Claude Skills
The open format is called Agent Skills and works in Claude Code, Codex, Cursor and other agents — most people know it as Claude Skills.
Every Agent Skill we could find on GitHub, deduplicated by content. 86 961 files from 2 125 authors, of which 68 678 are unique — the rest is the same skill repackaged into someone else's repository. For each one: what it weighs in tokens, whether it ships runnable scripts, and which MCP servers it needs.
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| Update SenseNova Skills (the sn-* bundle) inside an OpenClaw or hermes-agent skills", "update SN skills", "更新 sensenova skills", "更新 sn skills", "刷新 sn-*", "升级 sn-* skills", or names a specific sn-* skill to update (e.g. "更新 sn-ppt-standard", "refresh sn-image-base"). Default scope is the whole sn-* bundle; if the user names specific skills, update ONLY those.
Set up FirebaseUI Android Auth with predefined Compose screens in a consumer Android app. Use when adding Firebase Authentication UI, FirebaseUI Auth, FirebaseAuthScreen, authUIConfiguration, or sign-in providers to an Android/Kotlin project.
> Structure prediction for protein, nucleic-acid, and small-molecule complexes with the Chai-1 foundation model (Chai Discovery 2024, github.com/chaidiscovery/chai-lab). Reach for this skill to predict an antibody-antigen or protein-ligand complex from a single FASTA, to re-fold designed binders as an AlphaFold-multimer alternative, or to drive co-folding from Python for batched campaigns on a GPU.
> Predict protein structure for monomers and multimers with AlphaFold2 via the ColabFold runner (Mirdita et al. 2022, github.com/sokrypton/ColabFold; AlphaFold2 Jumper et al. 2021). Reach for this skill to fold a sequence or complex with the AF2/AF2-Multimer evoformer, to validate designed sequences by self-consistency pLDDT, ipTM, and RMSD, or to run a quick MSA-backed prediction using the public MMseqs2 server.
> Structure prediction for protein, nucleic-acid, and small-molecule complexes with Boltz-2 (Passaro & Wohlwend et al. 2025, github.com/jwohlwend/boltz). Reach for this skill to validate designed binders against a target, to co-fold a protein with a SMILES or CCD ligand, or to get an open-source AlphaFold3 alternative with optional binding-affinity prediction.
Prepare reproducible setup instructions and validate a user-managed named software environment on an Open-Science SSH Compute Host, including direct SSH and Slurm hosts. Use when a remote job needs packages, modules, cache variables, or a repeatable activation that the host does not already provide.
Use when a notebook run fails on a missing package (ImportError, ModuleNotFoundError, "there is no package called"), when you need to inspect an installed package version, or when you need to install, add, or manage Python or R packages for the notebook runtime. Covers inspect_packages, routing Python vs R through manage_packages, why in-cell %pip/!pip/install.packages() and OS installers are forbidden, restarting the kernel after an install, and when to stop and ask the user.
> Predict small-molecule binding poses with DiffDock-L (Corso et al. 2023/2024, github.com/gcorso/DiffDock) — blind diffusion docking that places a ligand into a protein pocket without a predefined search box and ranks the samples with a learned confidence model. Reach for this skill to dock a SMILES or SDF against a PDB, to generate ranked 3D poses for a small fragment library, or to get a starting pose for downstream rescoring. DiffDock predicts geometry, not affinity.
> Predict genome-wide functional tracks (RNA-seq, CAGE, DNase, ChIP) from DNA (1) Scoring the regulatory effect of a variant on expression/accessibility, (2) Generating predicted coverage tracks for a locus, (3) Prioritising non-coding variants by predicted track delta.
Use when the user wants to create or manage a Specialist agent or create, revise, publish, or delete a Skill through the conversational `/Customize` entry. Routes Skill work to the internal skill-creator and handles Specialist work through the JavaScript host.agents SDK.
> Embed proteins with Meta AI's ESM-2 (`fair-esm` package). Use this skill ML, (2) Masked-LM likelihood / mutation effect scoring, (3) Contact prediction from a sequence.
