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Found 162 Skills
Use when a developer asks their coding agent to initialize or work with moldea; plan an AI- or agent-enabled system and decide what should be agents versus deterministic software, services, tools, or human control; create or refine an AI agent or its behavioral system, including instructions, descriptions, handoff descriptions, tools, skills, schemas, variables and providers, routing or handoffs, bindings, or runtime integration; evaluate, reconcile, or validate an existing moldea system; or make ordinary behavior-affecting repository changes that may require maintaining an adopted moldea system. Loading the skill does not adopt moldea: initial adoption still requires explicit developer intent, while relevance-triggered maintenance applies once a repository uses or is adopting moldea.
Review a pull request or a set of code changes for bugs, logic errors, and project-convention violations using a confidence-filtered, multi-agent process. Use this skill when the user asks to review a PR, audit pending changes, or inspect a diff for problems before merging.
在新机器或新项目上落地「高智商领导 + 便宜执行」分层子代理：Codex Sol 领导 + Luna 工人， 可选 Claude Code 项目级 agents 与 Pi/pi-flow 跨工具编排。用于： (1) 从零安装并配置 Codex / Claude Code / Pi (2) 写入项目级 .codex/agents、AGENTS.md、.claude/agents (3) 修复 Sol 无法 spawn Luna 的 multi-agent catalog 问题 (4) 跑 Sol/Luna/多代理冒烟验证 触发：新机器设置、Sol-Luna、分层子代理、multi-agent 配置、codex agents 初始化
Multi-perspective in-depth analysis. Use multiple Sub-agents to act as consultants with different thinking frameworks, conduct independent analysis on the same material, then cross-summarize consensus and differences, and produce a structured diagnostic report. Triggered when the user says "Help me with multi-perspective analysis", "Multi-dimensional analysis", "Look at it from multiple perspectives", or "Help me diagnose it".
Understand the components, mechanics, and constraints of context in agent systems. Use when writing, editing, or optimizing commands, skills, or sub-agents prompts.
The canonical way to run agent-relay - self-bootstrap the local broker and autonomously spawn, monitor, and coordinate a team of worker agents without human intervention. Covers infrastructure startup, agent spawning, lifecycle monitoring, message-based reading via the relay MCP, and team coordination.