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.
48.168 de skill-uri din 2.325 de depozite · actualizat acum 3 ore
48.166 de skill-uri
- 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↓ —
- 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★ 5,8 K↓ —
- nowledge-memThinkInAIXYZ/deepchatUse Nowledge Mem for cross-tool startup context, recall of prior decisions, durable learnings, explicit conversation saving, and connection diagnosis. Use only the connection selected for this DeepChat agent or session.ProductivitateFără avertismente★ 6,4 K↓ —
- deepchat-sdd-cleanupThinkInAIXYZ/deepchatUse only when a developer explicitly asks to clean, prune, tidy, or organize DeepChat SDD documentation after implementation and validation. Scans docs/features, docs/issues, and docs/architecture; prefers multi-agent review when available; removes completed issue docs when a linked GitHub issue is closed or implementation and validation evidence proves the bug no longer exists, drops stale plans and legacy task files from completed feature or architecture goals, and deletes obsolete feature or architecture docs.PlanificareFără avertismente★ 6,4 K↓ —
- deepchat-settingsThinkInAIXYZ/deepchatDeepChat app settings modification (DeepChat 设置/偏好) skill. Activate ONLY when the user explicitly asks to change DeepChat's own settings/preferences (e.g., theme, language, font size...). Do NOT activate for OS/system settings, editor settings, or other apps.RedactareFără avertismente★ 6,4 K↓ —
- writing-specsJetBrains/thinkrailUse when a workflow step drafts or revises a spec artifact — a goal-and-requirements, an architecture, or a module SPEC — or when a workflow skill names it at such a step. The shared quality bar for specs — not a workflow, nothing to execute.RedactareFără avertismente★ 6,8 K↓ —
- humanize-chinesebrycewang-stanford/Auto-Empirical-Research-SkillsDetect and humanize AI-generated Chinese text. 20+ rule detection categories plus statistical features (sentence-length CV, short-sentence fraction, comma density, perplexity, GLTR, DivEye) plus scene-aware LR fusion (rule × 0.2 + LR × 0.8) trained on three scenes: general / academic / longform 长文本 (≥1500 字)。Unified CLI: ./humanize {detect,rewrite,academic,style,compare}. 8 style transforms (casual/zhihu/xiaohongshu/wechat/academic/literary/weibo/novel)。 Multi-paragraph rewriting (paragraph length CV、跨段 trigram 重复) plus best-of-N humanize (默认 N=10 取最低 LR)。165 replacement patterns + CiLin 同义词词林 38873 with collision blacklist。 Academic paper AIGC reduction for CNKI/VIP/Wanfang (知网/维普/万方 AIGC 检测降重)。 Pure Python, no dependencies, offline。v5.0.0 — HC3 fused 准确率 95%、学术 hero 100→35 (-65)、 工作汇报 96→13 (-83)、长篇博客 96→41 (-55)。 Use when user says: "去AI味", "降AIGC", "人性化文本", "humanize chinese", "AI检测", "AIGC降重", "去除AI痕迹", "文本改写", "论文降重", "知网检测", "维普检测", "AI写作检测", "让文字更自然", "detect AI text", "humanize text", "reduce AIGC scRedactareFără avertismente★ 4,8 K↓ —
- brainstormingJetBrains/thinkrailUse before implementing a feature, a change in behavior, or a bug fix — however small. Not for questions, checks, or edits that change no behavior (typos, documentation or configuration only, mechanical refactors).PlanificareFără avertismente★ 6,8 K↓ —
- cloud-iam-deepelementalsouls/Claude-BugHunterCloud IAM red-team attack chain across AWS, Azure, GCP — focused on EXTERNAL exploitation paths and post-credential-discovery privilege analysis. Covers IAM enumeration (aws iam, az role, gcloud iam), STS/AssumeRole chaining, Azure Managed Identity abuse (via SSRF/leak), GCP service account JSON abuse, IMDSv1/v2 attacks via SSRF, K8s ServiceAccount token privilege analysis once held (token discovery / cluster exposure is owned by hunt-k8s), role-trust-policy confused-deputy, cross-account assume-role enumeration, IAM privilege escalation patterns (24+ AWS, 8+ Azure, 6+ GCP), and AWS Cognito Identity Pool unauthenticated-role attack chain (GetId → GetCredentialsForIdentity → IAM role abuse). Built for the case where recon yields a credential (key, JSON, token) and you need to know what it grants and how to escalate. Use when an AWS key / Azure secret / GCP service account JSON / K8s SA token surfaces from a code repo, JS bundle, APK, breach corpus, or SSRF chain.DevOpsFără avertismente★ 5,4 K↓ —