> Biohub ESMFold2 / ESMFold2-Fast all-atom co-folding (Candido et al. 2026, github.com/Biohub/esm). Single-sequence and MSA modes; protein, DNA, RNA, ligand (CCD/SMILES), modified residues. FoldBench Ab-Ag 50-55%, PPI 70-77% DockQ-pass. Also covers the ESMC-{300M,600M,6B} protein language models from prediction, and the SAE interpretability head. MIT-licensed weights on structures with single-sequence input, (2) Validating designed binders with ESMFold2-Fast, (3) Running ESMFold2 with MSA input, (4) Getting ESMC embeddings or per-residue mutation scores, (5) Choosing kernel backend and sampling-step settings for paper-faithful throughput.
Compose one publication-grade multi-panel figure. Start from a one-line claim plus immutable data Artifact Version references, or inspect an existing figure and draft its outline directly. Plan a 12-column panel outline, delegate one worker per panel, compose and inspect the result, then run at most three adversarial review rounds while regenerating only affected panels. For a standalone plot use `figure-style`; for whole-paper figure ordering use `paper-narrative`.
> Inverse-fold a backbone with ligand, nucleic-acid, and metal context using LigandMPNN (Dauparas et al. 2023, github.com/dauparas/LigandMPNN). Reach for this skill to redesign the residues lining a binding pocket around a bound small molecule or cofactor, to design metal-coordinating sites where the geometry must be respected, or to get threaded designed-sequence PDBs out of any MPNN run.
Publication-grade correctness and legibility rules for final-deliverable scientific figures, not exploratory plots. Use for a figure that will ship in a report, paper, export, or kept artifact. Covers data fidelity, label economy, color threading, chart choice, layout, and render-then-verify QA without imposing a visual house style. For multi-panel composition use `figure-composer`; for whole-paper ordering use `paper-narrative`.
> Score, embed, and generate DNA sequences with Evo 2, a long-context genomic (1) Computing per-nucleotide or per-sequence likelihoods for variant effect scoring, (2) Embedding genomic windows for downstream classification, (3) Generating DNA conditioned on a prefix, (4) Scoring regulatory or coding regions across species.
> Generate a therapeutic indication dossier. Covers the patient population, epidemiology, disease biology, standard of care, regulatory precedent, and landmark clinical trials.
Find, verify, and synthesize scientific literature — from "what's the seminal paper for X" through full multi-source reviews. Covers grounding claims in real retrieved sources, avoiding fabricated citations, handling retractions, and calibrating confidence to evidence strength.
Judge and reshape the story told by an entire paper figure deck. Use when writing or revising a paper to derive a grounded brief from the manuscript and captions, review the full deck as a handling editor, and hand an ordered figure arc to `figure-composer`.
> Structure prediction using OpenFold3, an open-weights PyTorch reproduction of AlphaFold3 from the AlQuraishi Lab. Use this skill when predicting protein/nucleic-acid/ligand complex structures with an Apache-2.0-licensed AF3 reimplementation.
> Inverse-fold a protein backbone (PDB structure) into amino-acid sequence with ProteinMPNN (Dauparas et al. 2022, github.com/dauparas/ProteinMPNN). Reach for this skill to run sequence design on RFdiffusion backbones, to redesign one chain of a PDB while holding interface residues fixed, or to generate a temperature-swept set of sequences for downstream folding.
> Embed and annotate single-cell expression data with scGPT, a foundation model (1) Producing cell embeddings from an AnnData for clustering/integration, (2) Zero-shot or fine-tuned cell-type annotation, (3) Gene-level representation for perturbation/GRN tasks. For probabilistic single-cell models (scVI etc.), use the scvi-tools library.
Inspect Open-Science's JavaScript control REPL, discover managed Project files, Sessions, and Agent Frames, and safely feature-gate host.* calls with host.capabilities(). Use when an Agent needs to discover available host APIs, locate an Artifact or Upload Version, diagnose a Session, or read a Frame transcript in the current Project.
Evaluate and use SSH Remote Compute before choosing where to run GPU, high-memory, parallel, batch, model-inference, bioinformatics, or other long-running scientific work; supports short remote commands and asynchronous jobs with automatic harvest and analysis.
> Probabilistic single-cell RNA-seq with scvi-tools — scVI for a batch-corrected latent space, scANVI for semi-supervised label transfer, and Bayesian differential expression. Reach for this skill to integrate scRNA-seq batches, embed cells for clustering, transfer annotations from a reference onto a query, or score differentially expressed genes per cluster. For spatial deconvolution / mapping use the cell2location, DestVI, or Tangram methods instead.
