发现最适合你需求的 AI 技能
Operate CoinAPI market data reads through UXC with a curated OpenAPI schema, API-key auth, and read-first guardrails.
Submit a leave request through Feishu (Lark). Use when the user wants to request time off, submit a leave application, or mentions taking leave.
|
Dynamically select the best AI model for a task based on complexity, cost, and availability in GitHub Copilot. Use when deciding between free/paid models, or when you want automatic model routing based on query analysis.
Book massage services through Lokuli MCP. Use when user needs to find and book massage. Triggers on requests like "book a massage", "find massage near me", or any massage service request.
Universal AI memory infrastructure that stores, understands, and learns from past interactions. Works across ChatGPT, Claude, Gemini, DeepSeek, and any AI model. Provides cross-app persistent memory via simple API. Use when setting up long-term memory for agents, enabling context persistence across sessions, or when users want their AI to remember preferences, decisions, and history. Triggers on "cognimemo", "persistent memory", "cross-app memory", "ai memory", "remember across sessions".
MUST use for any multi-step project, long-running task, or infinite monitoring workflow. Plan, execute, track, and verify tasks with checkpoint validation. For projects, automation, and ongoing operations.
Avoid common LangChain mistakes — LCEL gotchas, memory persistence, RAG chunking, and output parser traps.
Verify trading reasoning with cognitive diagnostics before executing trades. Detects logical fallacies, calibration issues, and cognitive biases in your trade thesis.
Track intermittent fasting windows, extended fasts, and autophagy milestones
Detect systematic inference-level biases in an AI agent's reasoning via Cerebratech CogDx API ($0.10 per call, credits accepted). Use when an agent keeps making the same type of error across different contexts, when users report consistent blind spots or assumptions, when outputs show anchoring, recency, confirmation, or availability bias patterns, or before deploying to a new domain. Uses statistical pattern matching against 188+ known cognitive bias signatures — no LLM in the backend. Triggers
Book cleaning services through Lokuli MCP. Use when user needs to find and book cleaning. Triggers on requests like "book a cleaning", "find cleaning near me", or any cleaning service request.