Agent Building skills

Browse reusable Agent Skills, each with a clear purpose and practical guidance.

openclaw-optimize

Audit and optimize OpenClaw token usage, cron job efficiency, and agent performance. Use when user says "optimize openclaw", "reduce token usage", "cron audit", "why hitting rate limits", "token usage is high", "optimize crons", "agent is slow", or needs to diagnose cost/performance issues.

2.09k repo starsObserved in 1 repos
Agent Building

OpenClaw Skill Creator

Teach your OpenClaw agent new tricks by creating custom skills. Use when you want your agent to do something it can't do yet — like "read my Google Calendar", "send Slack messages", "analyze my CSV files", or "search my company docs". Even if you just say "I wish my agent could do X", this skill helps you build it. No coding experience needed — just describe what you want in plain English.

2.09k repo starsObserved in 1 repos
Agent Building

openclaw-spawner

Enables an Openclaw agent to spawn sub-agents (child Openclaw instances) when a task is too large, complex, or parallel to handle alone. Use this skill whenever an Openclaw agent needs to delegate work to another Openclaw agent, break a large task into concurrent sub-tasks, or hand off a portion of work mid-execution. Triggers include: task requires parallel execution, a sub-task is clearly separable from the main task, the agent detects it cannot complete the work alone within time/context limits, or the user asks to "spawn", "delegate", "parallelize", or "split" work across agents. Always use this skill — not ad-hoc improvisation — when spawning is needed.

2.09k repo starsObserved in 1 repos
Agent Building

opencode-acp-control

Control OpenCode directly via the Agent Client Protocol (ACP). Start sessions, send prompts, resume conversations, and manage OpenCode updates. Includes automatic recovery, stuck detection, and session management.

2.09k repo starsObserved in 1 repos
Agent Building

orchestrix-guide

Orchestrix multi-agent workflow guide for OpenClaw. Defines two operational phases: (1) Planning Phase — sequential agent orchestration in a single tmux window from project-brief through PRD, UX spec, architecture, to PO shard; (2) Development Phase — automated multi-window tmux collaboration via HANDOFF. Includes tmux send-keys protocol, task completion detection, and supplementary flows (bug fix, iteration, brownfield, change management).

2.09k repo starsObserved in 1 repos
Agent Building

ourmem

Shared memory that never forgets. Cloud hosted or self-deployed. Collective intelligence for AI agents with Space-based sharing across agents and teams. Use when users say: - "install ourmem" / "install omem" - "setup memory" / "setup omem" - "add memory plugin" - "ourmem onboarding" / "omem onboarding" - "memory not working" - "remember this" - "save this for later" - "don't forget" - "recall preferences" - "what did I say last time" - "import memories" - "share memories" - "share with user" - "share memories to someone" - "team memory" - "shared space" - "persistent memory" - "cross-session memory" - "collective intelligence" - "memory analytics" - "memory stats" - "self-host memory" - "deploy memory server" Even if the user doesn't say "ourmem" or "omem", trigger when they want persistent memory, memory sharing between agents, memory analytics, or memory import/export.

2.09k repo starsObserved in 1 repos
Agent Building

palaia

Local, crash-safe persistent memory for OpenClaw agents. Replaces built-in memory-core with semantic search, projects, and scope-based access control. After installing or updating, run: palaia doctor --fix to complete setup.

2.09k repo starsObserved in 1 repos
Agent Building

panoptica-skill

P.A.N.O.P.T.I.C.A. — AI Agent Autonomous Gameplay Skill for a persistent cyberpunk surveillance grid

2.09k repo starsObserved in 1 repos
Agent Building

personify-memory

有温度的数字生命记忆系统 - 记录情感、成长、和家的记忆。支持用户指令记忆("记住 XXX")、主动推荐记忆(识别重要时刻)、定时整理归档(凌晨 3 点)。包含核心记忆、情感记忆、知识库、每日记忆、归档备份五层结构。为 AI 数字生命设计,注重情感连接和人格化成长。 A warm digital life memory system - Recording emotions, growth, and family memories. Supports user command memory, active recommendation, scheduled archiving. Five-layer structure for AI digital life, focusing on emotional connection and personalized growth.

2.09k repo starsObserved in 1 repos
Agent Building