Prompt engineering, RAG, context management, and agent memory.
Everything upstream of the model call: prompt engineering patterns, retrieval and RAG pipelines, context window management, and persistent memory across sessions. These artifacts decide what your agent knows when it starts working, which usually matters more than which model you picked. Includes context compaction, knowledge-base wiring, and memory that survives a restart.
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Analyze command history to identify which skills work, which fail, and where to improve.
Use when the workflow needs to self-correct, improve over time, or establish feedback loops and evaluation cycles.
Local RAG MCP Server - Easy-to-setup document search with minimal configuration
Use when the workflow works but needs to handle more complex cases or produce higher-quality output through better tools, context, prompts, or models.
Use when porting a workflow to a different AI provider, deployment environment, model tier, or organizational context.
CLI for AgentRecall memory system
Use when the workflow needs multi-step processing with sequential, parallel, or conditional tool compositions and proper data flow.
Use when starting a new project, adding a new agent to an existing system, or setting up workflow infrastructure from scratch.
Memory Palace MCP server for AI agents
Use when the user wants to create templates, extract reusable patterns, document solutions, or build a pattern library from working workflows.
Use when workflow components are inconsistent, naming conventions vary, or a new team member's work needs alignment to project standards.
How an agent should operate as one mind inside a shared Company Brain built on MemClaw — recall before acting, obey fleet keystones, reuse and publish skills, and report outcomes so every task compounds across the whole organization. Use this whenever you work as part of a MemClaw-connected team or fleet and your work should build on, and feed back into, what the organization already knows; it sets the operating posture. For the mechanics of individual memclaw_* tools, see the companion "memclaw" skill.
Use when the workflow feels too complex, has accumulated cruft, or has redundant steps and overlapping tools that need consolidation.
Use when the workflow works but needs polish, or as the final step in a diagnose → fix → refine cycle before shipping.
Local utility for Rosetta — manage plans, install agents, and support AI coding workflows via CLI or MCP
Use when the user wants to tailor a workflow for a specific industry, domain, or vertical with specialized expertise, terminology, and guardrails.
MCP server for Maestro — exposes 25 workflow skills as tools, prompts, and resources for any MCP-compatible AI client
MemClaw Core API service
Use when starting a new project with Maestro or when no .maestro.md context file exists yet. Run once per project.
Use when the user wants to find problems, audit workflow quality, or get a comprehensive health check on their AI workflow.
Universal MCP Server with advanced AI memory capabilities and semantic search.
Use when the workflow is too slow, too expensive, or both and needs latency, cost, or token usage optimization.
Use when the workflow feels over-engineered, has premature optimizations, unnecessary abstraction layers, or complexity beyond actual requirements.
MCP server to work with LogSeq via the local HTTP server
Quick summary of the last session — commands run, files changed, and what to do next.
TypeScript MCP wrapper for the IAI-MCP Python core
教学过程中自动捕获和记录学习者的概念疑难点（"为什么/是什么/怎么推/什么意思"类型的问题），保存到进度文件的"概念疑难点记录"区，形成考前回顾清单。
Last-night exam-cram coach as a Claude Agent Skill: turns your slides, notes and past papers into a chaptered knowledge base + quiz bank, t…
Standalone, local-first semantic code-search engine for large and custom codebases.
Last-night exam-cram coach as a Claude Agent Skill: turns your slides, notes and past papers into a chaptered knowledge base + quiz bank, t…
Last-night exam-cram coach as a Claude Agent Skill: turns your slides, notes and past papers into a chaptered knowledge base + quiz bank, t…
A vector-powered CLI for semantic search over files (Vexor skill bundle).
Last-night exam-cram coach as a Claude Agent Skill: turns your slides, notes and past papers into a chaptered knowledge base + quiz bank, t…
帮助学生在临考前进行结构化极速复习：解析课程资料/大纲/重点，按章节生成 wiki 知识库与标准题库，组织针对性刷题与判分，并记录复习进度和错题。当用户即将考试、需要快速复习计划、练习题、错题复盘或考前小抄时使用（关键词：期末/备考/复习/刷题/划重点/错题；exam, cram, study plan, quiz, review）。不适用于长期学习规划、与考试无关的写作或编程任务。
Apply Sociotechnical Systems Theory to analyze and design work systems through joint optimization of social and technical subsystems. Use this skill when the user needs to diagnose why a technology implementation disrupted work practices, design IT-enabled work systems that balance human and technical needs, or when they ask 'why did this system hurt productivity despite being technically sound', 'how do we design work around new technology', or 'why are people resisting this technically superior system'.
