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Skill-uri SKILL.md publice din depozite GitHub cu peste 50 de stele și de la producători, scanate și evaluate. Instalează oricare dintre ele cu o singură comandă în Claude Code, Cursor, Codex, GitHub Copilot sau Gemini CLI.
45.604 skill-uri din 2.205 depozite · actualizat acum 12 ore
45.604 skill-uri
- top-value-coloringOpenSenseNova/SenseNova-Skills根据数据规模动态选择处理策略，对多表数据进行合并、统计筛选，并利用 openpyxl 实现关键指标的自动化样式高亮与格式化导出。AlteleFără avertismente★ 5,9 K↓ —
- excel-multi-sheet-threshold-analysisOpenSenseNova/SenseNova-Skills统计多Sheet Excel总行数并根据规模选择处理策略，提取特定维度信息进行去重统计，并生成摘要与明细报表。DocumenteFără avertismente★ 5,9 K↓ —
- outlier-detection-and-quality-assessmentOpenSenseNova/SenseNova-Skills执行全面的异常值检测与数据质量评估，利用 IQR 方法识别异常值并结合偏度、峰度分析数据分布特征，适用于非正态分布数据的预处理阶段。AlteleFără avertismente★ 5,9 K↓ —
- category-filtering-and-difficulty-analysisOpenSenseNova/SenseNova-Skills对Excel数据进行自定义分类统计、交叉分析与可视化，并基于多维度指标（如文本长度、术语密度、正则匹配等）进行综合评分与分级，适用于多类别数据分布统计及文本内容难度/质量评估场景。DocumenteFără avertismente★ 5,9 K↓ —
- excel-basic-statistics-and-routingOpenSenseNova/SenseNova-Skills对多Sheet Excel文件进行基础统计与，支持按条件筛选计算均值，以及从指定行区间提取数据去重求和，并生成结果文件与下载链接。DocumenteFără avertismente★ 5,9 K↓ —
- categorical-comparison-analysisOpenSenseNova/SenseNova-Skills对两类分类数据进行对比分析，统计数量差异与比例关系并生成可视化图表。AlteleFără avertismente★ 5,9 K↓ —
- melonjs-performanceActualizatmelonjs/melonJSUse this skill when a melonJS game drops frames, allocates heavily, or needs to scale to many objects. Covers object pooling, draw-call batching, atlases, baking with CanvasRenderTarget, instancing, culling and alwaysUpdate, the debug plugin, and where the real costs are. Triggers on: performance, slow, frame rate, fps, lag, pool, pool.register, pool.pull, batching, draw calls, InstancedMesh, culling, alwaysUpdate, inViewport, CanvasRenderTarget, optimise, profiling, debug plugin, memory, render targets, hdr.MediaFără avertismente★ 6,4 K↓ —
- scgptaipoch/open-scienceEmbed and annotate single-cell expression data with scGPT, a foundation model for single-cell biology. Use this skill when: (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.ȘtiințăFără avertismente★ 5,4 K↓ —
- melonjs-deploymentmelonjs/melonJSUse this skill when packaging, shipping or scaffolding a melonJS game — starting a project with create-melonjs, building for the web, wrapping as a native app with Capacitor or Cordova, publishing to WeChat Mini Games or Facebook Instant Games, browser support and transpiling. Triggers on: create-melonjs, scaffold, new project, build, deploy, publish, Capacitor, Cordova, native app, iOS, Android, WeChat, Instant Games, browser support, transpile, ES2022, bundle size, tree-shaking.DevOpsFără avertismente★ 6,4 K↓ —
- maui-shell-navigationdotnet/skillsGuide for implementing Shell-based navigation in .NET MAUI apps. Covers AppShell setup, visual hierarchy (FlyoutItem, TabBar, Tab, ShellContent), URI-based navigation with GoToAsync, route registration, query parameters, back navigation, flyout and tab configuration, navigation events, and navigation guards. Use when: setting up Shell navigation, adding tabs or flyout menus, navigating between pages with GoToAsync, passing parameters between pages, registering routes, customizing back button behavior, or guarding navigation with confirmation dialogs. Do not use for: deep linking from external URLs (see .NET MAUI deep linking documentation), data binding on pages (use maui-data-binding), dependency injection setup (use maui-dependency-injection), or NavigationPage-only apps that don't use Shell.AlteleFără avertismente★ 5,7 K↓ —
- mirrord-header-propagationmetalbear-co/mirrordMakes a codebase propagate W3C baggage (the `baggage` header carrying `mirrord-session=<key>`) end to end, so mirrord HTTP filters, preview environments, and queue splitting can route a whole request chain to one developer's session. Detects existing OpenTelemetry, Datadog, or other tracing that can already propagate baggage and enables it; otherwise adds a small propagation layer. Covers inbound/outbound HTTP and gRPC, publishing to and consuming from Kafka, RabbitMQ, SQS/SNS, GCP Pub/Sub, Azure Service Bus, NATS, Redis Pub/Sub, BullMQ and Temporal, per-message context restore in consumers, and storage hand-offs such as a GCS signed URL upload that triggers Pub/Sub or an S3 presigned upload that triggers SQS. Ends with a report of every flow found and which ones still drop the header. Use when the user asks to propagate headers, baggage, tracestate, the mirrord session key, or trace context across services or queues, or when a mirrord filter matches the first service but not downstream services or queue consDevOpsFără avertismente★ 5,4 K↓ —
