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 10 ore
45.604 skill-uri
- skill-creatoranthropics/skillsCreate new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.OficialTestareFără avertismente★ 183,6 K↓ —Apare și în 10 alte depozite
- cue-kind-definitiongrafana/skillsAuthor CUE kind definitions for grafana-app-sdk apps - schemas, versioning, field constraints, named type definitions, custom routes, and codegen configuration. Scaffolds kinds via `grafana-app-sdk project kind add`, writes spec/status schemas with type constraints (regex, enum, range), defines `#`-prefixed named types for reusable structs, registers versions in the app manifest, and runs `grafana-app-sdk generate` with explicit error recovery. Use when working with CUE kinds, adding a new resource type, adding a version to an existing kind, writing schema field constraints, defining `#Definition` types, adding custom routes, editing files under `kinds/`, or when the user asks to "model a resource", "add a CUE schema", or "write a kind" — even without saying "CUE" explicitly.OficialRedactareFără avertismente★ 290↓ —
- prometheus-label-strategygrafana/skillsExpert evaluator for Prometheus label strategy on Grafana Cloud. Audits, designs, and improves label schemas using cardinality scoring, access-pattern alignment, static vs. dynamic label rules, histogram bucket discipline, and instrumentation hygiene. Prevents high cardinality at the source — in application code and scrape target labels — without dropping labels that make series unique (which breaks the data). For reducing the cost of series already in Grafana Cloud, routes to the adaptive-metrics skill. Use when the user asks to evaluate, audit, design, or improve Prometheus labels — or asks how to prevent high cardinality at the source. For "why is my Prometheus slow / expensive right now" triage, see prometheus-cardinality-troubleshooter.OficialDesignFără avertismente★ 290↓ —
- private-connectivitygrafana/skillsSet up private network connectivity to Grafana Cloud — AWS PrivateLink, Azure Private Link, GCP Private Service Connect, and Private Data Source Connect (PDC). Provisions VPC endpoints, private endpoints, or PSC forwarding rules per signal type (metrics / logs / traces / profiles); wires Alloy to push to the private DNS endpoint instead of the public one; verifies private DNS resolution + endpoint approval state. Use when sending telemetry to Grafana Cloud without traversing the public internet, eliminating cloud egress costs, meeting PCI-DSS / HIPAA / data-residency compliance, configuring PDC for private data-source queries, or connecting AWS / Azure / GCP workloads to Grafana — even when the user says "stop paying egress", "keep our telemetry off the public internet", or "PCI compliance for Grafana" without naming PrivateLink.OficialDevOpsFără avertismente★ 290↓ —
- dynamic-large-file-parquet-analysisOpenSenseNova/SenseNova-Skills动态统计Excel总行数，当数据量过大（≥10000行）时自动转换为Parquet格式加速读取，并对指定目标列进行条件筛选、分类汇总与结果导出，适用于超大体积Excel文件的快速读取与统计分析。DocumenteFără avertismente★ 5,9 K↓ —
- plugin-bundle-sizegrafana/skillsOptimise Grafana app plugin bundle size using React.lazy, Suspense, and webpack code splitting. Use when the user asks to reduce plugin bundle size, optimise module.js, add code splitting, improve initial plugin load performance, split plugin chunks, lazy load plugin pages, or help implement lazy loading in a Grafana app plugin. Triggers on phrases like "optimise plugin bundle size", "module.js is too large", "plugin is slow to load", "code split the plugin", "reduce initial JS payload", or "help me with Suspense in my plugin".OficialInginerieFără avertismente★ 290↓ —
- assistant-mcpgrafana/skillsConnect AI coding agents (Claude Code, Cursor, VS Code, OpenAI Codex) to Grafana Cloud via the `mcp-grafana` Model Context Protocol server. Installs the server with `go install`, generates a Grafana service-account token, wires `~/.claude/settings.json` or `~/.cursor/mcp.json` with the `command` + `env` block, runs `--disable-write` for safer read-only sessions, switches to SSE transport for team-shared / VS Code setups, and verifies with `/mcp` + a `list_datasources` round-trip. Use when connecting Claude Code to Grafana, setting up MCP for Grafana, configuring the Grafana MCP server, using Grafana tools in Cursor/VS Code, querying Grafana from an AI agent, sharing the MCP server across a team — even when the user says "give my agent Grafana access", "let Claude see my metrics", or "Cursor + Grafana" without saying "MCP".OficialRedactareFără avertismente★ 290↓ —