Create, revise, evaluate, publish, and improve Open-Science Skills through the native JavaScript host.skills composer. Use when the user wants a reusable workflow, an existing Skill changed, test cases or benchmarks for a Skill, or better Skill triggering.
Cherry-pick a merged main-branch PR onto a MsQuic release branch (release/X.Y).
Guide systematic investigation of MsQuic CI test failures reported by GitHub Actions.
小跃虚拟伴侣 - 使用智谱 AI 提供温暖的对话陪伴和静态图片分享
统一管理多智能体角色的团队协作框架，支持智能体动态组合、灵活协作和扩展新角色。智能体本质上是"角色定义"，可以根据任务需求灵活组建团队，实现从会议决策到系统构建的完整能力。智能体角色明确分工：有干活的、有指挥的、有挑毛病的，能实时看到沟通过程，共享数据库记忆，确保上下文一致。
基于ByteDance agentkit-samples多媒体用例的小省导购员数字人带货视频生成技能，整合多模态内容生成能力（图像、视频、音频），支持AI绘画、语音合成、视频生成，与小省导购员人设融合，9:16竖屏适配，直接对接带货视频生成流程
分析文章内容，在需要视觉辅助理解的位置生成插画。配图可以是信息补充、概念具象化，或引导读者想象。当用户要求"给文章配图"、"为文章生成插图"、"添加配图"时使用此技能。
为3-12岁儿童提供温馨亲切的睡前寓言故事和成语典故讲解。支持用户唤醒后提供故事列表选择，或直接讲解指定故事/成语。讲解时保持亲切温馨的语气、0.6倍正常语速、通俗易懂的表达，为小朋友营造舒适的睡前氛围。
Connect to and control Google Chrome browser using agent-browser with CDP (Chrome DevTools Protocol). Use when the user wants to automate their existing Chrome browser, see browser actions in real-time, or needs to control the Chrome instance they're already using. Handles installation, setup, connecting via remote debugging, and all browser automation tasks with live visual feedback.
内容创作与发布全流程技能，整合网页采集、Markdown格式化、智能配图、多平台发布（微信公众号、X/Twitter）功能，实现从内容获取到发布的一站式解决方案
Formats plain text or markdown files with frontmatter, titles, summaries, headings, bold, lists, and code blocks. Use when user asks to "format markdown", "beautify article", "add formatting", or improve article layout. Outputs to {filename}-formatted.md.
Posts content to WeChat Official Account (微信公众号) via API or Chrome CDP. Supports article posting (文章) with HTML, markdown, or plain text input, and image-text posting (图文) with multiple images. Use when user mentions "发布公众号", "post to wechat", "微信公众号", or "图文/文章".
Posts content and articles to X (Twitter). Supports regular posts with images/videos and X Articles (long-form Markdown). Uses real Chrome with CDP to bypass anti-automation. Use when user asks to "post to X", "tweet", "publish to Twitter", or "share on X".