- paper-compilewanshuiyin/Auto-claude-code-research-in-sleepCompile LaTeX paper to PDF, fix errors, and verify output. Use when user says \"编译论文\", \"compile paper\", \"build PDF\", \"生成PDF\", or wants to compile LaTeX into a submission-ready PDF.ȘtiințăFără avertismente★ 18 K↓ —
- chai1aipoch/open-scienceStructure 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.ȘtiințăFără avertismente★ 5,4 K↓ —
- humanize-chinesebrycewang-stanford/Auto-Empirical-Research-SkillsDetect and humanize AI-generated Chinese text. 20+ rule detection categories plus statistical features (sentence-length CV, short-sentence fraction, comma density, perplexity, GLTR, DivEye) plus scene-aware LR fusion (rule × 0.2 + LR × 0.8) trained on three scenes: general / academic / longform 长文本 (≥1500 字)。Unified CLI: ./humanize {detect,rewrite,academic,style,compare}. 8 style transforms (casual/zhihu/xiaohongshu/wechat/academic/literary/weibo/novel)。 Multi-paragraph rewriting (paragraph length CV、跨段 trigram 重复) plus best-of-N humanize (默认 N=10 取最低 LR)。165 replacement patterns + CiLin 同义词词林 38873 with collision blacklist。 Academic paper AIGC reduction for CNKI/VIP/Wanfang (知网/维普/万方 AIGC 检测降重)。 Pure Python, no dependencies, offline。v5.0.0 — HC3 fused 准确率 95%、学术 hero 100→35 (-65)、 工作汇报 96→13 (-83)、长篇博客 96→41 (-55)。 Use when user says: "去AI味", "降AIGC", "人性化文本", "humanize chinese", "AI检测", "AIGC降重", "去除AI痕迹", "文本改写", "论文降重", "知网检测", "维普检测", "AI写作检测", "让文字更自然", "detect AI text", "humanize text", "reduce AIGC scRedactareFără avertismente★ 4,8 K↓ —
- sn-image-resumeOpenSenseNova/SenseNova-SkillsGenerates a designed portfolio-resume image from resume content provided in conversation text. Extracts optional style instructions, converts the resume into a fixed portfolio-resume layout prompt, and generates the final image through sn-image-base. Use when user asks to create "resume image", "portfolio resume", "简历图", "简历海报", or "个人简历视觉设计".MediaFără avertismente★ 5,9 K↓ —
- sn-research-reportOpenSenseNova/SenseNova-Skills用于撰写或组织研究报告结构。按读者认知任务（全景/对比/调查/时序）和领域惯例（学术/医疗/法律/政策）选择报告模板。ȘtiințăFără avertismente★ 5,9 K↓ —
- sn-ppt-storyOpenSenseNova/SenseNova-Skills当前 PPT 任务已由 sn-ppt-entry 建好 DECK_DIR（task_pack.json 与 info_pack.json 已写入）后，必须由本 skill 将 query、全部用户材料与已完成 Research 编排为唯一可编辑的 outline.md 时使用。本 skill 是 entry → 出口（standard / dazzle / creative）之间的强制中间环节：不允许执行 Agent 跳过本 skill 直接依据 task_pack / info_pack 即兴编写大纲，不允许出口 skill 代写或改写大纲；前置产物缺失时停止并返回 sn-ppt-entry 补齐，不得自行补做研究。ȘtiințăFără avertismente★ 5,9 K↓ —
- avoid-ai-writingbrycewang-stanford/Auto-Empirical-Research-SkillsAudit and rewrite content to remove AI writing patterns ("AI-isms"). Use this skill when asked to "remove AI-isms," "clean up AI writing," "edit writing for AI patterns," "audit writing for AI tells," or "make this sound less like AI." Supports a detection-only mode that flags patterns without rewriting.RedactareFără avertismente★ 4,8 K↓ —
- sn-image-imitateOpenSenseNova/SenseNova-SkillsGenerates a new image that imitates the style of a reference image while updating content based on user intent. Uses a three-stage pipeline: image annotation (long caption), caption rewriting, and image generation. Use when user asks to "imitate style", "保持这个风格重画", "按这张图风格生成", or "style transfer with new content".MediaFără avertismente★ 5,9 K↓ —
- mirrord-prev-envmetalbear-co/mirrordHelp users create and manage mirrord preview environments — running a modified service as an isolated pod in a shared Kubernetes cluster, scoped by an environment key and HTTP/queue traffic filtering, so teams can validate and review changes against real traffic without affecting live services. Use when a developer wants to run "mirrord preview" ad hoc, share a preview via a link (mirrord-share-ingress), or wire preview environments into CI with the metalbear-co/mirrord-preview GitHub Action (e.g. per-PR previews, least-privilege cluster access).DevOpsFără avertismente★ 5,4 K↓ —
