调研、论文、教育、考证学习（4728 个）
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.
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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.
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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.
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Pin & Paper — 黄色纸面 + 安全别针插图 + 墨蓝手写 Caveat + 纸纹理。任何应该感觉手作 / 温暖 / 文学的 deck：定性研究发现 / 创始人反思 / 长篇品牌故事 / workshop 复盘。
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A playful, joyful, two-color risograph print aesthetic built on a single warm off-white paper surface running through every section
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Paper-textured, print-inspired design with minimal colors, clean serif/sans typography, and tactile surface qualities.
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A friendly, hand-drawn sketch interface inspired by pencil illustrations on warm cream paper. Soft teal brand accents, hand-written display headings, rounded pill controls.
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A research-journal aesthetic printed on warm stone — authoritative, editorial, almost achromatic. Pages live on warm ivory parchment (never pure white), with near-black slate as the dominant ink.
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Pesquisa de Voz do Cliente (VOC) antes de escrever qualquer copy — coleta a linguagem literal do público em avaliações, fóruns, redes sociais, tickets de suporte e transcrições de vendas. Use quando o usuário disser "pesquisa de público", "voz do cliente", "VOC", "o que os clientes falam", "pesquisar concorrente", "analisar reviews", "levantar objeções", "não sei o que escrever", ou quando pedir copy sem que exista seção 6 preenchida em .claude/pwdev-copy-context.md. Produz frases verbatim, não paráfrases.
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Research topics thoroughly and write comprehensive, well-structured content including articles, documentation, blog posts, and technical writing with proper citations and sources. Use when writing blog posts, creating technical articles, researching topics, gathering sources, writing documentation, creating educational content, or producing research-backed content.
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Apply continuous improvement principles to iteratively enhance processes, code quality, team practices, and system performance through small, incremental changes. Use when improving development processes, optimizing workflows, reducing waste, enhancing code quality over time, implementing retrospective learnings, or fostering a culture of continuous improvement.
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Research competitors, analyze market positioning, identify differentiators, and understand competitive landscape to inform product strategy and positioning. Use when researching competitors, analyzing features, identifying market gaps, understanding pricing strategies, evaluating competitive advantages, researching market trends, or informing product decisions.
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Manage project learnings. Review, search, prune, and export what gstack has learned across sessions. Use when asked to "what have we learned", "show learnings", "prune stale learnings", or "export learnings". Proactively suggest when the user asks about past patterns or wonders "didn't we fix this before?"
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Creates professional PDF whitepapers from Markdown files. Use when the user wants to create a whitepaper, technical document, or PDF with professional formatting and typography.
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Orchestrate continual learning by delegating transcript mining and AGENTS.md updates to `agents-memory-updater`.
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Build a personalized learning roadmap with milestones and practice checkpoints
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Evaluate learning progress, identify blockers, and adjust the learning plan
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Multi-agent exploration and task delegation for complex areas of interest. Use when you need to deeply explore a codebase area, gather information from multiple perspectives, or delegate parallel research tasks for comprehensive analysis.
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Orchestrator for the learn-from suite - auto-detects source type (academic paper, GitHub repo, blog/web article, or in-conversation learnings) and routes to the correct sub-skill for credibility check, security scan, insight extraction, and application. Load when the user says "learn from", "learn from this", "extract insights from", "apply learnings from", "what can we learn from", or provides a URL, file path, or pasted content that should be ingested as knowledge. Single entry point for all learning workflows.
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Extract actionable skill knowledge from academic papers and research articles, assess credibility, run security checks, and either improve existing skills or create new ones. Load when the user asks to learn from a paper, extract insights from a research paper, turn a paper into a skill, apply paper findings to skills, read this paper and improve my skills, or process a research article. Also triggers on "skill from paper", "learn from this paper", "paper to skill", "extract from this research", "apply this paper", or when the user uploads or links to an academic PDF or paper URL.
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Promote project-specific memories into strict, small global memory only when they are cross-project, stable, useful, safe, and worth the global context cost. Load when the user says make this global, remember across projects, save this globally, or promote this learning.
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Extract actionable patterns, architecture decisions, code conventions, and skill-relevant insights from GitHub/GitLab repositories. Assess repo credibility, run the full security scan pipeline, and apply findings to existing skills, new skills, or the current project. Load when the user asks to learn from a repo, extract patterns from a codebase, study a repository, or analyze a repo for reusable techniques. Also triggers on "learn from this repo", "learn from this repository", "what can we learn from this codebase", "extract patterns from this repo", "study this repo".
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Research a skill domain before building or improving a skill. Searches academic papers, practitioner blogs, and GitHub skill repos in parallel to find current best practices, domain gotchas, and existing skill patterns. Called by universal-skill-creator and improve-skills before writing any skill. Also load directly when the user asks to research a domain for a skill, find existing skills on a topic, discover best practices for a skill, check what research exists before building an agent skill, or says "what does current research say about", "find best practices for".
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Capture actionable learnings that emerge during conversation — when the agent or user discovers that a skill, a set of skills, or a process needs to be updated based on what's happening in the current chat. Sub-skill of the learn-from orchestrator. Load when the user says "we should update the skill for this", "this should be a skill rule", "add this as a gotcha", "the skill should know about this", "update the process for this", "remember this for next time", "this is important for the skill". Also triggers when the agent notices a skill's guidance was wrong or incomplete, a process step failed or was unnecessary, a new pattern emerged, a guardrail was missing, a workaround became a pattern, or a debugging session reveals a gap.
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