小省导购员多智能体数字人口播带货视频生成系统，以"小省导购员"为核心人设，打造专业购物助手+数字人口播带货视频一体化服务。涵盖五大智能体（小省导购员、带货脚本师、数字人口播生成师、带货画面设计师、音画合成师），产出"数字人口播+带货画面+字幕音效"的成品视频，适配抖音、快手等短视频平台，支持淘宝、京东、拼多多、唯品会等全平台商品信息，具备知识库自动存取能力。
小省导购员数字人带货版即梦视频提示词生成系统，基于四大智能体协同（提示词生成师、质量管控师、知识库运维师、跨环节适配师），按照"主体+运动+场景+（镜头语言+光影+氛围）"公式输出中英文双版提示词，适配5s短视频。确保人物一致性、视觉连贯性、情绪连贯性，支持知识库智能复用和跨工具适配（Suno音乐、AI绘画），为数字人带货视频提供高质量提示词生成服务。
电商图片文案创作技能，支持多品类产品的吸引性文案生成，适用于电商平台的商品营销推广
跨境电商全链路自动化工具。集成1688采集、智能清洗、多平台上架（微信小店/Shopify/TikTok）、推广方案（关键词/竞品分析/广告文案）、短视频创作（MoviePy竖屏视频）、一键代发、爆品挖掘（趋势聚合+6维评分）、闲鱼二手选品捡漏（品牌识别/虚标过滤/捡漏评分/价格监控）、全自动流水线（挖掘→采集→清洗→上架→推广→视频）。
电商视频营销创作技能，支持多品类商品的营销视频脚本生成，包含6阶段创作流程、智能体提示词框架、8种商品类型模板，适用于电商平台、社交媒体、品牌推广
生成历史名人现代访谈短视频文案，通过古今反差与网络热梗的爆笑结合，创作具有传播力的虚构趣味内容
自动化生成历史科学类3分钟科普短视频的全流程素材包，包含口播文案、分镜脚本、Veo2提示词、人物形象规范等，适配即梦平台视频生成。
专为InfiniteTalk项目设计的小省导购员数字人带货提示词生成技能，基于四大智能体协同（提示词生成师、质量管控师、知识库运维师、跨环节适配师），生成适配Image-to-Video模式的结构化提示词（角色固定特征+动作时序+场景环境+音频匹配+光影氛围+技术约束），支持9:16竖屏、5s/幕、音频同步（Suno+chinese-wav2vec2-base）、一致性管控（角色/视觉/情绪），直接对接模型推理流程
音频驱动的稀疏帧视频配音工具，支持音频驱动的 Video-to-Video 和 Image-to-Video 生成，实现精准的唇形、头部、身体姿态同步，支持无限时长视频生成
| 智能内容创作与发布全流程系统。根据用户需求自动识别场景， 编排调用网页采集、智能配图、小红书图文生成、热点内容创作、多平台发布等技能， 实现从内容获取到发布的一站式自动化。 支持场景： 支持平台：微信公众号、小红书、X/Twitter、B站
Contract review skill that adds comment-based issue annotations without changing original text. Enforces a three-layer review (basic, business, legal), writes structured comments (issue type, risk reason, revision suggestion) with risk level encoded via reviewer name, and generates a contract summary, consolidated opinion, and Mermaid business flowchart (with rendered image). Output language must follow the contract’s language.
将法条/规范文件（.txt/.docx/.pdf）转为 Markdown。适用于用户要求“法条转 markdown”“pdf/docx 转 markdown”。处理 .pdf/.docx 时先检查是否已安装 mineru-ocr skill；未安装先引导安装，安装后优先用 mineru-ocr；仅在用户明确同意时再用本地回退方案。
提供基于 FFmpeg 和 ImageMagick 的多媒体处理能力，支持视频和图像的格式转换、分辨率调整、压缩等操作
AI Agent的社交网络. 发布帖子、评论、点赞和创建社区。当用户明确要求时才会使用，否则不会使用。
模拟多个AI智能体协作开会并进行决策讨论的场景。适用于需要从多个专业角度分析问题、进行辩论和达成共识的场景，如项目决策、技术方案评审、商业策略制定等。
PPT 视觉增强工具，支持多种风格渲染、交互式播放器生成和视频合成。可与 ppt-generator Skill 协同工作，实现从内容规划到视觉呈现的完整流程。
Create and edit JSON Canvas files (.canvas) with nodes, edges, groups, and connections. Use when working with .canvas files, creating visual canvases, mind maps, flowcharts, or when the user mentions Canvas files in Obsidian.
Create and edit Obsidian Bases (.base files) with views, filters, formulas, and summaries. Use when working with .base files, creating database-like views of notes, or when the user mentions Bases, table views, card views, filters, or formulas in Obsidian.
根据arXiv论文网址自动下载PDF并进行多维度分析，包括文本提取、词频分析、语音播报、播客对话生成、交互式网页、PPT、总结图和引用分析
萌宠带货短视频全流程创作技能，基于COZE视频大模型API，支持萌宠剧情/好物测评/品种科普/宠品带货等全类型创作，覆盖爆款解析反推、知识库联动、互动优化、素材批量下载、全素材整合，实现从创意到带货引流型成品视频的自动化生成，适配15-30秒竖屏9:16主流平台规格。
Claude Skills — questions
Answers built from the skills we actually parsed.