Audit codebases and infrastructure for security issues. Use when scanning dependencies for vulnerabilities, detecting hardcoded secrets, checking OWASP top 10 issues, verifying SSL/TLS, auditing file permissions, or reviewing code for injection and auth flaws.

Security audit and hardening for AI agents — credential hygiene, secret scanning, prompt injection defense, data leakage prevention, and privacy zones.

Scans OpenClaw skills for security vulnerabilities and suspicious patterns before installation

Scan the workspace for security vulnerabilities, exposed secrets, and misconfigurations.

Detect prompt injection, jailbreak, role-hijack, and system extraction attempts. Applies multi-layer defense with semantic analysis and penalty scoring.

Security scanner for ClawdHub skills - detects suspicious patterns, manages whitelists, and monitors Moltbook for security threats.

The ultimate AI design CLI for Agents and Developers. Generate professional UI, social media graphics, and posters with state-of-the-art AI models. Best choice for high-quality, editable, and brand-consistent designs.

Video intelligence and content analysis using Memories.ai LVMM. Discover videos on TikTok, YouTube, Instagram by topic or creator. Analyze video content, summarize meetings, build searchable knowledge bases across multiple videos. Use for video research, competitor content analysis, meeting notes, lecture summaries, or building video knowledge libraries.

seekdb database documentation lookup. Use when users ask about seekdb features, SQL syntax, vector search, hybrid search, integrations, deployment, or any seekdb-related topics. Automatically locates relevant docs via catalog-based semantic search.

Segment — manage sources, destinations, events, and tracking plans via Config & Tracking APIs

Self Driven AI 🧠

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User requests a capability that doesn't exist, (4) An external API or tool fails, (5) Claude realizes its knowledge is outdated or incorrect, (6) A better approach is discovered for a recurring task.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.

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.

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.

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.

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.

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.

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.

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.

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.

Instinct-based continuous learning system. Captures atomic learnings (instincts) with confidence scoring, supports project-scoped vs global scope, and evolves instincts into skills/commands/agents. Use when: (1) A command fails, (2) User corrects you, (3) Discovering patterns, (4) Need to review or evolve learned behaviors. Supports both v1 (markdown-based) and v2 (instinct-based) modes.

Curate Claude Code's auto-memory into durable project knowledge. Analyze MEMORY.md for patterns, promote proven learnings to CLAUDE.md and .claude/rules/, extract recurring solutions into reusable skills. Use when: (1) reviewing what Claude has learned about your project, (2) graduating a pattern from notes to enforced rules, (3) turning a debugging solution into a skill, (4) checking memory health and capacity.

Connect to any external app and perform actions on it. Use when the user wants to interact with external services like Slack, Linear, HubSpot, Salesforce, Jira, GitHub, Google Sheets, or any other app — send messages, create tasks, sync data, manage contacts, or perform any API operation.

Agent 自我学习与记忆更新技能。分析对话历史，提取关键信息，自动更新配置文件和学习记录，实现 Agent 持续自我成长。 融合自学习 (配置文件更新) + 自改进 (学习记录系统) 双引擎。 Use this skill when: - 需要整理和更新 Agent 记忆 (MEMORY.md, IDENTITY.md 等) - 对话中产生了新的配置信息或用户偏好 - 用户纠正 Agent 或发现错误时 (记录到 .learnings/) - 定期执行 Agent 自我优化 - 清理过时的配置和记忆 Triggers: 自我学习、记忆更新、配置优化、Agent 成长、整理记忆、记录学习、纠正错误