所有 Skills
找到 8165 个 Skills
Skills 列表
telegram-bot-builder
构建解决实际问题的Telegram机器人的专家——从简单自动化到复杂的AI驱动机器人。涵盖机器人架构、Telegram Bot API、用户体验、变现策略以及将机器人扩展到数千用户。
sickn33mobile-design
（移动优先 · 触控优先 · 尊重平台）
sickn33game-development
游戏开发编排器。根据平台、维度和引擎适配性（网页2D/3D、混合DOM+画布、叙事工具）进行路由。在启动或构建游戏项目、选择框架，或在Phaser、PixiJS、Kaplay、Canvas/WebGL、Three.js、Babylon.js、Godot、Unity或Ink/Twine之间做选择时使用。
sickn33software-architecture
专注于高质量软件架构的指南。当用户想要编写代码、设计架构、分析代码或任何与软件开发相关的情况时，应使用此技能。
sickn333d-web-experience
擅长使用 Three.js、React Three Fiber、Spline、WebGL 等技术构建网页 3D 体验的专家。涵盖产品配置器、3D 作品集、沉浸式网站以及为网页体验增添深度。
sickn33playwright-skill
【重要 - 路径解析】此 Skill 可能安装在不同的位置（如插件系统、手动安装、全局或特定项目）。在执行任何命令之前，请先根据加载此 SKILL.md 文件的位置确定 Skill 所在目录，并在后续所有命令中使用该路径。
sickn33prisma-expert
您是 Prisma ORM 专家，精通模式设计、迁移、查询优化、关系建模以及 PostgreSQL、MySQL 和 SQLite 的数据库操作。
sickn33
autoskill
Observe the user's screen via screenpipe, detect repeated research workflows, match them against existing scientific-agent-skills, and draft new skills (or composition recipes that chain existing ones) for the patterns not yet covered. Use when the user asks to analyze their recent work and propose skills based on what they actually do. Requires the screenpipe daemon (https://github.com/screenpipe/screenpipe) running locally on port 3030 — the skill has no other data source and will refuse to run if screenpipe is unreachable. All detection runs locally; only redacted cluster summaries reach the LLM.
k-dense-ainextjs-supabase-auth
Next.js App Router 与 Supabase Auth 深度集成最佳实践指南
sickn33browser-automation
浏览器自动化为 Web 测试、数据抓取与 AI Agent 交互提供核心动力。
sickn33hugging-science
Use when the user is doing AI/ML work in a scientific domain such as biology, chemistry, physics, astronomy, climate, genomics, materials, medicine, ecology, energy, engineering, math, drug discovery, protein design, weather modeling, theorem proving, single-cell, or PDE solving. Hugging Science is a curated catalog of scientific datasets, models, blog posts, and interactive Spaces. This skill helps discover and use resources via `datasets`, `transformers`, the HF Inference API, `gradio_client`, and methodology citations.
k-dense-aiapi-security-best-practices
实现安全的API设计模式，包括身份验证、授权、输入验证、速率限制以及防范常见API漏洞
sickn33nextjs-best-practices
Next.js App Router 原则。服务端组件、数据获取、路由模式。
sickn33clean-code
此技能体现了Robert C. Martin（Uncle Bob）《代码整洁之道》的原则。用它来将“能工作的代码”转变为“整洁的代码”。
sickn33typescript-expert
TypeScript和JavaScript专家，精通类型级编程、性能优化、单体仓库管理、迁移策略和现代工具链。
sickn33
attribution
当用户需要找出究竟是哪些营销活动真正带动了转化和收入、选择或解读归因模型、或者调和不同工具之间互相冲突的数据时使用。当用户提到以下词汇或需求时也可调用：“归因 (attribution)”、“归因模型 (attribution model)”、“首触 vs 尾触 (first-touch vs last-touch)”、“多触点归因 (multi-touch)”、“哪个渠道带进来的收入更多”、“我的真实 CAC 是多少”、“后台数据对不上”、“Google/Meta 显示 X，但 GA 却显示 Y”、“媒体混合模型 (media mix model)”、“MMM”、“增量分析 (incrementality)”、“地理位置提升测试 (geo lift)”、“对照组测试 (holdout test)”、“你是从哪里听说我们的 (how did you hear about us)”、“自报归因 (self-reported attribution)”、“暗社交 (dark social)”；或者想要自行埋点实现归因——“把我的预约/订单绑定回溯到来源”、“SavvyCal/Calendly 归因”、“缩小用户身份辨识缝隙 (close the identify gap)”、“追踪第三方域名的转化”、“第一方/自建归因 (first-party / self-hosted attribution)”。关于事件埋点设置和 UTM，参见 analytics。关于广告平台 Pixel/CAPI，参见 ads。关于 Pipeline 和 CRM 收入报表，参见 revops。关于 AI 搜索归因的盲区，参见 ai-seo。
coreyhaines31opentrons-integration
Author, review, migrate, simulate, and troubleshoot official Opentrons Python Protocol API v2 protocols for Flex and OT-2 robots. Use for robot-specific liquid handling, deck and labware setup, pipettes, modules, runtime parameters, liquid classes, and Opentrons App analysis. Use pylabrobot instead when one workflow must support multiple robot vendors.
k-dense-airowan
Rowan is a cloud-native molecular modeling and medicinal-chemistry workflow platform with a Python API. Use for pKa and macropKa prediction, conformer and tautomer ensembles, docking and analogue docking, protein-ligand cofolding, MSA generation, molecular dynamics, permeability, descriptor workflows, and related small-molecule or protein modeling tasks. Ideal for programmatic batch screening, multi-step chemistry pipelines, and workflows that would otherwise require maintaining local HPC/GPU infrastructure.
k-dense-aiqutip
Simulate and audit closed and open quantum-system models with QuTiP 5, including deterministic, trajectory, steady-state, spectral, and phase-space workflows. Use for local quantum-dynamics work where physical assumptions, dimensions, and numerical convergence must be explicit.
k-dense-aicobrapy
Constraint-based metabolic modeling (COBRA). FBA, FVA, gene knockouts, flux sampling, SBML models, for systems biology and metabolic engineering analysis.
k-dense-aiqiskit
Build, simulate, transpile, and execute quantum circuits with Qiskit and IBM Quantum Runtime. Use for Qiskit 2.x circuits and operators, V2 Sampler or Estimator primitives, target-aware transpilation, local or noisy simulation, IBM QPU execution, Runtime sessions or batches, error mitigation, and Qiskit ecosystem packages.
k-dense-aipylabrobot
Develop and review PyLabRobot lab-automation resources, liquid-handling plans, offline simulations, and supported-device integrations. Use for PyLabRobot protocols or API questions; keep physical execution behind an explicit operator safety gate.
k-dense-aineuropixels-analysis
Analyze Neuropixels extracellular recordings end-to-end with SpikeInterface. Covers loading SpikeGLX/Open Ephys/NWB data, preprocessing, drift/motion correction, Kilosort4 (and CPU) spike sorting, quality metrics, and unit curation (threshold-based, model-based UnitRefine, and AI-assisted visual review). Use when working with Neuropixels 1.0/2.0 recordings, spike sorting, or extracellular electrophysiology analysis.
k-dense-ailamindb
Use when working with LaminDB, the open-source lineage-native lakehouse for biological datasets and models. Covers setup, artifact registration, query/search, lineage tracking, validation, ontology-backed annotation with Bionty, collections, branches, storage, and workflow integrations.
k-dense-ai