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Found 771 Skills
Agent skill for sona-learning-optimizer - invoke with $agent-sona-learning-optimizer
Multi-agent systems with LangGraph - supervisor/swarm/handoff/router patterns, state coordination, Deep Agents, guardrails, testing, observability, deployment. Use when building multi-agent workflows, coordinating agents, or need cost-optimized orchestration. Uses Claude, DeepSeek, Gemini (no OpenAI).
This skill automatically generates a comprehensive glossary of terms from a learning graph's concept list, ensuring each definition is precise, concise, distinct, non-circular, and free of business rules. Use this skill when creating a glossary for an intelligent textbook after the learning graph concept list has been finalized.
A validation framework that ensures Claude's responses are current, accurate, complete, and clear. Use this skill whenever the user asks a factual or research question, requests analysis or recommendations (e.g., "What's the best framework for X?", "Compare options for Y"), or any prompt where recency and accuracy matter. Also trigger when the user explicitly asks for validated, verified, or fact-checked answers. This skill should activate broadly — if the answer depends on facts that could have changed in the last few months, use it. Even questions that seem straightforward ("Is X still the recommended approach?") benefit from this skill's validation pipeline. Do NOT trigger for purely creative writing, casual chat, or tasks that are entirely opinion-based with no factual claims.
Human-led curation of accumulated metis and guardrails. Surface patterns across sessions, propose what to promote, compact, or dismiss. Use after multiple sessions, before a new phase, or when search results feel noisy.
Use when the user needs prompt design, optimization, few-shot examples, chain-of-thought patterns, structured output, evaluation metrics, or prompt versioning. Triggers: new prompt creation, prompt optimization, few-shot example design, structured output specification, A/B testing prompts, evaluation framework setup.
Use when generating or reasoning over text with Alibaba Cloud Model Studio Qwen flagship text models (`qwen3-max`, `qwen3.5-plus`, `qwen3.5-flash`, snapshots, and compatible open-source variants). Use when building chat, agent, tool-calling, or long-context text generation workflows on Model Studio.
Add a new tool to an existing FastMCP server with guided configuration
This skill should be used when the user asks to "optimize a DSPy program", "use MIPROv2", "tune instructions and demos", "get best DSPy performance", "run Bayesian optimization", mentions "state-of-the-art DSPy optimizer", "joint instruction tuning", or needs maximum performance from a DSPy program with substantial training data (200+ examples).
Chain-of-Verification (CoVe) prompting system. Converts lazy prompts into rigorous 4-stage verified output. Use for any code generation, debugging, or implementation task. Automatically invoked by wavybaby for medium/high complexity tasks. Reduces hallucinations and catches subtle bugs.
Parameter-efficient fine-tuning with Low-Rank Adaptation (LoRA). Use when fine-tuning large language models with limited GPU memory, creating task-specific adapters, or when you need to train multiple specialized models from a single base.
Creates system prompts, writes tool descriptions, and structures agent instructions for agentic systems. Use when the user asks to create, generate, or design prompts for AI agents, especially for tool-using agents, planning agents, or autonomous systems. **PROACTIVE ACTIVATION**: Auto-invoke when designing prompts for agents, tools, or agentic workflows in AI projects. **DETECTION**: Check for agent/tool-related code, prompt files, or user mentions of "prompt", "agent", "LLM". **USE CASES**: Designing system prompts, tool descriptions, agent instructions, prompt optimization, reducing hallucinations.