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 10 ore
45.604 skill-uri
- dynamic-large-file-parquet-analysisOpenSenseNova/SenseNova-Skills动态统计Excel总行数,当数据量过大(≥10000行)时自动转换为Parquet格式加速读取,并对指定目标列进行条件筛选、分类汇总与结果导出,适用于超大体积Excel文件的快速读取与统计分析。DocumenteFără avertismente★ 5,9 K↓ —
- lambda-labs-gpu-cloudOrchestra-Research/AI-Research-SKILLsReserved and on-demand GPU cloud instances for ML training and inference. Use when you need dedicated GPU instances with simple SSH access, persistent filesystems, or high-performance multi-node clusters for large-scale training.AlteleFără avertismente★ 13,9 K↓ —
- sentencepieceOrchestra-Research/AI-Research-SKILLsLanguage-independent tokenizer treating text as raw Unicode. Supports BPE and Unigram algorithms. Fast (50k sentences/sec), lightweight (6MB memory), deterministic vocabulary. Used by T5, ALBERT, XLNet, mBART. Train on raw text without pre-tokenization. Use when you need multilingual support, CJK languages, or reproducible tokenization.ProductivitateFără avertismente★ 13,9 K↓ —
- multi-sheet-reading-and-analysisOpenSenseNova/SenseNova-Skills用于读取多工作表Excel文件,动态评估数据量以启用Parquet大文件优化,并执行正则清洗、分类汇总、线性拟合及生成带格式的图表与结果文件。DocumenteFără avertismente★ 5,9 K↓ —
- multi-file-excel-parquet-analysisOpenSenseNova/SenseNova-Skills读取多 Sheet Excel 文件并统计规模,支持大文件向 Parquet 格式转换、分类数据统计及可视化报告生成。DocumenteFără avertismente★ 5,9 K↓ —
- excel-bar-chart-visualizationOpenSenseNova/SenseNova-Skills读取多工作表Excel文件,自动处理合并单元格与数据清洗,进行交叉分组统计并生成带总计行的结果表,最后绘制支持中英文字体的美化柱状图,适用于多维度数据汇总与可视化分析。DocumenteFără avertismente★ 5,9 K↓ —
- openrlhf-trainingOrchestra-Research/AI-Research-SKILLsHigh-performance RLHF framework with Ray+vLLM acceleration. Use for PPO, GRPO, RLOO, DPO training of large models (7B-70B+). Built on Ray, vLLM, ZeRO-3. 2× faster than DeepSpeedChat with distributed architecture and GPU resource sharing.PlanificareFără avertismente★ 13,9 K↓ —
- whisperOrchestra-Research/AI-Research-SKILLsOpenAI's general-purpose speech recognition model. Supports 99 languages, transcription, translation to English, and language identification. Six model sizes from tiny (39M params) to large (1550M params). Use for speech-to-text, podcast transcription, or multilingual audio processing. Best for robust, multilingual ASR.MediaFără avertismente★ 13,9 K↓ —
- excel-multi-sheet-dynamic-analysisOpenSenseNova/SenseNova-Skills用于分析包含多个Sheet的Excel文件,动态判断数据量级以决定是否转换为Parquet进行大文件处理,并支持跨Sheet的特定字段统计、数据清洗、交叉分析与可视化,最终生成带下载链接的汇总报告。DocumenteFără avertismente★ 5,9 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↓ —
- 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↓ —
- competitor-gapRyze-AI-Adgent/open-seo-mcp-skillsFind keywords a competitor ranks for that the user's site doesn't — the content gap, prioritized by volume and winnability. Use when asked "what does competitor.com rank for", "keyword gap vs X", "steal competitor keywords", or "why do they outrank us".AlteleFără avertismente★ 7,1 K↓ —
- brand-guidelinescomposio-community/awesome-codex-skillsApplies OpenAI's brand colors and typography to any artifact that should match the Codex/OpenAI look-and-feel. Use it when brand colors or style guidelines, visual formatting, or company design standards apply.DesignFără avertismente★ 17 K↓ —
- create-plancomposio-community/awesome-codex-skillsCreate a concise plan. Use when a user explicitly asks for a plan related to a coding task.PlanificareFără avertismente★ 17 K↓ —
