3,111 artifacts
Skills, MCPs, agents, and plugins. Search to find fast, or page through the catalog.
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This skill helps Claude write secure web applications. Use this when working on any web application or when a user requests a scan or audit to ensure security best practices are followed.
Use this skill whenever the user asks about Apple apps — Reminders, Calendar, Contacts, Notes, Mail, or tmux sessions. This includes creating/completing reminders, checking/adding calendar events, looking up contacts, reading/writing notes, sending/reading email, and capturing tmux session content. Also use this skill when the user mentions tasks, todos, scheduling, birthdays, free time slots, or end-of-day summaries. The bridges are CLI tools installed at ~/.claude/ that give Claude Code native access to these Apple apps on macOS.
分析减肥数据、计算代谢率、追踪能量缺口、管理减肥阶段
分析旅行健康数据、评估目的地健康风险、提供疫苗接种建议、生成多语言紧急医疗信息卡片。支持WHO/CDC数据集成的专业级旅行健康风险评估。
分析中医体质数据、识别体质类型、评估体质特征,并提供个性化养生建议。支持与营养、运动、睡眠等健康数据的关联分析。
分析睡眠数据、识别睡眠模式、评估睡眠质量，并提供个性化睡眠改善建议。支持与其他健康数据的关联分析。
分析康复训练数据、识别康复模式、评估康复进展，并提供个性化康复建议
分析职业健康数据、识别工作相关健康风险、评估职业健康状况、提供个性化职业健康建议。支持与睡眠、运动、心理健康等其他健康数据的关联分析。
分析营养数据、识别营养模式、评估营养状况，并提供个性化营养建议。支持与运动、睡眠、慢性病数据的关联分析。
分析心理健康数据、识别心理模式、评估心理健康状况、提供个性化心理健康建议。支持与睡眠、运动、营养等其他健康数据的关联分析。
分析一段时间内健康数据的趋势和模式。关联药物、症状、生命体征、化验结果和其他健康指标的变化。识别令人担忧的趋势、改善情况，并提供数据驱动的洞察。当用户询问健康趋势、模式、随时间的变化或"我的健康状况有什么变化？"时使用。支持多维度分析（体重/BMI、症状、药物依从性、化验结果、情绪睡眠），相关性分析，变化检测，以及交互式HTML可视化报告（ECharts图表）。
分析健康目标数据、识别目标模式、评估目标进度,并提供个性化目标管理建议。支持与营养、运动、睡眠等健康数据的关联分析。
分析运动数据、识别运动模式、评估健身进展，并提供个性化训练建议。支持与慢性病数据的关联分析。
分析家族病史、评估遗传风险、识别家庭健康模式、提供个性化预防建议
生成紧急情况下快速访问的医疗信息摘要卡片。当用户需要旅行、就诊准备、紧急情况或询问"紧急信息"、"医疗卡片"、"急救信息"时使用此技能。提取关键信息（过敏、用药、急症、植入物），支持多格式输出（JSON、文本、二维码），用于急救或快速就医。
AI驱动的综合健康分析系统，整合多维度健康数据、识别异常模式、预测健康风险、提供个性化建议。支持智能问答和AI健康报告生成。
Integrate digital health data sources (Apple Health, Fitbit, Oura Ring) and connect to WellAlly.tech knowledge base. Import external health device data, standardize to local format, and recommend relevant WellAlly.tech knowledge base articles based on health data. Support generic CSV/JSON import, provide intelligent article recommendations, and help users better manage personal health data.
End-to-end bulk RNA-seq orchestrator — takes raw FASTQ reads through QC and trimming (FastQC, fastp/Trim Galore), alignment and quantification (STAR, Salmon, featureCounts), assembles a gene-level counts matrix, then hands off to differential expression (pydeseq2), pathway/GSEA enrichment (pathway-enrichment), and publication figures (scientific-visualization). Use whenever the user has bulk RNA-seq reads or quant output and wants a complete, reproducible differential-expression workflow — e.g. "analyze my RNA-seq", "FASTQ to DESeq2", "run nf-core/rnaseq", "STAR/Salmon quantification", "build a counts matrix for DESeq2", or "go from reads to differentially expressed genes and enriched pathways". Routes between an nf-core/rnaseq (Nextflow) path and a standalone STAR/Salmon path, and covers experimental design, strandedness, and QC gates. For single-cell RNA-seq use the scanpy skill instead.
