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
- k6-cloud-investigate-testgrafana/skillsInvestigate a Grafana Cloud k6 test — describe the script, list run history, identify pass/fail status, pull raw metric time-series and log lines for one or more runs, and (if asked) safely edit the test script. Use when the user asks about a specific k6 cloud test or run, gives a `/a/k6-app/tests/<id>` or `/a/k6-app/runs/<id>` URL, asks "is this test passing", "why are my k6 tests failing", "show me metrics for run X", "show me logs for run X", or wants to add thresholds / fix a failing test. Trigger this skill even when the user doesn't explicitly say "investigate" — pasted `/a/k6-app/...` URLs, "why did run X fail", "what happened with my test", "is my test healthy", "the latest run looks weird", "checks are failing but the run says passed", or any request to diagnose a Grafana Cloud k6 run all qualify.OficialTestareFără 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↓ —
- 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↓ —
- loki-label-analyzergrafana/skillsExpert evaluator for Grafana Loki label strategy. Audits, designs, and improves label schemas using cardinality scoring, access-pattern alignment, static vs. dynamic label rules, and consistency checks. Use when the user asks to evaluate, audit, design, or improve a Loki label strategy — or asks why their Loki queries are slow.OficialDesignFără 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↓ —
- 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↓ —
- 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↓ —
- 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↓ —
- 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★ 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↓ —
- performance-rcagrafana/skillsInvestigates CPU, memory, and contention problems with Grafana Pyroscope profiles via the gcx CLI. Compares affected and baseline workloads, locates changed application stacks, and tests root-cause hypotheses against symptom and change evidence. Use when a service shows high CPU, growing memory, GC pressure, lock contention, or hot functions, when code regressed after a deploy, or when given a suspect service, flame graph, trace, or profiling anomaly report. For profiling setup use pyroscope; for profilecli-based analysis use profilecli-insights.OficialTestareFără avertismente★ 290↓ —
- dpm-findergrafana/skillsFind the Prometheus metrics that drive your Grafana Cloud bill. `dpm-finder` is a Grafana Professional Services CLI that ranks metrics by Data Points per Minute (DPM) with per-label-set breakdown, optional `--cost-per-1000-series` pricing, and a Prometheus-exporter mode. Use when investigating high Grafana Cloud spend, hunting noisy / high-cardinality metrics, comparing pre/post recording-rule cardinality, or feeding cost data into dashboards — even when the user says "why is my Mimir bill so high?", "find the biggest metrics", "cardinality offenders", or "optimize Prometheus cost" without naming dpm-finder.OficialFinanțeFără avertismente★ 290↓ —
- 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★ 290↓ —
- opentelemetrygrafana/skillsInstrument any app with OpenTelemetry and ship metrics / logs / traces to Grafana Cloud or self-hosted Mimir / Loki / Tempo / Pyroscope. Covers SDK auto-instrumentation for Go, Java (Grafana JVM agent), Python (`opentelemetry-instrument`), Node.js, .NET (`Grafana.OpenTelemetry`), Beyla eBPF for zero-code; Grafana Cloud OTLP gateway + Basic-auth (instanceID + API key, base64); env-var config (`OTEL_EXPORTER_OTLP_*`, `OTEL_RESOURCE_ATTRIBUTES`); Alloy / OTel-Collector pipelines; Kubernetes Operator inject-annotations; and head + tail sampling. Use when instrumenting a service, pointing OTLP at Grafana Cloud, switching from Jaeger / Datadog / New Relic, choosing head- vs tail-sampling, or debugging "spans aren't showing in Explore" — even when the user says "auto-instrument my Java app", "send traces to Grafana", "what env vars do I set", "OTLP endpoint", or "Operator inject" without naming OpenTelemetry.OficialDevOpsFără avertismente★ 290↓ —