- replica-reconJakeschincariol/replica-skillReverse-engineers any app into a recon map: screen inventory, user flows, component list, inferred data model and a feature matrix, from public pages, screenshots, app store listings, help docs and the user's own account. The first step of the Replica pack. Use when the user says "clone this app", "reverse engineer X", "how does X work", "map out X", "what screens does X have", "I want to build my own version of X", "copy this app", or pastes an app's URL or App Store link and wants to rebuild it.AlteleFără avertismente★ 5,4 K↓ —
- dowhybrycewang-stanford/Auto-Empirical-Research-SkillsCausal inference framework for answering "does X cause Y?" beyond correlation. DoWhy (Microsoft Research) provides the identify-estimate-refute loop: define a causal graph (DAG), identify the causal effect using backdoor/frontdoor/instrumental variable criteria, estimate treatment effects with multiple estimators, and validate results with automated refutation tests. Use when: distinguishing causation from correlation, estimating treatment effects (ATE, ATT, CATE), designing and analyzing A/B tests with confounders, using instrumental variables, performing counterfactual reasoning ("what would have happened if..."), validating causal claims with sensitivity analysis, working with observational data where randomization is impossible, or any analysis where the question is "what is the CAUSAL effect of X on Y" rather than just "how do X and Y relate?"TestareFără avertismente★ 4,8 K↓ —
- replica-architectJakeschincariol/replica-skillPlans the stack, database schema and API for an app clone, from the recon map replica-recon wrote. Picks boring, managed tech, turns the inferred data model into real SQL with indexes and access rules, lists every route by flow, and orders the build as a thin vertical slice first. Use when the user says "plan the clone", "what stack should I use", "design the database", "write the schema", "plan the API", "architecture for my version of X", or after /replica-recon finishes.PlanificareFără avertismente★ 5,4 K↓ —
- sn-team-harnessOpenSenseNova/SenseNova-SkillsUse when a user asks what SenseNova Team Harness is, wants an introduction or overview, is getting started, or is deciding whether it fits — a self-hosted workspace where people and local AI agents collaborate on conversations, projects, work items, and artifacts. Covers its core concepts (Workspace, Project, Conversation, Agent, WorkItem, Resource, Artifact, Local Computer), main capabilities, how to run it, and the basic usage flow.AlteleFără avertismente★ 5,9 K↓ —
ml-ai
grafana/skills
OficialDevOpsActualizat acum 15 ore
De la autor
Turn on AI + ML features in Grafana Cloud — Grafana Assistant (NL → PromQL/LogQL/TraceQL, dashboard build, incident investigation, MCP integration), Dynamic Alerting (Prophet forecasting + DBSCAN outlier detection), Sift (8-analysis automated root-cause), Knowledge Graph + RCA Workbench, and the LLM Plugin (OpenAI / Anthropic / Azure / Ollama / vLLM / LiteLLM). Use when you want anomaly alerts without static thresholds, natural-language querying, automated incident investigation, dashboards generated from a sentence, or a managed LLM proxy for plugins — even when the user says "alert when something looks weird", "explain this PromQL", "find the root cause", "make this a dashboard", or "wire Claude into Grafana" without naming any of these products.
Instalare
npx skills add grafana/skills --skill ml-ai -a claude-code
Se instalează în .claude/skills/ml-ai/ · Fiecare comandă descarcă skill-ul direct de pe GitHub cu utilitarul open source skills.
Descarcă .zip
Identic octet cu octet cu commit-ul scanat, cu licența depozitului și un fișier SOURCE.txt.
La ce are acces
Doar instrucțiuniFolosește rețeauaLicență: APACHE-2.0
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De ce 91
Securitate100
Proveniență100
Întreținere100
Licență100
Adopție41
Fișiere (3)
- SKILL.md
- references/llm-and-graph.md
- references/sift.md