- frontend-session-rcagrafana/skillsDiagnoses a Grafana Frontend Observability (RUM) session: whether it is healthy, what went wrong, ranked problems with timestamps and evidence, likely cause, how to fix it. Optional follow-up: zoom in on the top error, impact across sessions, Session Replay, or a Tempo trace if the user asks. Fetches telemetry with `gcx frontend sessions get --save` and reads only that dump file. Use when the user asks to explain, diagnose, analyse, RCA, or review a session; asks if a session is healthy; pastes Frontend Observability session context (app id, session id, datasource UID); or mentions Faro, user journey, Core Web Vitals, exceptions, ANR, or a web or mobile RUM session — even if they do not say "session narrator" or "frontend-session-rca". Do not use this skill to instrument an app (Faro Web, React Native, Flutter, native OpenTelemetry) — use `app-observability` for Faro Web setup instead.OficialDesignFără avertismente★ 290↓ —
- mimirgrafana/skillsStand up Grafana Mimir for horizontally scalable, multi-tenant, long-term Prometheus + OTLP metrics storage. Covers monolithic / read-write / microservices deployment, S3 / GCS / Azure / filesystem block storage, Prometheus `remote_write` and OTLP ingestion, multi-tenancy with `X-Scope-OrgID`, ingester replication factor, compactor retention, and per-tenant limits. Use when running Mimir locally or on Kubernetes (Helm `mimir-distributed`), scaling Prometheus past a single node, picking ingest / query / backend split, configuring tenants and ingestion rate, debugging `/ready` 503s or `429 Too Many Requests`, or pointing Grafana at a Mimir datasource — even when the user says "I need long-term Prometheus storage", "scale Prometheus", "multi-tenant metrics backend", "Cortex replacement", "remote_write target", or "store 10M active series" without naming Mimir.OficialDevOpsFără avertismente★ 290↓ —
- infrastructuregrafana/skillsShip Kubernetes, host, container, and cloud-provider telemetry into Grafana Cloud — `k8s-monitoring` Helm chart for K8s clusters (metrics + logs + traces + events + cost), Alloy `prometheus.exporter.unix` for Linux hosts, cAdvisor + Docker discovery for containers, and CloudWatch / Azure Monitor / Google Cloud Monitoring datasource setup. Use when onboarding a new cluster or VM fleet to Grafana Cloud, picking the right Helm values for K8s scraping, wiring kube-state-metrics + node-exporter + cAdvisor, alerting on `PodCrashLooping` / node memory / PVC capacity, or pulling AWS / Azure / GCP cloud metrics — even when the user says "monitor my cluster", "send K8s metrics to Grafana", "scrape EC2 metrics", "cluster pod logs", or "install the monitoring helm chart" without naming `k8s-monitoring` or Alloy.OficialDevOpsFără avertismente★ 290↓ —
- 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↓ —
- lokigrafana/skillsGrafana Loki log aggregation and LogQL query language. Covers LogQL syntax (log queries, metric queries, label matchers, line filters, parsers: json/logfmt/pattern/regexp/unpack, label filters, line_format), Loki architecture, log ingestion via Alloy/Promtail/Fluent Bit, structured metadata, and Logs Drilldown. Use when writing LogQL queries, configuring Loki, troubleshooting log pipelines, or analyzing logs.OficialRedactareFără avertismente★ 290↓ —
- 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↓ —
- alloygrafana/skillsBuild a unified telemetry pipeline with Grafana Alloy — one OpenTelemetry-compatible binary that collects metrics, logs, traces, and profiles and ships to Grafana Cloud / Prometheus / Loki / Tempo / Pyroscope. Covers the Alloy config language (blocks, `sys.env`, component refs), `prometheus.scrape` → `remote_write`, `loki.source.file` + `loki.process` → `loki.write`, `otelcol.receiver.otlp` → `otelcol.exporter.otlp`, `pyroscope.scrape`, K8s / Docker / EC2 discovery, relabeling, modules (`import.file/git/http`), clustering, Fleet Management `remotecfg`, the Alloy UI at `:12345`, and `alloy fmt` / `alloy validate`. Use when writing a `config.alloy`, replacing Grafana Agent / OTel Collector, scraping K8s pods, parsing logs, ingesting OTLP, or debugging "Alloy isn't sending anything" — even when the user says "set up the agent", "write me a scrape config", "drop these logs before sending", or "OTel collector config" without naming Alloy.OficialDevOpsFără avertismente★ 290↓ —
