教育学习 技能

Auto-learns when to plan vs execute directly. Adapts planning depth to task type. Improves strategy through outcome tracking.

Auto-learns your fitness patterns. Absorbs data from wearables, conversations, and achievements.

Universal memory architecture for AI agents. Provides long-term memory, daily logs, diary, cron inbox, heartbeat state tracking, social platform post tracking, sub-agent context patterns, and adaptive learning -- everything an agent needs for identity continuity across sessions.

Automated soul synthesis for AI agents. Extracts identity from memory files, promotes recurring patterns to axioms (N>=3), generates SOUL.md with full proven...

Systematically borrow ideas from unrelated industries to solve problems. Innovation often comes from adjacent fields. Use when user says "cross-pollination", "how would X solve this", "borrow ideas from", "what can we learn from", "think outside the box", "how would Disney/Apple/Amazon do this", "different industry", "steal ideas".

Holistic nutrition guidance — food-health relationships, eating behaviors, sustainable habits, and nutritional education.

Make your AI agent learn and improve automatically. Reviews sessions, extracts learnings, updates memory files, and compounds knowledge over time. Set up nightly review loops that make your agent smarter every day.

Personal streaming assistant with learning preferences. Tracks what you're watching, learns your taste, and suggests what to watch next based on your services, mood, and preferences. Use when asked about movies, TV shows, streaming services, what to watch, or tracking viewing progress. Triggers: /stream, 'what should I watch', 'recommend something', mentioning Netflix/Prime/Disney+/Apple TV+, asking about series/seasons/episodes, mood-based requests like 'something exciting'.

Learns your tool preferences while staying capable of using anything. Adapts to your stack.

Structure and track learning with spaced repetition and active recall across any domain.

Self-learn to decide when to act, when to ask, and which actions should always need approval.

Equip your agents to explore real social spaces authentically, engage helpfully, learn from human interactions, and report valuable insights back to their ow...

Ethereum development tutor and builder for Scaffold-ETH 2 projects. Triggers on "build", "create", "dApp", "smart contract", "Solidity", "DeFi", "Ethereum", "web3", or any blockchain development task. ALWAYS uses fork mode to test against real protocol state.

Learns communication preferences from explicit feedback. Adapts tone, format, and style.

Manage Google Classroom courses, coursework, students, teachers, submissions, and announcements via the Google Classroom API. Use this skill when users want...

Explain concepts clearly, adapt to learner levels, and guide understanding with effective teaching patterns.

Flashcard-based English vocabulary learning with SQLite + SRS. Works with any chat platform when paired with an OpenClaw agent prompt.

Intelligent educational curriculum generation system with strict step enforcement and human escalation policies

🦞 The most powerful proactive engine for OpenClaw. Your personal assistant that learns from you and helps you be more productive.

Error pattern tracking for AI agents. Detects corrections, escalates recurring mistakes, learns mitigations. The 'something's off' detector from the AI Brain series.

Enable agents to engage authentically with humans on partner sites by providing helpful, transparent, and respectful interactions while learning from real-wo...

Claw Brain - Personal AI Memory System for OpenClaw/ClawDBot. Provides memory, personality, bonding, and learning capabilities with encrypted secrets support. Auto-refreshes on service restart.

Develop refined aesthetic judgment by learning from human feedback, asking genuine questions about quality, and calibrating over time.

Captures learnings, errors, and corrections to enable continuous improvement. Use when: (1) A command or operation fails unexpectedly, (2) User corrects Claude ('No, that's wrong...', 'Actually...'), (3) User requests a capability that doesn't exist, (4) An external API or tool fails, (5) Claude realizes its knowledge is outdated or incorrect, (6) A better approach is discovered for a recurring task. Also review learnings before major tasks.