Skill-uri pentru agenți pe care le poți verifica înainte să le instalezi
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 5 ore
45.604 skill-uri
- get-prompt-from-imagewuyoscar/GPT-Image2-SkillAnalyze user-provided reference images and reverse-engineer high-fidelity AI image-generation prompts. Use when the user asks to recreate, imitate, reverse-engineer, or extract prompts from photographs, illustrations, 3D renders, products, characters, landscapes, typography, logos, posters, or other visual references. Do not use for requests that only require OCR or an ordinary image description.MediaFără avertismente★ 5,9 K↓ —
- playwright-cizebbern/claude-code-guideProduction-ready CI/CD configurations for Playwright — GitHub Actions, GitLab CI, CircleCI, Azure DevOps, Jenkins, Docker, parallel sharding, reporting, code coverage, and global setup/teardown.TestareFără avertismente★ 4,7 K↓ —
- ppt-analysisOpenSenseNova/SenseNova-SkillsPPT (.pptx/.ppt) 全量解析。覆盖：所有 slide 文本/表格/图表提取、嵌入图片 caption、纯图片 slide 渲染识别、数据标签提取。DocumenteFără avertismente★ 5,9 K↓ —
- deepchat-sddThinkInAIXYZ/deepchatUse before substantial DeepChat code, configuration, documentation, test, build, feature, issue, refactor, or architecture changes that need a durable RFC and an explicit execution path. Skip trivial style fixes, small localized logic changes, routine docs edits, and simple bugs unless the developer asks for SDD. Use plan.md as the only separate tracker when needed, default to implementation-first validation, and ask before optional GitHub issue sync unless the developer explicitly requested sync.TestareFără avertismente★ 6,4 K↓ —
- sn-da-large-file-analysisOpenSenseNova/SenseNova-Skills万行以上 Excel 数据集的高性能分析引擎。提供 openpyxl read_only 流式读取（iter_rows 支持 10 万行以上）、Parquet 转换加速、内存优化、分块处理和大文件写入模式。**遇到以下任一情况就主动使用本 skill**：①数据行数 ≥ 10k（由 sn-da-excel-workflow 的行数评估步骤触发）；②用户出现触发词：大文件 / 大数据量 / 性能优化 / 内存不足 / OOM / 百万行 / 十万行 / 流式读取 / Parquet / 分块处理 / large file / big data / streaming read / chunked processing；③直接使用 pd.read_excel() 导致超时或内存溢出；④用户明确要求对大规模数据集进行高性能处理。仅不用于：小于 10k 行的常规 Excel 分析（使用 sn-da-excel-workflow 即可）。DocumenteFără avertismente★ 5,9 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↓ —
- slr-prismabrycewang-stanford/Auto-Empirical-Research-SkillsGuide users through writing a systematic literature review (SLR) following the PRISMA 2020 framework. Use this skill whenever the user mentions 'systematic review', 'systematic literature review', 'SLR', 'PRISMA', 'PRISMA 2020', 'PRISMA flow diagram', 'PRISMA checklist', or asks for help writing, structuring, or auditing a literature review that follows reporting guidelines. Also trigger when the user asks about inclusion/exclusion criteria for a review, search strategies for databases like Scopus/WoS/PubMed, study selection processes, risk of bias assessment, or narrative synthesis for a review paper. This skill covers the full PRISMA 2020 checklist (27 items), produces a Word document manuscript in strict journal article format, generates an annotated PRISMA flow diagram, and enforces APA 7th Edition referencing throughout. It does NOT cover meta-analysis or statistical pooling. By Chuah Kee Man.DocumenteFără avertismente★ 4,8 K↓ —
- grouped-statisticsOpenSenseNova/SenseNova-Skills对多 Sheet 的 Excel 文件进行行数统计、数据合并与前向填充。DocumenteFără avertismente★ 5,9 K↓ —
- code-testingdotnet/skillsALWAYS USE for test work that requires changes: write, add, generate, repair, or strengthen tests for existing code in xUnit, MSTest, NUnit, pytest, Vitest/Jest, Go, or another framework. Includes regression cases, failing or flaky tests, coverage-driven additions, and audit-then-fix requests. Focused work stays direct; broad or multi-stage work invokes test-engineer. DO NOT USE for only running tests, analysis-only audits, framework/platform migrations, a test blocked on a missing production seam (testability-obstacle), or MSTest API/configuration corrections that do not design new cases (writing-mstest-tests). Within an active test-engineer pipeline, reuse supplied guidance and do not re-enter this skill.TestareFără avertismente★ 5,7 K↓ —