- promqlgrafana/skillsWrite, validate, and optimize PromQL for Prometheus / Grafana Mimir / Grafana Cloud Metrics. Covers `rate` vs `irate` vs `increase`, label matchers and regex, `sum / avg / topk / by / without` aggregation, classic + native `histogram_quantile`, ratios with divide-by-zero guards, `absent` / `changes` for staleness, time offsets and `predict_linear`, recording-rule naming, SLO + burn-rate math, and a cardinality-hunting playbook. Use when writing a metric query, fixing wrong p95s, building an error-budget alert, debugging "query is slow", finding the noisy label that blew up cardinality, or migrating a dashboard query to a recording rule — even when the user says "calculate the error rate", "p99 latency", "sum by service", "why is this query slow", or "what's filling Mimir" without naming PromQL.OficialRedactareFără avertismente★ 300↓ —
- pyroscopegrafana/skillsContinuously profile applications with Grafana Pyroscope and read the result as flame graphs. Covers three instrumentation paths — language SDK push (Go / Java / Python / Ruby / Node / .NET / Rust), Alloy eBPF auto-instrumentation (no code change, requires kernel 5.8+ with BTF), and SDK → Alloy receiver — plus ProfileQL queries, profile types (CPU / memory / allocations / goroutines / mutex), Grafana Cloud Profiles endpoint, and Span Profiles trace-to-profile linking. Use when adding profiling to a service, deploying Alloy as a cluster-wide eBPF profiler, hunting CPU / memory hotspots from a flame graph, comparing two profiles to find a regression, or correlating a slow Tempo trace to its profile — even when the user says "find what's burning CPU", "flame graph this app", "continuous profiling", "heap hotspots", or "why is allocation so high" without naming Pyroscope.OficialDevOpsFără avertismente★ 300↓ —
- k6-trend-analysisgrafana/skillsAnalyze Grafana Cloud k6 test run trends over time. Detects slow metric drift (e.g., P95 latency creeping up while still passing thresholds), computes headroom to thresholds, flags anomalies, and recommends threshold tightening. Use when the user asks about test performance trends, wants to know if metrics are degrading, asks whether thresholds should be tightened, or wants a health check across recent runs for a specific test. Trigger on phrases like "how is my test trending", "is P95 getting worse", "check for performance regression", "should I tighten thresholds", "are my tests degrading", "show me trends for test X", "analyze my k6 test runs", or "is my test getting slower". Also trigger when a user asks to check all tests in a project -- run this skill once per test and synthesize.OficialTestareFără avertismente★ 300↓ —
- grafana-ossgrafana/skillsConfigure Grafana OSS — provisions dashboards from YAML, sets up data sources (Prometheus / Loki / Tempo / Pyroscope), writes dashboard JSON with template variables, builds panel queries, assigns built-in roles (Viewer / Editor / Admin / GrafanaAdmin), mints service-account tokens, edits grafana.ini server config, creates annotations, installs plugins via provisioning, and validates each step with a health-check curl. Use when building dashboards, configuring data sources, setting up provisioning YAML, picking a panel type, writing template variables, managing users and roles, configuring SMTP/OAuth in grafana.ini, creating annotations via API, troubleshooting why a provisioned dashboard isn't showing up, or running Grafana OSS locally — even when the user says "set up a Prometheus data source", "provision dashboards from git", "make a service account", or "configure SSO in OSS" without saying "Grafana OSS".OficialRedactareFără avertismente★ 300↓ —
- bb-methodologyelementalsouls/Claude-BugHunterUse at the START of any bug bounty hunting session, when switching targets, or when feeling lost about what to do next. Master orchestrator that combines the 5-phase non-linear hunting workflow with the critical thinking framework (developer psychology, anomaly detection, What-If experiments). Routes to all other skills based on current hunting phase. Also use when asking "what should I do next" or "where am I in the process."ProductivitateFără avertismente★ 5,4 K↓ —
