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 6 ore
45.604 skill-uri
- cloud-integrationsgrafana/skillsSet up, configure, and troubleshoot Grafana Cloud integrations for AWS, Azure, and other cloud providers. Use when the user asks to connect AWS CloudWatch, set up Azure Monitor, configure Confluent Cloud observability, install a Grafana integration, set up hosted exporters, use AWS Firehose for CloudWatch logs, or troubleshoot a cloud integration. Triggers on phrases like "AWS CloudWatch", "Azure Monitor", "Confluent integration", "cloud integration", "hosted exporter", "AWS Firehose", "install integration", "cloud metrics", or "cloud logs".OficialDevOpsFără avertismente★ 290↓ —
- skill-authoringgrafana/skillsAuthor, audit, and improve Grafana SKILL.md files against Anthropic's published Agent Skills guidance and the four-dimension rubric the grafana/skills CI gate uses (conciseness, actionability, workflow clarity, progressive disclosure). Applies the canonical SKILL.md structure (YAML frontmatter + body + references/ + scripts/ + assets/), the "pushy description" trigger pattern, the three-level progressive-disclosure model, and the validate-fix-rerun feedback loop. Use when creating a new skill in this repo, when reviewing a skill PR, when a skill's Tessl review score is below 75 (the merge gate), when a skill's description isn't getting picked up by agents, when restructuring a long SKILL.md into a bundle, or when the user asks how to write, improve, optimize, audit, or fix a skill - even if they don't say "skill" explicitly (e.g. "this isn't triggering", "Tessl scored this 72", "split this doc").OficialRedactareFără avertismente★ 290↓ —
- 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↓ —
- 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↓ —
- replica-reconJakeschincariol/replica-skillReverse-engineers any app into a recon map: screen inventory, user flows, component list, inferred data model and a feature matrix, from public pages, screenshots, app store listings, help docs and the user's own account. The first step of the Replica pack. Use when the user says "clone this app", "reverse engineer X", "how does X work", "map out X", "what screens does X have", "I want to build my own version of X", "copy this app", or pastes an app's URL or App Store link and wants to rebuild it.AlteleFără avertismente★ 5,4 K↓ —
- cost-managementgrafana/skillsCut your Grafana Cloud bill by attributing spend to teams and reducing telemetry volume. Covers FOCUS-compliant billing dashboards, cost-attribution labels in Alloy, Adaptive Metrics (cardinality reduction), Adaptive Logs (drop/sample), Adaptive Traces (tail sampling), usage alerts, and an optimization checklist. Use when investigating a high Grafana Cloud bill, attributing observability cost to a team or service, reducing active series / log bytes / trace spans, or setting up usage / quota alerts — even when the user says "our Grafana bill is too high", "who's burning the most metrics", "drop debug logs", "sample our traces", or "alert me before we hit quota" without naming Cost Management.OficialDevOpsFără avertismente★ 290↓ —
- 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↓ —
- chai1aipoch/open-scienceStructure prediction for protein, nucleic-acid, and small-molecule complexes with the Chai-1 foundation model (Chai Discovery 2024, github.com/chaidiscovery/chai-lab). Reach for this skill to predict an antibody-antigen or protein-ligand complex from a single FASTA, to re-fold designed binders as an AlphaFold-multimer alternative, or to drive co-folding from Python for batched campaigns on a GPU.ȘtiințăFără avertismente★ 5,4 K↓ —
- scgptaipoch/open-scienceEmbed and annotate single-cell expression data with scGPT, a foundation model for single-cell biology. Use this skill when: (1) Producing cell embeddings from an AnnData for clustering/integration, (2) Zero-shot or fine-tuned cell-type annotation, (3) Gene-level representation for perturbation/GRN tasks. For probabilistic single-cell models (scVI etc.), use the scvi-tools library.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↓ —
- line-chart-visualizationOpenSenseNova/SenseNova-Skills提取结构化数据并进行特征清洗与聚类分析，生成包含趋势对比、分布特征与参数敏感性的多维度综合可视化图表，适用于各类趋势预测与多维对比场景。AlteleFără avertismente★ 5,9 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↓ —
- 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↓ —
- 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↓ —
- app-sdk-conceptsgrafana/skillsUse when starting any grafana-app-sdk work — scaffolding a Grafana app, initializing a Grafana App Platform app, picking a deployment mode (standalone operator / grafana/apps / frontend-only), wiring app-specific config, or onboarding to the SDK. Covers `grafana-app-sdk` CLI install, `project init` per deployment mode, project layout, the schema-centric workflow (CUE kinds → generated code → reconciler/admission logic), and `SpecificConfig` for env-driven app configuration. Use even if the user just says "make a new app", "Grafana app platform", "kinds and watchers", "operator scaffold", or asks about `apps/` inside the Grafana repo, without naming the SDK explicitly.OficialDevOpsFără avertismente★ 290↓ —
