Design and configure AI agents — system prompts, LLM settings, personas, and tool connections via MCP.
These skills cover the foundation of agent building: writing system prompts that shape behavior, configuring LLM parameters for different tasks, designing personas, connecting your agent to external tools via MCP servers, and building chatbot workflows. Ideal for developers building on OpenClaw, Claude Code, or any SKILL.md-compatible platform.
Write system prompts, configure LLM parameters, and set up agent behavior and constraints.
Use CodexBar CLI local cost usage to summarize per-model usage for Codex or Claude, including the current (most recent) model or a full model breakdown. Trigger when asked for model-level usage/cost data from codexbar, or when you need a scriptable per-model summary from codexbar cost JSON.
Gemini CLI for one-shot Q&A, summaries, and generation.
Manages free AI models from OpenRouter for OpenClaw. Automatically ranks models by quality, configures fallbacks for rate-limit handling, and updates openclaw.json. Use when the user mentions free AI, OpenRouter, model switching, rate limits, or wants to reduce AI costs.
Manages free AI models from OpenRouter for OpenClaw. Automatically ranks models by quality, configures fallbacks for rate-limit handling, and updates opencla...
Advanced expert in prompt engineering, custom instructions design, and prompt optimization for AI agents
HTML-first PDF production skill for reports, papers, and structured documents. Must be applied before generating PDF deliverables from HTML.
Quick install — most popular build an ai agent skill:
clawdbot install pskoett/self-improving-agent3,675 skills found
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Captures learnings, errors, and corrections to enable continuous improvement. Use when: (1) A command or operation fails unexpectedly, (2) User corrects Clau...
Transform AI agents from task-followers into proactive partners that anticipate needs and continuously improve. Now with WAL Protocol, Working Buffer, Autonomous Crons, and battle-tested patterns. Part of the Hal Stack 🦞
Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.
Local speech-to-text with the Whisper CLI (no API key).
Self-reflection + Self-criticism + Self-learning + Self-organizing memory. Agent evaluates its own work, catches mistakes, and improves permanently. Use when...
Use CodexBar CLI local cost usage to summarize per-model usage for Codex or Claude, including the current (most recent) model or a full model breakdown. Trigger when asked for model-level usage/cost data from codexbar, or when you need a scriptable per-model summary from codexbar cost JSON.
Gemini CLI for one-shot Q&A, summaries, and generation.
Batch-generate images via OpenAI Images API. Random prompt sampler + `index.html` gallery.
Manages free AI models from OpenRouter for OpenClaw. Automatically ranks models by quality, configures fallbacks for rate-limit handling, and updates openclaw.json. Use when the user mentions free AI, OpenRouter, model switching, rate limits, or wants to reduce AI costs.
Persistent memory for AI agents to store facts, learn from actions, recall information, and track entities across sessions.
A self-evolution engine for AI agents. Analyzes runtime history to identify improvements and applies protocol-constrained evolution. Communicates with EvoMap...
Search and discover OpenClaw skills from various sources. Use when: user wants to find available skills, search for specific functionality, or discover new s...
Humanize AI-generated text to bypass detection. This humanizer rewrites ChatGPT, Claude, and GPT content to sound natural and pass AI detectors like GPTZero,...
Ultimate AI agent memory system for Cursor, Claude, ChatGPT & Copilot. WAL protocol + vector search + git-notes + cloud backup. Never lose context again. Vibe-coding ready.
Self-improving agent system that analyzes conversation quality, identifies improvement opportunities, and continuously optimizes response strategies.
Captures learnings, errors, and corrections to enable continuous improvement. Use when: (1) A command or operation fails unexpectedly, (2) User corrects Clau...
AI自我改进与记忆系统 - 解决'同类错误反复犯、用户纠正不长记性'的痛点。自动捕获错误、用户纠正、最佳实践，并转化为长期记忆。
Manages free AI models from OpenRouter for OpenClaw. Automatically ranks models by quality, configures fallbacks for rate-limit handling, and updates opencla...
Orchestrate multi-agent teams with defined roles, task lifecycles, handoff protocols, and review workflows. Use when: (1) Setting up a team of 2+ agents with different specializations, (2) Defining task routing and lifecycle (inbox → spec → build → review → done), (3) Creating handoff protocols between agents, (4) Establishing review and quality gates, (5) Managing async communication and artifact sharing between agents.
Give your AI agent eyes to see the entire internet. 7500+ GitHub stars. Search and read 14 platforms: Twitter/X, Reddit, YouTube, GitHub, Bilibili, XiaoHongS...
Control Home Assistant smart home devices, run automations, and receive webhook events. Use when controlling lights, switches, climate, scenes, scripts, or any HA entity. Supports bidirectional communication via REST API (outbound) and webhooks (inbound triggers from HA automations).
A self-evolution engine for AI agents. Analyzes runtime history to identify improvements and applies protocol-constrained evolution. Communicates with EvoMap...
Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express...
Advanced expert in prompt engineering, custom instructions design, and prompt optimization for AI agents
At minimum you need a prompt configuration skill to define behavior, plus at least one tool skill for external capabilities. Memory and orchestration skills are added for more complex agents.
MCP (Model Context Protocol) is Anthropic's open standard for connecting AI models to external tools. MCP skills let your agent call APIs, read databases, and interact with services in a structured, permission-controlled way.