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
- webapp-testinganthropics/skillsToolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.OficialTestareFără avertismente★ 183,6 K↓ —Apare și în 8 alte depozite
- 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↓ —
- use-js-interopdotnet/skillsAdd, review, or fix JavaScript interop in Blazor components. USE FOR: calling JavaScript from Blazor, calling .NET from JavaScript, collocated .razor.js modules, IJSRuntime, IJSObjectReference lifecycle, DotNetObjectReference, ElementReference, timing rules for when JS is available, IAsyncDisposable disposal of JS references, server-side JS interop safety. DO NOT USE FOR: general Blazor component authoring without JS interop needs (use author-component), forms (use collect-user-input).InginerieFără avertismente★ 5,7 K↓ —
- vectorizationdotnet/skillsDesign, implement, optimize, and review SIMD code in .NET. USE FOR: vectorizing scalar loops with TensorPrimitives, Vector64/128/256/512, or platform hardware intrinsics; reviewing existing SIMD code, including the generic Vector type, for contract equivalence, tail handling, memory safety, portability, fallbacks, and measured performance. DO NOT USE FOR: performance work unrelated to SIMD or vectorization.DesignFără avertismente★ 5,7 K↓ —
- invalid-data-cleaningOpenSenseNova/SenseNova-Skills用于大规模Excel数据的预处理,通过统计总行数判断是否转换为Parquet格式以提升读写效率,并使用正则表达式清洗指定文本列(如仅保留中文字符),最后导出清洗后的文件并提供下载链接。DocumenteFără avertismente★ 5,9 K↓ —
- microbenchmarkingdotnet/skillsActivate this skill when BenchmarkDotNet (BDN) is involved in the task — creating, running, configuring, or reviewing BDN benchmarks. Also activate when microbenchmarking .NET code would be useful and BenchmarkDotNet is the likely tool. Consider activating when answering a .NET performance question requires measurement and BenchmarkDotNet may be needed. Covers microbenchmark design, BDN configuration and project setup, how to run BDN microbenchmarks efficiently and effectively, and using BDN for side-by-side performance comparisons. Do NOT use for profiling/tracing .NET code (dotnet-trace, PerfView), production telemetry, or load/stress testing (Crank, k6).TestareFără avertismente★ 5,7 K↓ —
- category-statisticsOpenSenseNova/SenseNova-Skills提取指定类别列并统计各类别数量与占比,生成高分辨率的柱状图、饼图等组合可视化报告,适用于分类数据的分布情况分析。AlteleFără avertismente★ 5,9 K↓ —
- condition-filtering-and-large-file-optimizationOpenSenseNova/SenseNova-Skills根据数据规模动态选择处理策略。AlteleFără avertismente★ 5,9 K↓ —
- designlang-tokensManavarya09/design-extractUse when styling UI for v0.dev — references the extracted design system tokens instead of inventing colors, spacing, or typography.DesignFără avertismente★ 4,4 K↓ —
- code-testing-agentdotnet/skillsLegacy compatibility alias for the code-testing skill. Do not self-activate for user requests and do not treat this name as a custom agent. When invoked explicitly by older instructions, load code-testing and follow it instead.TestareFără avertismente★ 5,7 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↓ —
- indication-dossieraipoch/open-scienceGenerate a therapeutic indication dossier. Covers the patient population, epidemiology, disease biology, standard of care, regulatory precedent, and landmark clinical trials.ȘtiințăFără avertismente★ 5,4 K↓ —
- designlang-tokensManavarya09/design-extractUse when styling UI for raycast.com — references the extracted design system tokens instead of inventing colors, spacing, or typography.DesignFără avertismente★ 4,4 K↓ —
- excel-threshold-analysis-and-stylingOpenSenseNova/SenseNova-Skills根据 Excel 数据量级自动判断处理策略,执行数值列清洗、条件过滤,并使用 openpyxl 对符合条件的单元格进行样式标记与导出。DocumenteFără avertismente★ 5,9 K↓ —
- esmfold2aipoch/open-scienceBiohub ESMFold2 / ESMFold2-Fast all-atom co-folding (Candido et al. 2026, github.com/Biohub/esm). Single-sequence and MSA modes; protein, DNA, RNA, ligand (CCD/SMILES), modified residues. FoldBench Ab-Ag 50-55%, PPI 70-77% DockQ-pass. Also covers the ESMC-{300M,600M,6B} protein language models from the same release: masked-LM logits, hidden states, mutation scoring, contact prediction, and the SAE interpretability head. MIT-licensed weights on HuggingFace org `biohub`. Use this skill when: (1) Predicting complex structures with single-sequence input, (2) Validating designed binders with ESMFold2-Fast, (3) Running ESMFold2 with MSA input, (4) Getting ESMC embeddings or per-residue mutation scores, (5) Choosing kernel backend and sampling-step settings for paper-faithful throughput.ȘtiințăFără avertismente★ 5,4 K↓ —
- 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↓ —
- 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↓ —
- diffdockaipoch/open-sciencePredict small-molecule binding poses with DiffDock-L (Corso et al. 2023/2024, github.com/gcorso/DiffDock) — blind diffusion docking that places a ligand into a protein pocket without a predefined search box and ranks the samples with a learned confidence model. Reach for this skill to dock a SMILES or SDF against a PDB, to generate ranked 3D poses for a small fragment library, or to get a starting pose for downstream rescoring. DiffDock predicts geometry, not affinity.ȘtiințăFără avertismente★ 5,4 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↓ —
- mirrord-chaosmetalbear-co/mirrordHelp users chaos test their app with mirrord: inject artificial latency or connection errors into a mirrord session's outgoing traffic via per-session chaos rules managed with the `mirrord chaos` CLI. Use when a user wants to add latency or delay to outgoing connections or a dependency (e.g. a slow database), simulate connection failures (reset, timed out, refused), test app behavior under degraded network conditions, or wire chaos rules into CI test runs. Always use this skill instead of the deprecated _experimental_.latency mirrord config option.TestareFără avertismente★ 5,4 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↓ —
- proteinmpnnaipoch/open-scienceInverse-fold a protein backbone (PDB structure) into amino-acid sequence with ProteinMPNN (Dauparas et al. 2022, github.com/dauparas/ProteinMPNN). Reach for this skill to run sequence design on RFdiffusion backbones, to redesign one chain of a PDB while holding interface residues fixed, or to generate a temperature-swept set of sequences for downstream folding.DesignFără avertismente★ 5,4 K↓ —
- time-series-and-categorical-analysisOpenSenseNova/SenseNova-Skills对时间序列或分类数据进行多维度趋势分析、百分比清洗、绩效分级建模与预测,并生成高分辨率的可视化综合报告,适用于业务指标监控与预测场景。AlteleFără avertismente★ 5,9 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↓ —
designlang-tokens
Manavarya09/design-extract
De la autor
Use when styling UI for sentry.io — references the extracted design system tokens instead of inventing colors, spacing, or typography.
Instalare
npx skills add Manavarya09/design-extract --skill designlang-tokens -a claude-code
Se instalează în .claude/skills/designlang-tokens/ · 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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