- 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↓ —
- 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↓ —
- 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↓ —
- deepchat-data-importThinkInAIXYZ/deepchatHelp developers build third-party tools that import, inspect, migrate, or analyze DeepChat data. Use when Codex needs to work with DeepChat provider configuration, model configuration, MCP/app settings, sessions, messages, legacy chat data, `agent.db`, `chat.db`, SQLCipher encrypted SQLite, Electron safeStorage wrapped passwords, Tauri importers, or native macOS/Windows/Linux data access.AlteleFără avertismente★ 6,4 K↓ —
- code-documenterzebbern/claude-code-guideUse when adding docstrings, creating API documentation, or building documentation sites. Invoke for OpenAPI/Swagger specs, JSDoc, doc portals, tutorials, user guides.InginerieFără avertismente★ 4,7 K↓ —
- mirrord-header-propagationmetalbear-co/mirrordMakes a codebase propagate W3C baggage (the `baggage` header carrying `mirrord-session=<key>`) end to end, so mirrord HTTP filters, preview environments, and queue splitting can route a whole request chain to one developer's session. Detects existing OpenTelemetry, Datadog, or other tracing that can already propagate baggage and enables it; otherwise adds a small propagation layer. Covers inbound/outbound HTTP and gRPC, publishing to and consuming from Kafka, RabbitMQ, SQS/SNS, GCP Pub/Sub, Azure Service Bus, NATS, Redis Pub/Sub, BullMQ and Temporal, per-message context restore in consumers, and storage hand-offs such as a GCS signed URL upload that triggers Pub/Sub or an S3 presigned upload that triggers SQS. Ends with a report of every flow found and which ones still drop the header. Use when the user asks to propagate headers, baggage, tracestate, the mirrord session key, or trace context across services or queues, or when a mirrord filter matches the first service but not downstream services or queue consDevOpsFără avertismente★ 5,4 K↓ —
- boltzaipoch/open-scienceStructure prediction for protein, nucleic-acid, and small-molecule complexes with Boltz-2 (Passaro & Wohlwend et al. 2025, github.com/jwohlwend/boltz). Reach for this skill to validate designed binders against a target, to co-fold a protein with a SMILES or CCD ligand, or to get an open-source AlphaFold3 alternative with optional binding-affinity prediction.ȘtiințăFără avertismente★ 5,4 K↓ —
- mirrord-kafkametalbear-co/mirrordHelps DevOps engineers configure mirrord Operator's Kafka queue splitting feature end-to-end. Generates the MirrordSplitConfig and MirrordPropertyList Kubernetes CRD YAMLs (the current resources; MirrordKafkaTopicsConsumer + MirrordKafkaClientConfig are deprecated but still supported), the matching mirrord.json split_queues section with message_filter and jq_filter, and Helm value guidance. Use this skill whenever the user mentions Kafka splitting with mirrord, MirrordSplitConfig, MirrordPropertyList, MirrordKafkaClientConfig, MirrordKafkaTopicsConsumer, Kafka queue/topic splitting, configuring mirrord with Kafka, Kafka Streams splitting, MSK IAM auth, or troubleshooting Kafka splitting sessions. Also trigger on split_queues with queue_type Kafka, or connecting mirrord to a Kafka cluster. This is a Team/Enterprise feature of mirrord.DevOpsFără avertismente★ 5,4 K↓ —
- replica-deployJakeschincariol/replica-skillShips an app clone live on the user's own domain: a preflight gate (tests green, parity must-haves done, rebrand sweep clean, listing linted, legal pages up), production database and env vars, the host, DNS records for the domain and for email, Stripe live mode, OAuth redirects, monitoring, and mobile builds to TestFlight and Play. Use when the user says "deploy it", "ship it", "put it live", "connect my domain", "go to production", "publish the app", or after /replica-launch.DevOpsFără avertismente★ 5,4 K↓ —
platform-detection
dotnet/skills
TestareActualizat acum 7 ore
De la autor
Identify a .NET project's test platform, framework, command mode, and SDK-style vs classic project system. Use only for "which test platform/framework?", "VSTest or MTP?", or "what runner does this project use?", including bridge settings, UseVSTest opt-outs, and incompatible or conflicting VSTest/MTP configuration. Resolves global.json, project, packages.config, Directory.Build.props, and Directory.Packages.props precedence for MSTest/xUnit/NUnit/TUnit. DO NOT USE when the user asks to run/filter tests or for commands, flags, TRX/dumps, or test-command/filter errors; use run-tests directly. Do not route hot-reload or migration requests here as the entry skill; mtp-hot-reload may use this skill internally for platform detection.
Instalare
npx skills add dotnet/skills --skill platform-detection -a claude-code
Se instalează în .claude/skills/platform-detection/ · 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
Proveniență85
Întreținere100
Licență100
Adopție59
Fișiere (2)
- SKILL.md
- references/command-mode.md