- code-testing-extensionsdotnet/skillsProvides file paths to language-specific extension files for the code-testing pipeline. Read this reference-only catalog for extension guidance files (e.g., dotnet.md for .NET, cpp.md for C++). Agents and skills read its bundled files directly; do not invoke this catalog through the model's skill tool.TestareFără avertismente★ 5,7 K↓ —
- create-skill-testdotnet/skillsScaffolds eval.yaml evaluation specs for skills, custom agents, and redistributable gh-aw workflow packages in the dotnet/skills repository. Use when creating skill or workflow-package tests, writing evaluation stimuli, defining graders and rubrics, sizing an eval for statistical power, or setting up test fixture files. Handles the Vally eval.yaml schema, fixture organization, and overfitting avoidance. Do not use for running or debugging existing evals (use improve-skill-quality) nor for skills authoring (use create-skill).TestareFără avertismente★ 5,7 K↓ —
- seo-vs-adsRyze-AI-Adgent/open-seo-mcp-skillsFind money leaking between search ads and SEO — queries you pay for while already ranking organically, and paid queries with no organic coverage. Use when asked "am I paying for clicks I'd get free", "brand bidding waste", "SEO vs ads overlap", or "cut wasted ad spend with SEO".MarketingFără avertismente★ 7,1 K↓ —
- create-skilldotnet/skillsScaffolds new agent skills for the dotnet/skills repository. Use when creating a new skill, generating SKILL.md files, writing a skill description that the runtime will actually route to, or setting up skill directory structures. Handles frontmatter generation, section templates, and validation guidance. Do not use for fixing a skill that already fails its evaluation (use improve-skill-quality) or for writing eval.yaml (use create-skill-test).TestareFără avertismente★ 5,7 K↓ —
- statistical-distribution-and-outlier-analysisOpenSenseNova/SenseNova-Skills执行数值型数据的分布分析与异常值检测，支持通过正则表达式从文本中提取误差项并生成高分辨率的箱线图与直方图报告。AlteleFără avertismente★ 5,9 K↓ —
- nitroantfu/skillsNitro is the framework-agnostic server toolkit (powering Nuxt) for building and deploying web servers anywhere. Use when working with nitro.config, server routes/event handlers, route rules, caching, storage, tasks, websockets, or deploying to Node/Bun/Deno/Cloudflare/Vercel.DevOpsFără avertismente★ 6 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↓ —
- technology-selectiondotnet/skillsGuides technology selection and implementation of AI and ML features in .NET 8+ applications using ML.NET, Microsoft.Extensions.AI (MEAI), Microsoft Agent Framework (MAF), GitHub Copilot SDK, ONNX Runtime, and OllamaSharp. Covers the full spectrum from classic ML through modern LLM orchestration to local inference. Use when adding classification, regression, clustering, anomaly detection, recommendation, LLM integration (text generation, summarization, reasoning), RAG pipelines with vector search, agentic workflows with tool calling, Copilot extensions, or custom model inference via ONNX Runtime to a .NET project. DO NOT USE FOR projects targeting .NET Framework (requires .NET 8+), the task is pure data engineering or ETL with no ML/AI component, or the project needs a custom deep learning training loop (use Python with PyTorch/TensorFlow, then export to ONNX for .NET inference).DateFără avertismente★ 5,7 K↓ —
- fetch-and-send-datadotnet/skillsCall APIs, load data into components, and handle the async lifecycle in Blazor. USE FOR fetching data from a backend, submitting data to an API, displaying loading/error states, registering HttpClient, building service abstractions for Auto/WebAssembly render modes. DO NOT USE for form validation (see collect-user-input), prerendering persistence (see support-prerendering), or project scaffolding (see create-blazor-project).MediaFără avertismente★ 5,7 K↓ —
