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
- 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↓ —
- 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↓ —
- testinggrafana/skillsProbe, load-test, and instrument frontends from Grafana Cloud. Covers Synthetic Monitoring (HTTP / DNS / TCP / Ping / Traceroute / Multihttp / k6-browser scripted checks from 20+ global probes, alert on `probe_success` + TLS-cert expiry), Grafana Cloud k6 (distributed load tests across AWS load-zones, scenarios, `http_req_duration` thresholds, CI integration via `grafana/k6-action`), and Frontend Observability with Faro Web SDK (RUM, Core Web Vitals, custom events, `pushError`, distributed-trace correlation). Use when checking website / API uptime from multiple regions, gating a release on a load test, watching for TLS-cert renewal, instrumenting a React/Vue app, tracking Core Web Vitals, or correlating frontend errors to backend traces — even when the user says "is my login flow up?", "monitor my API", "ping our endpoint every minute", "release-gate load test", "browser performance monitoring", "session replay", or "RUM" without naming Synthetic Monitoring / k6 / Faro.OficialTestareFără avertismente★ 290↓ —
- k6-managegrafana/skillsInteract with Grafana Cloud k6 (GCk6) — manage load tests, test runs, scripts, projects, schedules, env vars, fetch metrics or logs, and run scripts locally — using the `gcx` CLI (or direct curl when gcx is unavailable). Use this skill whenever the user mentions a k6 cloud test or run, asks to list/edit/create/start/abort k6 load tests, wants to fetch logs or metrics for a test run, manage k6 project limits or schedules, run a k6 script locally or via `k6 cloud run`, or needs to call any `/cloud/v6/`, `/cloud/v5/`, or k6-app Loki endpoint against a Grafana Cloud stack. Trigger even when the user doesn't explicitly say "gcx" or "API" — phrases like "why did my k6 test fail", "show me logs for run X", "bump VUh limit on project Y", or "update my k6 script" all qualify.OficialTestareFără avertismente★ 290↓ —
- 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★ 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↓ —
- 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↓ —
- vercel-composition-patternszebbern/claude-code-guideReact composition patterns that scale. Use when refactoring components with boolean prop proliferation, building flexible component libraries, or designing reusable APIs. Triggers on tasks involving compound components, render props, context providers, or component architecture. Includes React 19 API changes.MediaFără avertismente★ 4,7 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★ 290↓ —
- secure-code-reviewzebbern/claude-code-guideSystematically reviews code for SQL injection, XSS, SSRF, broken access control, cryptographic failures, and other common OWASP Top 10 vulnerabilities, providing vulnerable code examples and ready-to-use remediation guidance. Trigger this skill when users ask for a security review, vulnerability scan, or penetration testing assistance, or mention keywords like OWASP, SQL injection, XSS, code audit, or security checklist.InginerieFără avertismente★ 4,7 K↓ —
- admingrafana/skillsManage Grafana Cloud accounts — organizations, stacks, RBAC roles and assignments, SSO/SAML/OAuth/GitHub auth, service accounts for CI/CD, user invites, team membership, and API-driven provisioning. Creates stacks via the Cloud API, mints service-account tokens, applies role assignments, configures SSO providers, and provisions teams/folders/dashboards via Terraform. Use when managing Grafana Cloud access, configuring SSO/SAML/OAuth, setting up service accounts for Terraform/CI/CD, assigning RBAC roles, inviting users, managing multiple stacks or organizations, provisioning cloud resources via API or Terraform, or auditing admin actions — even when the user says "set up SSO", "create a stack", "make a service account", or "onboard a team" without explicitly saying "admin".OficialDevOpsFără avertismente★ 290↓ —
- 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↓ —
- 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↓ —
- 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↓ —
- melonjs-particles-and-trailsActualizatmelonjs/melonJSUse this skill for particle effects and motion trails in melonJS — ParticleEmitter configuration, burst versus stream emission, the referenceSpace frame of reference introduced in 20.2, 3D particle motion through elevation and minSpread/maxSpread in 20.8, and the Trail renderable. Covers the emitter that silently does nothing until you call an emit method. Triggers on: Trail3d, ribbon, exhaust trail, speed streak, ski track, tyre mark, ribbonNormal, ParticleEmitter, particles, burstParticles, streamParticles, referenceSpace, ParticleEmitterSettings, elevation, minSpread, maxSpread, spawn area, Trail, explosion, smoke, sparks, debris, ring, exhaust, emitter, tintOverLife, colour over life, color over life, flame, fire.MediaFără avertismente★ 6,4 K↓ —
- lifelinesbrycewang-stanford/Auto-Empirical-Research-SkillsComplete survival analysis library in Python. Handles right-censored data, Kaplan-Meier curves, and Cox regression. Standard for clinical trial analysis and epidemiology.ȘtiințăFără avertismente★ 4,8 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↓ —
- 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↓ —
- 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↓ —
- stop-slopbrycewang-stanford/Auto-Empirical-Research-SkillsRemove AI writing patterns from prose. Use when drafting, editing, or reviewing text to eliminate predictable AI tells.RedactareFără avertismente★ 4,8 K↓ —
- 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↓ —
- 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
- hunt-rag-vectorelementalsouls/Claude-BugHunterHunt vector-store / embedding-layer weaknesses in RAG pipelines (OWASP LLM08 Vector and Embedding Weaknesses) — persistent corpus poisoning that survives across sessions and users (distinct from one-shot indirect prompt injection, which is owned by hunt-llm-ai), cross-tenant vector-database IDOR (unauthenticated or unscoped queries against Pinecone/Weaviate/Chroma/Milvus/Qdrant/pgvector), source-text/metadata leakage in similarity-search results, and retrieval-hijack via adversarial embedding proximity ('SEO poisoning' for RAG). Targets: any app with a shared knowledge base, document upload feeding a chatbot, or a directly reachable vector-DB port. Validate: a second, clean session/account must inherit a poisoned result, or a cross-tenant artifact must be independently verifiable — confabulation is not a finding, same bar as hunt-llm-ai. Use when target is RAG-backed, exposes a vector-DB port, or lets users upload documents that other users' queries later retrieve.SecuritateFără avertismente★ 5,3 K↓ —
performance-rca
grafana/skills
OficialTestareActualizat acum 9 ore
De la autor
Investigates 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.
Instalare
npx skills add grafana/skills --skill performance-rca -a claude-code
Se instalează în .claude/skills/performance-rca/ · 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: APACHE-2.0
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De ce 91
Securitate100
Proveniență100
Întreținere100
Licență100
Adopție41
Fișiere (2)
- SKILL.md
- references/advanced-analysis.md