- prometheusgrafana/skillsPrometheus and Grafana Cloud Metrics overview including PromQL query language, Metrics Drilldown, alerting, recording rules, and integration patterns. Use when working with Prometheus, writing PromQL queries, configuring alerting, or discussing metrics architecture and best practices.OficialRedactareFără avertismente★ 300↓ —
- linkedin-employee-advocacysergebulaev/linkedin-skillsStand up and run a LinkedIn employee advocacy program for a marketing or sales team. Covers 14-day launch playbook, brand-guideline governance, per-post time budget, cadence benchmarks, and team ROI (reach, engagement, pipeline). Triggers on "employee advocacy", "get the team posting", "scale LinkedIn across team", "advocacy ROI". Not for planning one person's own calendar (use linkedin-content-planner).MarketingFără avertismente★ 5,4 K↓ —Apare și în 1 alt depozit
- app-observabilitygrafana/skillsGet RED metrics + service maps + frontend RUM + AI/LLM monitoring out of Grafana Cloud — Application Observability (`traces_spanmetrics_*` from OTel traces, p50/p95/p99 latency, exemplar-to-trace, traces-to-logs / profiles), Frontend Observability with the Faro Web SDK (Core Web Vitals, session replay, `pushError`, React + router integration, `TracingInstrumentation` for browser → backend trace correlation), and AI Observability via OpenLIT (token / cost / latency, GPU, hallucination + toxicity evals). Use when standing up APM for a service, wiring an Alloy OTLP receiver + forwarding to Cloud, instrumenting a React frontend for RUM, debugging why service-map edges are missing, monitoring LLM cost drift, or correlating a frontend error to its backend trace — even when the user says "set up APM", "show service map", "monitor browser perf", "session replay", "RUM SDK", or "watch our OpenAI bill" without naming App / Frontend / AI Observability.OficialDevOpsFără avertismente★ 300↓ —
- designlang-tokensManavarya09/design-extractUse when styling UI for render.com — references the extracted design system tokens instead of inventing colors, spacing, or typography.DesignFără avertismente★ 4,4 K↓ —
- melonjs-getting-startedmelonjs/melonJSUse this skill when starting or bootstrapping a melonJS game, creating the Application, choosing a renderer, or setting up the first scene. Covers the mandatory async init, the world container, adding renderables, and the WebGPU/WebGL 2/Canvas fallback. Triggers on: melonjs, new Application, app.init, app.world, video.AUTO, video.WEBGL, video.CANVAS, Stage, state.change, getting started, bootstrap.MediaFără avertismente★ 6,4 K↓ —
- linkedin-content-plannersergebulaev/linkedin-skillsGenerate a 7-day LinkedIn content plan from a theme, audience, and pillars. Produces per-day post pillar, format, hook type, CTA, posting time, daily comment targets, and a weekly inbound-readiness check. Use when the user wants to plan a week or month of content, not draft a single post (use linkedin-post-writer).MarketingFără avertismente★ 5,4 K↓ —Apare și în 1 alt depozit
- cross-examinezebbern/claude-code-guideInterview the user relentlessly about a plan or design until reaching shared understanding, resolving each branch of the decision tree. Use when user wants to stress-test a plan, get grilled on their design, or mentions "grill me".TestareFără avertismente★ 4,7 K↓ —
- sn-proactive-agentOpenSenseNova/SenseNova-Skills安装、启动和使用 Proactive Agent，记录项目进展并在合适时机提醒下一步。AlteleFără avertismente★ 6 K↓ —
- sn-research-reportOpenSenseNova/SenseNova-Skills用于撰写或组织研究报告结构。按读者认知任务（全景/对比/调查/时序）和领域惯例（学术/医疗/法律/政策）选择报告模板。ȘtiințăFără avertismente★ 6 K↓ —
- group-by-analysisOpenSenseNova/SenseNova-Skills对多 Sheet 的 Excel 文件进行行数统计、大文件 Parquet 转换预处理、数据清洗及分组聚合分析，并生成带样式标记的统计表与可视化图表。DocumenteFără avertismente★ 6 K↓ —
line-chart-visualization
OpenSenseNova/SenseNova-Skills
AlteleActualizat alaltăieri
De la autor
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。
Instalare
npx skills add OpenSenseNova/SenseNova-Skills --skill line-chart-visualization -a claude-code
Se instalează în .claude/skills/line-chart-visualization/ · 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
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De ce 91
Securitate100
Proveniență85
Întreținere100
Licență100
Adopție60
Fișiere (1)
- SKILL.md