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 11 ore
44.573 de skill-uri
- vercel-react-best-practiceszebbern/claude-code-guideReact and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.InginerieFără avertismente★ 4,7 K↓ —
- pivot-table-cross-analysisOpenSenseNova/SenseNova-Skills利用交叉表与热力图对分类数据进行多维度占比分析，适用于奖项分布、绩效评估或市场占有率等结构化数据的清洗与可视化。AlteleFără avertismente★ 5,9 K↓ —
- playwright-skillzebbern/claude-code-guideBattle-tested Playwright patterns for E2E, API, component, visual, accessibility, and security testing. Covers locators, fixtures, POM, network mocking, auth flows, debugging, CI/CD (GitHub Actions, GitLab, CircleCI, Azure, Jenkins), framework recipes (React, Next.js, Vue, Angular), and migration guides from Cypress/Selenium. TypeScript and JavaScript.TestareFără avertismente★ 4,7 K↓ —
- melonjs-3dmelonjs/melonJSUse this skill for anything 3D or 2.5D in melonJS — Camera3d, Mesh, InstancedMesh, Sprite3d billboards, Light3d, ground shadows, glTF/GLB scenes, and depth sorting. Covers the Y-down/+Z-forward convention that is the inverse of OpenGL, the cameraClass opt-in, clip planes, and what does not work on the Canvas fallback. Triggers on: Camera3d, Mesh, InstancedMesh, Sprite3d, Trail3d, ribbon, exhaust trail, Light3d, billboard, glTF, glb, 3D, 2.5D, depth, cameraClass, fov, setClipPlanes, setFog, fog, distance fog, height fog, heightFalloff, transparent, transparency, alpha, blendMode, fade, castGroundShadow, lit, setBasis, getBasis, lookAt, up vector, gimbal, slerp, great circle, turn a direction.PlanificareFără avertismente★ 6,4 K↓ —
- create-custom-agentdotnet/skillsCreates VS Code custom agent files (.agent.md) for specialized AI personas with tools, instructions, and handoffs. Use when scaffolding new custom agents, configuring agent workflows, or setting up agent-to-agent handoffs.PlanificareFără avertismente★ 5,7 K↓ —
- linkedin-post-writersergebulaev/linkedin-skillsDraft a new LinkedIn post from scratch using one of 20 2026 hook formulas (anaphora, R.I.P., time-anchor, curiosity-gap, contrarian, controlled A/B, false-binary, and more) plus a founders-edition angle library, picked by engagement goal (comments, reposts, likes, saves). Runs the humanizer pass and schedules via Publora on approval. Use to write a post, find a hook or proven format, or get founder-specific angles. Not for reviewing existing drafts (use linkedin-humanizer --mode audit).MarketingFără avertismente★ 5,2 K↓ —Apare și în 1 alt depozit
- sql-injection-testingzebbern/claude-code-guideThis skill should be used when the user asks to "test for SQL injection vulnerabilities", "perform SQLi attacks", "bypass authentication using SQL injection", "extract database information through injection", "detect SQL injection flaws", or "exploit database query vulnerabilities". It provides comprehensive techniques for identifying, exploiting, and understanding SQL injection attack vectors across different database systems.TestareFără avertismente★ 4,7 K↓ —
- cachingzebbern/claude-code-guideCaching strategies — invalidation, TTL guidelines, cache keys, cache layers, and when not to cache. Use when implementing or reviewing caching logic.AlteleFără avertismente★ 4,7 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↓ —
- 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↓ —
- agentic-workflowsdotnet/skillsRoute gh-aw workflow design/create/debug/upgrade requests to the right prompts.DesignFără avertismente★ 5,7 K↓ —
- 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↓ —
- designlang-tokensManavarya09/design-extractUse when styling UI for posthog.com — references the extracted design system tokens instead of inventing colors, spacing, or typography.DesignFără avertismente★ 4,4 K↓ —
- word-analysisOpenSenseNova/SenseNova-SkillsWord (.docx/.doc) 文档全量解析。覆盖：正文/段落文本提取、表格数据提取、高亮/颜色格式读取、多文件汇总对比、嵌入图片转 caption。DocumenteFără avertismente★ 5,9 K↓ —
- range-reading-and-large-file-analysisOpenSenseNova/SenseNova-Skills读取多 Sheet Excel 文件，根据数据量动态选择处理策略，支持特定区域数据提取、大文件 Parquet 转换、统计分析及可视化图表生成。DocumenteFără avertismente★ 5,9 K↓ —
- excel-conditional-filtering-optimizationOpenSenseNova/SenseNova-Skills根据多维数值条件筛选 Excel 数据并导出结果，支持大规模数据的自动性能优化处理。DocumenteFără avertismente★ 5,9 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↓ —
- excel-outlier-detection-and-highlightingOpenSenseNova/SenseNova-Skills识别 Excel 中的超限数值与错误单元格并进行高亮标注。DocumenteFără avertismente★ 5,9 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↓ —
- 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↓ —
- designlang-tokensManavarya09/design-extractUse when styling UI for perplexity.ai — references the extracted design system tokens instead of inventing colors, spacing, or typography.DesignFără avertismente★ 4,4 K↓ —
- antislop-copywritingmiqdadbadjuber/anti-slopCopy and text skill for antislop. Use when writing or editing prose: headlines, tone, CTAs, and anti-AI-writing patterns. Load with the core.MarketingFără avertismente★ 7,1 K↓ —
- pie-chart-data-analysisOpenSenseNova/SenseNova-Skills对多Sheet Excel或CSV数据进行分类汇总统计，自动识别关键字段并生成包含占比、数值及美化饼图的可下载分析报告。DateFără 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↓ —
testing
grafana/skills
OficialTestareActualizat acum 14 ore
De la autor
Probe, load-test, and instrument frontends from Grafana Cloud. Covers Synthetic Monitoring (HTTP / DNS / TCP / Ping / Traceroute / Multihttp / k6-browser scripted checks from 20+ global probes, alert on `probe_success` + TLS-cert expiry), Grafana Cloud k6 (distributed load tests across AWS load-zones, scenarios, `http_req_duration` thresholds, CI integration via `grafana/k6-action`), and Frontend Observability with Faro Web SDK (RUM, Core Web Vitals, custom events, `pushError`, distributed-trace correlation). Use when checking website / API uptime from multiple regions, gating a release on a load test, watching for TLS-cert renewal, instrumenting a React/Vue app, tracking Core Web Vitals, or correlating frontend errors to backend traces — even when the user says "is my login flow up?", "monitor my API", "ping our endpoint every minute", "release-gate load test", "browser performance monitoring", "session replay", or "RUM" without naming Synthetic Monitoring / k6 / Faro.
Instalare
npx skills add grafana/skills --skill testing -a claude-code
Se instalează în .claude/skills/testing/ · 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
Verificări de siguranță pe SKILL.md
Niciun avertisment.
De ce 91
Securitate100
Proveniență100
Întreținere100
Licență100
Adopție41
Fișiere (5)
- SKILL.md
- references/k6-and-faro.md
- references/k6-cloud.md
- references/synthetic-monitoring.md
- references/synthetic.md