- melonjs-particles-and-trailsActualizatmelonjs/melonJSUse this skill for particle effects and motion trails in melonJS — ParticleEmitter configuration, burst versus stream emission, the referenceSpace frame of reference introduced in 20.2, 3D particle motion through elevation and minSpread/maxSpread in 20.8, and the Trail renderable. Covers the emitter that silently does nothing until you call an emit method. Triggers on: Trail3d, ribbon, exhaust trail, speed streak, ski track, tyre mark, ribbonNormal, ParticleEmitter, particles, burstParticles, streamParticles, referenceSpace, ParticleEmitterSettings, elevation, minSpread, maxSpread, spawn area, Trail, explosion, smoke, sparks, debris, ring, exhaust, emitter, tintOverLife, colour over life, color over life, flame, fire.MediaFără avertismente★ 6,4 K↓ —
- paperjsxcomposio-community/awesome-codex-skillsGenerate PPTX presentations, DOCX documents, XLSX spreadsheets, and PDF reports from structured JSON input using PaperJSX.DocumenteFără avertismente★ 17 K↓ —
- sn-report-format-discoveryOpenSenseNova/SenseNova-Skills用于用户希望推荐研究成品形式,或最终形式无法从需求中直接判断时。把需求解析为一个简短的 format 字符串,不创建格式文件或 schema。AlteleFără avertismente★ 5,9 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↓ —
- pdf-analysisOpenSenseNova/SenseNova-SkillsPDF 文档解析。自动区分文字型 PDF 与扫描型 PDF,覆盖:文本/表格提取、多页全量扫描、嵌入图表 caption、单位感知数值计算。DocumenteFără avertismente★ 5,9 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↓ —
- sn-da-non-spreadsheet-analysisOpenSenseNova/SenseNova-SkillsWord / PDF / PPT 文档解析与数据分析引擎。覆盖三类文件格式的全量提取、表格数值化、图表理解与跨文档汇总分析。**遇到以下任一情况就主动使用本 skill**:①用户上传或指定了 .docx / .doc / .pdf / .pptx / .ppt 文件并要求分析、提取或统计其中内容;②用户出现触发词:Word分析 / PDF解析 / PPT提取 / 文档分析 / 报告解析 / 幻灯片分析 / 发票提取 / 合同分析 / 文档统计 / 错别字 / 语病 / 字号检查 / 简历分析 / 多文档对比;③任务涉及从文档中提取表格、数值、图表、格式(颜色/高亮/字号)、组织架构、时间线等结构化信息。仅不用于:Excel/CSV 数据分析(使用 sn-da-excel-workflow)、纯图片分析(使用 sn-da-image-caption)。DateFără avertismente★ 5,9 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↓ —
- openfold3aipoch/open-scienceStructure 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.ȘtiințăFără avertismente★ 5,4 K↓ —
- deslopbrycewang-stanford/Auto-Empirical-Research-SkillsRemove AI writing patterns from prose. Use this skill when writing, drafting, editing, reviewing, or revising any text to eliminate predictable AI tells, slop, and formulaic patterns. Trigger this skill whenever the user asks to "deslop", "de-AI", "make it sound human," "remove AI patterns," "remove AI tropes," "clean up AI writing," fix "slop," "deslop" text, or review prose for authenticity. Also use when the user asks you to write or draft anything and wants it to sound natural rather than AI-generated. Common use cases include scientific writing (manuscripts, abstracts, cover letters, grant narratives, discussion sections, peer review responses), blog posts, newsletters, memos, reports, and any other substantial prose.ȘtiințăFără avertismente★ 4,8 K↓ —
grafana-scenes
grafana/skills
De la autor
Build Grafana plugin pages using the @grafana/scenes framework. Use when creating new scene pages, adding panels/visualizations, setting up drilldown navigation, defining variables, configuring query runners, building table/timeseries/stat panels, or extending SceneObjectBase for custom scene objects. Triggers on any work involving SceneApp, SceneAppPage, EmbeddedScene, SceneQueryRunner, SceneDataTransformer, PanelBuilders, SceneFlexLayout, QueryVariable, or drilldown/tab configuration in Grafana plugins.
Instalare
npx skills add grafana/skills --skill grafana-scenes -a claude-code
Se instalează în .claude/skills/grafana-scenes/ · Fiecare comandă descarcă skill-ul direct de pe GitHub cu utilitarul open source skills.
Identic octet cu octet cu commit-ul scanat, cu licența depozitului și un fișier SOURCE.txt.
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- SKILL.md