Last-night exam-cram coach as a Claude Agent Skill: turns your slides, notes and past papers into a chaptered knowledge base + quiz bank, t…
Last-night exam-cram coach as a Claude Agent Skill: turns your slides, notes and past papers into a chaptered knowledge base + quiz bank, t…
Conduct stakeholder analysis using identification, Power-Interest matrix classification, and influence strategy development. Use this skill when the user needs to map stakeholders for a project, manage conflicting interests, prioritize communication, or build a stakeholder engagement plan — even if they say 'who needs to approve this', 'how do I get buy-in', or 'who might block this project'.
Last-night exam-cram coach as a Claude Agent Skill: turns your slides, notes and past papers into a chaptered knowledge base + quiz bank, t…
Last-night exam-cram coach as a Claude Agent Skill: turns your slides, notes and past papers into a chaptered knowledge base + quiz bank, t…
Apply Kuhn's paradigm theory to analyze scientific progress through the cycle of normal science, anomalies, crisis, and revolution. Use this skill when the user needs to understand why a field resists change, trace paradigm shifts in a discipline, analyze incommensurability between competing frameworks, or when they ask 'why do scientists ignore contradictory evidence', 'how do scientific revolutions happen', or 'why can't proponents of different paradigms agree'.
Apply Self-Determination Theory to analyze motivation quality along the autonomy continuum and design interventions that satisfy basic psychological needs. Use this skill when the user needs to diagnose why intrinsic motivation is declining, evaluate incentive structures for motivational crowding, design need-supportive environments, or when they ask 'why did rewards backfire', 'how to foster intrinsic motivation', or 'what needs drive engagement'.
Operate a Shopee Taiwan store — listings, promotions, flash sales, SIP (Shopee Supported Program) cross-border, ads (蝦皮廣告), and reputation/review management. Use when setting up or running Shopee TW operations, participating in platform campaigns (雙11, 618), or managing seller-center workflows. Do NOT use for Shopee API integration specifics (no official Asgard MCP yet) or DTC platforms. STATUS: SKELETON — body pending.
Design conversational commerce experiences across messaging platforms including chatbot flows, product cards, and conversion strategies. Use this skill when the user needs to sell through LINE, WhatsApp, Instagram DM, or other messaging channels, design chatbot purchasing flows, or integrate messaging into their sales funnel — even if they say 'sell through LINE', 'build a shopping chatbot', 'customers ask to buy in our DMs', or 'conversational sales strategy'.
Comply with Taiwan consumer protection law (消保法) — 7-day 鑑賞期 scope and exceptions (生鮮 / 客製化 / 數位商品 / 藥品), return / refund timing, disclosure requirements, and unfair-term invalidation. Use when drafting T&C, handling return disputes, or assessing if a SKU is exempt from 鑑賞期. Do NOT use for PDPA (use tw-ecom-compliance-pdpa). STATUS: SKELETON — body pending.
Integrate 街口支付 (JKOPay) for Taiwan e-commerce — web/app flow, JKO 幣 rewards, merchant settlement cycle, and scan-to-pay vs app-to-pay UX. Use when targeting younger TW demographic or integrating in-app JKO flow. Do NOT use for generic wallet integration (LINE Pay / Apple Pay handled elsewhere). STATUS: SKELETON — body pending.
Design and conduct user research using interviews, focus groups, surveys, and field observation. Use this skill when the user needs to understand customer needs, validate product assumptions, gather qualitative insights, or design a research study — even if they say 'we need to talk to users', 'how do we validate this idea', or 'what do our customers actually think'.
Apply the Capital Asset Pricing Model (CAPM) to estimate expected returns and assess risk-return tradeoffs. Use this skill when the user needs to calculate expected return on an asset, interpret beta as systematic risk exposure, evaluate whether an investment compensates for risk, or when they ask 'what return should I expect', 'what is the risk premium', or 'how does beta affect pricing'.