agents using Claude API, including BaseAgent lifecycle, structured tool use, token budget enforcement, and cron scheduling.
Complete project architecture and structure guide for LobeHub. Use for codebase exploration, project organization, file location, and architectural context.
Automated quality gate using 5 parallel AI agents to review code changes for correctness, style, and consistency.