Autonomously improve a real artifact (code, training recipe, agent harness, data pipeline, prompt) against an objective and an evaluator, using Hypothesis Tree Refinement (HTR) from the Arbor paper. Use this whenever someone wants to iteratively optimize something over many experiments without overfitting — e.g. "get my model's eval score up", "improve this agent/harness", "tune this pipeline", "beat the baseline on this benchmark", "run a search over approaches and keep the best", "do an MLE-bench / Kaggle-style optimization", or any long-horizon "make this artifact better and don't just memorize the dev set" task. Trigger it even when the user doesn't say "Arbor" or "hypothesis tree" but describes repeated experiment-and-evaluate loops, branching exploration of competing ideas, or worries about a dev/test gap. Runs Claude itself as the coordinator with subagent executors in isolated git worktrees; for the standalone `arbor` CLI tool see references/arbor-upstream.md.
基于退哥短线交易规则的A股场景化决策技能。Use when 用户要按交易场景查看短线规则、做选股、判断趋势回踩、涨停回调、连板接力、洗盘结束、卖出失效或仓位纪律。
基于“均线定方向，MACD定节奏”的A股选股与交易计划技能。Use when 用户要求把均线与MACD结合做选股、筛票、盘前候选池、趋势跟随、回踩再上、金叉确认、顶背离减仓、或希望把技术判断沉淀成可执行规则与风控模板。
A股“MACD底背离 + 零轴下二次金叉”实战分析与交易执行技能。用于把用户的盘感描述转成可执行的三档决策（上观察名单/可试错出手/必须放弃）、盘中检查单、入场与风控规则。适用于用户提到“二次金叉”“水下二次金叉”“底背离”“第一脚第二脚”“回踩验底”“MACD背离”“抄底修复”“想做但怕假信号”等场景。
A股模拟盘交易与回测技能。Use when 用户要启动模拟仓服务、创建多账户、下限价单/市价单、撤单、查询持仓资金、验证涨跌停成交逻辑或运行A股回测。
查询A股实时行情、历史数据、技术指标、事件、资金面、热门行业/概念、板块热力图与个股行业信息。Use when 用户提到股票代码、板块、热门概念、热门行业、概念涨跌、行业涨跌、热力图、市场快讯、技术分析、财务指标、指数成分、交易日历、宏观数据或个股所属行业。
Interactive walkthrough of the Memory Kit system using the user's actual project files
End-of-session ritual — audit today's patterns against accumulated memory, propose promotions, refresh MEMORY.md, and write the session handoff. Use when the user says "/close-session", "закрой сессию", "закрываем", "we're done for today", "wrap up".
Persistent memory for Claude Code agents with an agent-audit-ritual architecture. User only talks; the agent captures, audits, proposes promotions, and writes. Memory lives in layers — a hot cache (MEMORY.md) held under three size caps, per-session handoffs (context/handoffs/), topical knowledge articles (knowledge/concepts/), and canonical rules (.claude/rules/) — plus multi-project isolation via projects/<name>/ and an experiments/ sandbox. /close-session runs the end-of-session audit ritual. Zero external dependencies.
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When something goes wrong, the user must be able to recover or try again. Toasts, inline errors, banners, and notification patterns each have a specific role. Use when designing error states, success confirmations, async feedback, in-place editing, or any system that communicates state changes to the user.
UI design and review should apply Nielsen's 10 Usability Heuristics — the foundational principles for evaluating and improving usability. Use when auditing an interface, designing interaction flows, writing error messages, or reviewing any UI for usability issues.