- 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
- your-skill-namegrafana/skillsClear description of what this skill does and when to use it. Use when the user asks about X or wants to work with Y. Include specific trigger phrases so agents auto-load it correctly. Max 1024 characters.OficialPlanificareFără avertismente★ 290↓ —
- 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↓ —
- beylagrafana/skillsAuto-instrument an application's HTTP / gRPC / DB traffic with Grafana Beyla eBPF — no code changes, no SDK, no restart. Covers requirements (Linux 5.8+ with BTF, CAP_SYS_ADMIN, host PID), language matrix (Go / Java / Python / Ruby / Node / .NET / Rust / C++ / PHP), Docker + Helm + DaemonSet install, port- / process- / Kubernetes-metadata discovery, OTLP traces + Prometheus metrics export, routes decorator (cardinality control), trace sampling, and Grafana Cloud via Alloy. Use when adding observability to a service you can't recompile, instrumenting a closed-source binary, getting RED metrics + spans onto Tempo/Mimir without touching the app, or rolling Beyla as a cluster-wide DaemonSet — even when the user says "zero-code APM", "instrument legacy app", "trace this binary", "eBPF observability", or "no SDK" without naming Beyla.OficialDevOpsFără avertismente★ 290↓ —
- mirrord-prev-envmetalbear-co/mirrordHelp users create and manage mirrord preview environments — running a modified service as an isolated pod in a shared Kubernetes cluster, scoped by an environment key and HTTP/queue traffic filtering, so teams can validate and review changes against real traffic without affecting live services. Use when a developer wants to run "mirrord preview" ad hoc, share a preview via a link (mirrord-share-ingress), or wire preview environments into CI with the metalbear-co/mirrord-preview GitHub Action (e.g. per-PR previews, least-privilege cluster access).DevOpsFără avertismente★ 5,4 K↓ —
- sn-ppt-storyOpenSenseNova/SenseNova-Skills当前 PPT 任务已由 sn-ppt-entry 建好 DECK_DIR（task_pack.json 与 info_pack.json 已写入）后，必须由本 skill 将 query、全部用户材料与已完成 Research 编排为唯一可编辑的 outline.md 时使用。本 skill 是 entry → 出口（standard / dazzle / creative）之间的强制中间环节：不允许执行 Agent 跳过本 skill 直接依据 task_pack / info_pack 即兴编写大纲，不允许出口 skill 代写或改写大纲；前置产物缺失时停止并返回 sn-ppt-entry 补齐，不得自行补做研究。ȘtiințăFără avertismente★ 5,9 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★ 5,2 K↓ —Apare și în 1 alt depozit
- linkedin-comment-draftersergebulaev/linkedin-skillsDraft a LinkedIn comment on someone else's post from its URL, or reshare (repost) it to your feed with optional commentary. Use when the user pastes a post URL and asks to comment, engage, be first commenter, or repost with their thoughts. Produces 1-3 variants in the user's voice, picks a reaction, and publishes via Publora on approval. Not for replying to existing comments (use linkedin-reply-handler).MarketingFără avertismente★ 5,2 K↓ —Apare și în 1 alt depozit
- linkedin-thread-monitorsergebulaev/linkedin-skillsTrack which of your LinkedIn comments earned author replies. Flags the 6-24h warm-reply window where thread momentum peaks, classifies threads as hot/warm/cool/dormant, and routes warm ones to linkedin-reply-handler for follow-up drafts. Powered by Apify, no LinkedIn login. Triggers on "what threads need follow-up", "author replied", "monitor my comments". Not for analyzing likers on a post (use linkedin-engager-analytics).MarketingFără avertismente★ 5,2 K↓ —Apare și în 1 alt depozit
- sn-team-harnessOpenSenseNova/SenseNova-SkillsUse when a user asks what SenseNova Team Harness is, wants an introduction or overview, is getting started, or is deciding whether it fits — a self-hosted workspace where people and local AI agents collaborate on conversations, projects, work items, and artifacts. Covers its core concepts (Workspace, Project, Conversation, Agent, WorkItem, Resource, Artifact, Local Computer), main capabilities, how to run it, and the basic usage flow.AlteleFără avertismente★ 5,9 K↓ —
excel-smart-analysis-and-cleaning
OpenSenseNova/SenseNova-Skills
DocumenteActualizat 9 oct. 2026
De la autor
对多 Sheet Excel 进行智能清洗、跨表核对与可视化分析。。
Instalare
npx skills add OpenSenseNova/SenseNova-Skills --skill excel-smart-analysis-and-cleaning -a claude-code
Se instalează în .claude/skills/excel-smart-analysis-and-cleaning/ · 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
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De ce 91
Securitate100
Proveniență85
Întreținere100
Licență100
Adopție59
Fișiere (1)
- SKILL.md