- hunt-miscelementalsouls/Claude-BugHunterHunting skill for misc vulnerabilities. Built from 225 public bug bounty reports. Use when hunting misc on any target.SecuritateFără avertismente★ 5,3 K↓ —
- marginaleffectsbrycewang-stanford/Auto-Empirical-Research-SkillsManual for the marginaleffects R and Python package, and guide to the book "Model to Meaning". Use when users ask about predictions, comparisons, slopes, marginal effects, average treatment effects (ATE/ATT/CATE), hypothesis testing, contrasts, counterfactuals, risk ratios, odds ratios, causal inference with G-computation, or need help with marginaleffects functions like predictions(), comparisons(), slopes(), hypotheses(), datagrid(), avg_predictions(), avg_comparisons(), avg_slopes(), or plot functions.TestareFără avertismente★ 4,8 K↓ —
- stacked-chart-visualizationOpenSenseNova/SenseNova-Skills处理包含百分比字符串的分类占比数据，通过补全缺失维度并生成堆叠柱状图，直观展示多维度构成随时间或分类的变化趋势。AlteleFără avertismente★ 5,9 K↓ —
- mirrord-configmetalbear-co/mirrordHelps users generate, edit, and validate mirrord.json configuration files for mirrord (MetalBear). Use when the user wants to connect their local process to a Kubernetes environment, configure features (env/fs/network), or needs feedback on an existing mirrord.json. Always ensures output JSON is valid and schema-conformant.DevOpsFără avertismente★ 5,4 K↓ —
- antfuantfu/skillsAnthony Fu's opinionated tooling and conventions for JavaScript/TypeScript projects. Use when setting up new projects, configuring ESLint/Prettier alternatives, monorepos, library publishing, or when the user mentions Anthony Fu's preferences.InginerieFără avertismente★ 6 K↓ —
- melonjs-tilemapsActualizatmelonjs/melonJSUse this skill for Tiled maps in melonJS — loading TMX/TSX levels, spawning entities from Tiled objects, collision shapes authored in Tiled, isometric and hexagonal maps, and image layers. Covers registerTiledObjectClass and the pool.register name contract, camera bounds, compressed maps needing the inflate plugin, and the level director API. Triggers on: Tiled, TMX, TSX, tilemap, level.load, level.load async, await level.load, tileset, ImageLayer, isometric, hexagonal, staggered, pool.register, Collectable, Trigger, object layer, collision layer, parallax, registerTiledObjectClass, registerTiledObjectFactory, TMXObject, resolvedProperty, resolvedProperties, tile class, tile properties.MediaFără avertismente★ 6,4 K↓ —
melonjs-camera-and-drawing
melonjs/melonJS
ActualizatMediaActualizat acum 6 ore
De la autor
Use this skill for camera control and immediate-mode drawing in melonJS — following a target, viewport bounds, shake and fade, secondary cameras and what each one draws, and drawing shapes, lines and gradients inside a custom draw(). Covers world versus screen coordinate conversion, clipping and masking, baking with CanvasRenderTarget, and reading pixels back. Triggers on: Camera2d, viewport, follow, setBounds, minimap, second camera, split screen, cullMask, visibilityLayer, hide from a camera, shake, fadeIn, fadeOut, worldToLocal, localToWorld, colorMatrix, renderer.fill, renderer.stroke, Rect, Ellipse, Polygon, Line, Gradient, clipRect, mask, CanvasRenderTarget, NoiseTexture2d, lookAt, setBasis, toImageData, getImageData, toBlob, toDataURL, screenshot, read pixels.
Instalare
npx skills add melonjs/melonJS --skill melonjs-camera-and-drawing -a claude-code
Se instalează în .claude/skills/melonjs-camera-and-drawing/ · 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 instrucțiuniNu am văzut acces la rețeaLicență: MIT
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De ce 91
Securitate100
Proveniență86
Întreținere100
Licență100
Adopție60
Fișiere (1)
- SKILL.md