- 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↓ —
- sn-report-format-discoveryOpenSenseNova/SenseNova-Skills用于用户希望推荐研究成品形式,或最终形式无法从需求中直接判断时。把需求解析为一个简短的 format 字符串,不创建格式文件或 schema。AlteleFără avertismente★ 5,9 K↓ —
- adaptive-metricsgrafana/skillsCut Grafana Cloud Metrics cost by shrinking active-series count with Adaptive Metrics aggregation rules — auto-recommendations from query history, custom exact/regex rules, label-drop config, unused-metric detection, and Alloy remote_write fallback. Use when investigating a high Mimir/Grafana Cloud bill, hunting high-cardinality labels (`pod_uid`, `service_instance_id`, `version`), pre-aggregating counters/gauges, dropping unused metrics, or measuring `grafanacloud_instance_active_series` before/after — even when the user says "reduce cardinality", "too many series", "metrics spend", "active series count is exploding", or "drop the version label" without naming Adaptive Metrics.OficialFinanțeFără avertismente★ 290↓ —
- send-datagrafana/skillsSending telemetry data to Grafana Cloud — metrics via Prometheus remote write or OTLP, logs via Loki push or Alloy, traces via OTLP to Tempo, profiles via Pyroscope. Covers Alloy-based pipelines, direct SDK/agent integrations, cloud integrations catalog, and credentials management. Use when connecting an application or infrastructure to Grafana Cloud, setting up data ingestion, configuring remote write, or choosing between ingestion methods.OficialDevOpsFără avertismente★ 290↓ —
- dynamic-percentage-and-large-file-analysisOpenSenseNova/SenseNova-Skills根据文件行数动态切换大文件处理策略(Parquet转换),通过逐行扫描或列匹配提取关键指标并计算占比、均值等统计量,最终输出结构化Excel报告及可视化图表。DocumenteFără avertismente★ 5,9 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★ 290↓ —
- ml-aigrafana/skillsTurn on AI + ML features in Grafana Cloud — Grafana Assistant (NL → PromQL/LogQL/TraceQL, dashboard build, incident investigation, MCP integration), Dynamic Alerting (Prophet forecasting + DBSCAN outlier detection), Sift (8-analysis automated root-cause), Knowledge Graph + RCA Workbench, and the LLM Plugin (OpenAI / Anthropic / Azure / Ollama / vLLM / LiteLLM). Use when you want anomaly alerts without static thresholds, natural-language querying, automated incident investigation, dashboards generated from a sentence, or a managed LLM proxy for plugins — even when the user says "alert when something looks weird", "explain this PromQL", "find the root cause", "make this a dashboard", or "wire Claude into Grafana" without naming any of these products.OficialDevOpsFără avertismente★ 290↓ —
- humanize-scanepoko77-ai/im-not-ai한글 글에 AI 티가 얼마나 있는지 재고, 실제로 고치면 어떻게 되는지 표본으로 보여주는 정찰 스킬. 실측 판별력 상위 6개만 본다. 워크스페이스·진단·게이트·서브에이전트 없이 이 대화 안에서 끝낸다(파일 0개, 서브에이전트 0회). 손볼 게 많다고 나오면 전수 윤문은 humanize-korean(=/humanize)으로 넘긴다. 트리거 — "이 글 AI 같아?", "AI 티 있나 봐줘", "스캔해줘", "윤문 돌릴 값어치 있나", "AI 티 점수", "quick humanize", "/humanize-scan".RedactareFără avertismente★ 6,2 K↓ —
- excel-conditional-comparison-and-large-file-processingOpenSenseNova/SenseNova-Skills对比Excel多表中的特定系数并对异常值进行颜色标记。DocumenteFără avertismente★ 5,9 K↓ —
- melonjs-pluginsmelonjs/melonJSUse this skill when adding a melonJS plugin or adapter — the debug panel, Spine skeletal animation, compressed Tiled map support, Capacitor packaging — or when writing your own plugin. Covers plugin.register and its version gate, plugin.cache, plugin.patch, and why physics adapters are not plugins. Triggers on: plugin, plugin.register, plugin.cache, plugin.get, plugin.patch, BasePlugin, debug-plugin, DebugPanelPlugin, SpinePlugin, TiledInflatePlugin, CapacitorPlugin, adapter, custom plugin, plugin version mismatch, already registered.MediaFără avertismente★ 6,4 K↓ —
nowledge-mem
ThinkInAIXYZ/deepchat
De la autor
Use 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.
Instalare
npx skills add ThinkInAIXYZ/deepchat --skill nowledge-mem -a claude-code
Se instalează în .claude/skills/nowledge-mem/ · 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.
La ce are acces
Verificări de siguranță pe SKILL.md
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De ce 91
Fișiere (1)
- SKILL.md