조사, 논문, 교육, 자격증 공부 (4.5천건)
Converting technical knowledge into durable learning documents and publishable articles. Use for diff-based teaching, decision records, onboarding, note/Zenn/Qiita/dev.to posts, article series, retrospectives, and cross-platform repurposing.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Triggers when researching competitive or professional positioning: market intelligence, engineer brands, profiles, and content strategy. Research and strategy only — not code.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Simulating users to evaluate existing flows and generate synthetic demand: cognitive walkthroughs, feature requests, unmet needs, JTBD, and opportunity trees. Not real-user research.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Multi-source research with citations using You.com. Use for questions that need several sources compared and synthesized, such as library or framework comparisons, tool and vendor evaluations, market research, or deep-dive reports. Routes between a cost-conscious agentic search loop and the one-shot `you-research` MCP tool.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Plan how to build with You.com. Use when adding web search, content extraction, or research to an app or agent: finds the right You.com API, MCP server, SDK, or docs path (for example Vercel AI SDK, LangChain, Python SDK, or REST) through the `you-discover` tool and Docs MCP.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through experience.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Train one of AgentDB's 9 RL algorithms on a stream of episodes. Use when the user has accumulated successful/failed episodes and wants to derive a policy, or when a task type is repeated enough to benefit from RL routing.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Show AgentDB health — pattern count, embedder status, cache hit rate, learning gain since init. Use when the user asks "is agentdb working?", "how many memories?", "show agentdb stats", or after long-running sessions to confirm state.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Implement persistent memory patterns for AI agents using AgentDB. Includes session memory, long-term storage, pattern learning, and context management. Use when building stateful agents, chat systems, or intelligent assistants.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Close the learning loop — record reward signal for an action AgentDB suggested. Use after using anything from agentdb_pattern_search / reflexion_recall / skill_search / learning_route. The bandit needs the signal to improve.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Implement adaptive learning with ReasoningBank for pattern recognition, strategy optimization, and continuous improvement. Use when building self-learning agents, optimizing workflows, or implementing meta-cognitive systems.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Implement ReasoningBank adaptive learning with AgentDB's 150x faster vector database. Includes trajectory tracking, verdict judgment, memory distillation, and pattern recognition. Use when building self-learning agents, optimizing decision-making, or implementing experience replay systems.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Map a scoped topic across three coexisting horizons — current system under strain (H1), preferred future (H3), and transition innovations sorted as H2+ or H2- — to understand change dynamics and identify responsible next actions.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Review the week using accumulated session evidence — retrieval rates, hint depths, calibration accuracy, transfer and unassisted results. The learner identifies patterns and sets a strategy goal. Use weekly or after a multi-session period.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Select evidence-based study strategies matched to material type, learning goal, and student habits. Use when advising students on revision techniques, homework, or independent study approaches.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
After scaffolded practice, run an unassisted check — a problem with no AI help. Separates what the learner can do with support from what they can do independently. Critical for preventing phantom attainment.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Tier vocabulary from a text or topic into everyday, academic, and technical categories with teaching priorities. Use when pre-teaching vocabulary or identifying language barriers in a text.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Map evidence-based connections between a wellbeing initiative and specific academic learning outcomes. Use when justifying wellbeing programmes, integrating SEL, or linking pastoral and academic work.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Modify a lesson plan using SIOP sheltered instruction principles to support language learners across all four skills. Use when planning lessons for classes that include EAL students.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Define the scope and purpose of a complex inquiry before mapping or futures work begins. Use when a class or group needs to agree what they are investigating, who it matters to, and at what scale.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Before any explanation or answer, require the learner to produce a free-recall attempt and confidence rating. Use when a student wants help understanding or reviewing a topic — this skill ensures the AI works from what the learner already knows.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Wrap a learning session in a plan → monitor → reflect cycle. Use at the start of any substantial study session to set goals, mid-session to check strategy, and at session end to consolidate what changed. Builds self-regulated learning as a habit.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Anchor curriculum learning in a specific local place with connections to community, culture, and identity. Use when connecting academic content to students' local environment and heritage.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
When a learner gets something wrong or feels stuck, require them to diagnose the problem before receiving help. Ensures help targets the actual cognitive breakdown, not just the surface error.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.