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.
39.866 de skill-uri din 1.828 de depozite · actualizat acum 11 minute
39.236 de skill-uri
- antislop-layoutmobilemiqdadbadjuber/anti-slopMobile layout skill for antislop. Use for layouts that reflow across screen sizes, phone to desktop: grids, overflow, tap targets. Load with the core.AlteleFără avertismente★ 7 K↓ —
- grade-testsdotnet/skillsGrade curated individual tests for readiness, A-F quality and improvements. ALWAYS USE FOR: grade tests, review only a named test, per-test readiness or quality bands for supplied methods, bodies, file spans or bounded PR diffs, including existing tests. Return Pass/Failed/Uncertain/Not applicable; unresolved/empty scopes omit grades. Compose read-only per-test evidence. Polyglot. DO NOT USE FOR: suite audits (test-engineer/test-anti-patterns), concrete fix/feature detection proof (test-value-evidence), writing/fixing tests, or coverage.TestareFără avertismente★ 5,7 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↓ —
- 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↓ —
- large-file-kpi-analysisOpenSenseNova/SenseNova-Skills根据数据量自动选择读取策略（大文件转Parquet），提取关键指标进行单位一致性验证与排序分析，并输出可下载的结果表格。AlteleFără avertismente★ 5,9 K↓ —
- text-normalization-and-large-file-processingOpenSenseNova/SenseNova-Skills对Excel文件进行文本标准化清洗（如去除异常前缀、提取纯中文字符等），并，最终输出清洗后的Excel文件并提供下载链接。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↓ —
- excel-large-file-processing-and-cleaningOpenSenseNova/SenseNova-Skills读取多 sheet Excel 文件，动态识别目标列进行统计，并使用正则清洗文本字段提取中文字符，最终输出标准化 Excel 文件。DocumenteFără avertismente★ 5,9 K↓ —
- dump-collectdotnet/skillsConfigure and collect crash dumps for modern .NET applications. USE FOR: enabling automatic crash dumps for CoreCLR or NativeAOT, capturing dumps from running .NET processes, setting up dump collection in Docker or Kubernetes, using dotnet-dump collect or createdump. DO NOT USE FOR: analyzing or debugging dumps, post-mortem investigation with lldb/windbg/dotnet-dump analyze, profiling or tracing, or for .NET Framework processes.DevOpsFără avertismente★ 5,7 K↓ —
- 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↓ —
- 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↓ —
- memory-managementThinkInAIXYZ/deepchatGuide the agent to recall, remember, and route durable learning into Memory, Skills, Scheduled Tasks, or Tape.ProductivitateFără avertismente★ 6,4 K↓ —
- customizeaipoch/open-scienceUse 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.PlanificareFără avertismente★ 5,4 K↓ —
- uitw93/WazaProduces distinctive production UI and screenshot-grounded visual polish. Use when building or restyling pages, components, or typography. Not for backend logic or data pipelines.DesignFără avertismente★ 7,4 K↓ —Apare și în 1 alt depozit
- fair-esm2aipoch/open-scienceEmbed proteins with Meta AI's ESM-2 (`fair-esm` package). Use this skill when: (1) Extracting per-residue or per-sequence embeddings for downstream ML, (2) Masked-LM likelihood / mutation effect scoring, (3) Contact prediction from a sequence.AlteleFără avertismente★ 5,4 K↓ —
- redteam-mindsetelementalsouls/Claude-BugHunterRed-team operator discipline — the mindset corrections that separate offensive testing from defensive WAPT. Built from authorized red-team work where conservative defaults caused multiple findings to be missed and one to be incorrectly retracted. Use at the START of any red-team engagement and again whenever feeling stuck or considering "stopping" on a defended target. The single most important skill to load when scope is "external red team" not "bug bounty / WAPT".TestareFără avertismente★ 5,3 K↓ —
- solublempnnaipoch/open-scienceInverse-fold a backbone with SolubleMPNN — ProteinMPNN retrained on a soluble-PDB subset (Dauparas et al. 2022) — for sequences biased toward cytosolic expression and reduced aggregation. Reach for this skill when designs from vanilla ProteinMPNN are aggregating or going to inclusion bodies, when redesigning a membrane-adjacent fold for soluble expression, or when an E. coli expression screen is the next step.AlteleFără avertismente★ 5,4 K↓ —
- deepspeedOrchestra-Research/AI-Research-SKILLsExpert guidance for distributed training with DeepSpeed - ZeRO optimization stages, pipeline parallelism, FP16/BF16/FP8, 1-bit Adam, sparse attentionAlteleFără avertismente★ 13,9 K↓ —
- designlang-tokensManavarya09/design-extractUse when styling UI for retool.com — references the extracted design system tokens instead of inventing colors, spacing, or typography.DesignFără avertismente★ 4,4 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↓ —
- designlang-tokensManavarya09/design-extractUse when styling UI for resend.com — references the extracted design system tokens instead of inventing colors, spacing, or typography.DesignFără avertismente★ 4,4 K↓ —
- linkedin-reply-handlersergebulaev/linkedin-skillsDraft a reply to one LinkedIn comment from its URL, or sweep a whole thread from just the post URL and draft a reply to every comment worth answering, in one batch. Use for replying to a comment, following an author reply, or clearing all comments on a post. Resolves the correct parentComment (LinkedIn flattens threads to 2 levels), filters low-value comments before a sweep, and posts via Publora on approval. Not for top-level comments (use linkedin-comment-drafter).MarketingFără avertismente★ 5,1 K↓ —Apare și în 1 alt depozit
- 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↓ —
- designlang-tokensManavarya09/design-extractUse when styling UI for loom.com — references the extracted design system tokens instead of inventing colors, spacing, or typography.DesignFără avertismente★ 4,4 K↓ —
vercel-composition-patterns
zebbern/claude-code-guide
MediaActualizat ieri
De la autor
React composition patterns that scale. Use when refactoring components with boolean prop proliferation, building flexible component libraries, or designing reusable APIs. Triggers on tasks involving compound components, render props, context providers, or component architecture. Includes React 19 API changes.
Instalare
npx skills add zebbern/claude-code-guide --skill vercel-composition-patterns -a claude-code
Se instalează în .claude/skills/vercel-composition-patterns/ · 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
Verificări de siguranță pe SKILL.md
Niciun avertisment.
De ce 91
Securitate100
Proveniență84
Întreținere100
Licență100
Adopție58
Fișiere (14)
- AGENTS.md
- README.md
- SKILL.md
- metadata.json
- rules/_sections.md
- rules/_template.md
- rules/architecture-avoid-boolean-props.md
- rules/architecture-compound-components.md
- rules/patterns-children-over-render-props.md
- rules/patterns-explicit-variants.md
- rules/react19-no-forwardref.md
- rules/state-context-interface.md
- încă 2