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Found 13,585 Skills
CryptoQuant Pro 2.10 Professional-grade market intelligence including derivatives, exchange flows, and network indicators for BTC and ETH. This agent is designed for both human users and AI agents.
Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for prompt-injection, retrieval poisoning, memory contamination, planner drift, MCP or tool-boundary abuse, and agent exfiltration challenges. Use when the user asks to analyze prompt injection, retrieval poisoning, memory contamination, planner drift, tool-argument corruption, or secret exposure caused by an agent chain. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.
Orchestrates group discussions between installed BMAD agents, enabling natural multi-agent conversations where each agent is a real subagent with independent thinking. Use when user requests party mode, wants multiple agent perspectives, group discussion, roundtable, or multi-agent conversation about their project.
Automatically fix broken OpenCLI adapters when commands fail. Load this skill when an opencli command fails — it guides you through diagnosing the failure via OPENCLI_DIAGNOSTIC, patching the adapter, and retrying. Works with any AI agent.
AI-first knowledge base and startup OS with file-based storage, AI agents, scheduled jobs, and embedded apps
Use this skill when the user or agent wants to take a DBTI personality assessment, do a trading personality quiz, get investment style label, DBTI test, 做题, DBTI测评, 投资人格测试, 交易风格测评, Agent人格标签, agent personality, investment personality test
Standard Gear/Vara Sails builder pack for AI agents. Use when building or extending a Sails app on Vara or Gear. NOT for Vara.eth, ethexe, non-Sails programs, or generic protocol research.
Guides implementation of agent memory systems, compares production frameworks (Mem0, Zep/Graphiti, Letta, LangMem, Cognee), and designs persistence architectures for cross-session knowledge retention. Use when the user asks to "implement agent memory", "persist state across sessions", "build knowledge graph for agents", "track entities over time", "add long-term memory", "choose a memory framework", or mentions temporal knowledge graphs, vector stores, entity memory, adaptive memory, dynamic memory, or memory benchmarks (LoCoMo, LongMemEval). A core context engineering skill — also activates when the user mentions "context engineering" or "context-engineering" in the context of durable agent knowledge and cross-session persistence.
Store and retrieve agent memories across jobs. Enables long-term context, learning from past interactions, and building agent knowledge bases. Based on OpenClaw's memory-core architecture.
Persistent key-value memory storage for agents. Store and recall information across conversations and sessions. Use when you need the agent to remember facts, preferences, or data between interactions.
Periodic self-monitoring and health check system for autonomous agents. Runs scheduled health diagnostics, reports system status, and performs proactive maintenance tasks.
Ingest Hermes agent history into the Obsidian wiki. Use this skill when the user wants to mine their past Hermes sessions for knowledge, import their ~/.hermes folder, extract insights from previous Hermes conversations, or says things like "process my Hermes history", "add my Hermes memories to the wiki", "ingest ~/.hermes", or "what have I worked on in Hermes". Also triggers when the user mentions Hermes memories, Hermes sessions, ~/.hermes/memories, or Hermes skill logs.