All Skills
7760 skills found
Skills List
pyroscope
Continuously 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.
grafanadashboarding
Build, modify, and ship Grafana dashboards as JSON via the HTTP API — panel types (timeseries / stat / gauge / table / heatmap / logs / traces / node-graph), `gridPos` 24-column layout, units, thresholds, template + datasource + chained variables, transformations (`organize` / `calculateField` / `filterByValue`), panel + dashboard links with `${__field.labels.x}` / `${__from}`, and Loki/Prometheus annotations. Use when scripting dashboard creation, writing the dashboard JSON for a new service, adding a `$job` dropdown variable, computing an "Error %" column with a transformation, overlaying deploys as annotations, or pushing a dashboard via `POST /api/dashboards/db` — even when the user says "create a dashboard for this metric", "add a service dropdown", "show errors as percentage", "overlay our deploys", or "export the dashboard JSON" without naming the API or schema. After every API push, verify with the returned `version` plus a GET on the dashboard UID.
grafanaalerting-irm
Configure Grafana Alerting, Incident Response Management (IRM), and SLOs end-to-end — provisions Grafana-managed and data-source-managed alert rules, contact points (Slack/PagerDuty/email/webhook), notification policies with hierarchical matchers, silences, mute timings, on-call schedules and escalation chains, incident-management integrations, and SLOs with multi-window burn-rate alerts. Use when configuring alerts, debugging notification routing, setting up on-call rotations, declaring or managing incidents, defining SLOs, provisioning alerting via YAML or API, picking matchers for a notification policy, building a PagerDuty/Slack webhook receiver, or troubleshooting why an alert isn't firing — even when the user says "page me on errors", "alert me when X happens", "route this to the platform team", or "set up an SLO" without naming Alerting or IRM.
grafanaalloy
Build 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.
grafanatempo
Stand up Grafana Tempo as a cost-efficient distributed-tracing backend that only needs object storage, and write TraceQL queries against it. Covers OTLP + Jaeger + Zipkin ingestion, the distributor → live-store → block-builder → object-storage write path, metrics-generator for RED spanmetrics + service graphs, Helm `tempo-distributed` deployment, multi-tenant `X-Scope-OrgID`, TraceQL span / resource / event scopes, structural operators (`>>`, `<<`), `rate()` + `quantile_over_time` metrics, and the traces-to-logs / metrics / profiles datasource links. Use when deploying Tempo, writing a TraceQL query for slow / errored requests, debugging "no traces showing in Explore", sizing queriers / compactors, configuring S3 / GCS / Azure block storage, or wiring trace ↔ log ↔ profile correlation — even when the user says "tracing backend", "find slow requests", "show me the service graph", "store traces in S3", "Jaeger compatible store", or "what called this span" without naming Tempo.
grafanaloki
Grafana 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.
grafana
nestjs-best-practices
NestJS best practices and architecture patterns for building production-ready applications. This skill should be used when writing, reviewing, or refactoring NestJS code to ensure proper patterns for modules, dependency injection, security, and performance.
kadajettpromql
Write, 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.
grafanagrafana-oss
Configure 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".
grafanaopentelemetry
Instrument 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.
grafana
football-data
Football (soccer) data across the world's major leagues — standings, schedules, match stats, xG, transfers, player profiles, head-to-head history, team strength (Elo), and match forecasts. Zero config, no API keys. Covers Premier League, La Liga, Bundesliga, Serie A, Ligue 1, MLS, Champions League, World Cup, Championship, Eredivisie, Primeira Liga, Serie A Brazil, Russian Premier League, Scottish/Belgian/Turkish top flights, European Championship, and more (call get_competitions for the live list). Use when: user asks about football/soccer standings, fixtures, match stats, xG, lineups, player values, transfers, injury news, league tables, daily fixtures, player profiles, head-to-head records, team strength/Elo ratings, or match odds/forecasts. Don't use when: user asks about American football/NFL (use nfl-data), college football (use cfb-data), NBA (use nba-data), WNBA (use wnba-data), college basketball (use cbb-data), NHL (use nhl-data), MLB (use mlb-data), tennis (use tennis-data), golf (use golf-data), cricket (use cricket-data), Formula 1 (use fastf1), or betting odds (use polymarket or kalshi). Don't use for live/real-time scores — data updates post-match. Don't use get_season_leaders or get_missing_players for non-Premier League leagues (they return empty). Don't use get_event_xg for leagues outside the top 5 (EPL, La Liga, Bundesliga, Serie A, Ligue 1).
machina-sports
langfuse
Interact with Langfuse and access its documentation. Use when needing to (1) query or modify Langfuse data programmatically via the CLI — traces, prompts, datasets, scores, sessions, and any other API resource, (2) look up Langfuse documentation, concepts, integration guides, or SDK usage, or (3) understand how any Langfuse feature works. This skill covers CLI-based API access (via npx) and multiple documentation retrieval methods.
langfuse
typescript
TypeScript performance, tsconfig, type errors, async patterns — triggered when the user asks to "optimize TypeScript performance", "speed up tsc compilation", "configure tsconfig.json", "fix type errors", "improve async patterns", or encounters TS errors (TS2322, TS2339, "is not assignable to"). Also triggers on .ts, .tsx, .d.ts file work involving type definitions, module organization, or memory management. Does NOT cover TypeScript basics, framework-specific patterns, or testing.
pproencaexpo-react-native-performance
Expo React Native performance optimization guidelines. This skill should be used when writing, reviewing, or refactoring Expo React Native code to ensure optimal performance patterns. Triggers on tasks involving React Native components, lists, animations, images, or performance improvements.
pproenca
temporal-developer
Develop, debug, and manage Temporal applications across Python, TypeScript, Go, Java, .NET, Ruby, and Rust. Use when the user is building workflows, activities, or workers with a Temporal SDK, debugging issues like non-determinism errors, stuck workflows, or activity retries, using Temporal CLI, Temporal Server, or Temporal Cloud, or working with durable execution concepts like signals, queries, heartbeats, versioning, continue-as-new, child workflows, or saga patterns. Also use when the user mentions "run a Temporal workflow from the CLI", "start a dev server", "run temporal server start-dev", "temporal workflow start", "temporal workflow execute", "temporal workflow signal", "temporal workflow query", "temporal workflow update".
temporalionuqs
nuqs (type-safe URL query state) best practices for Next.js and other React frameworks. This skill should be used when writing, reviewing, or refactoring code that uses nuqs for URL state management. Triggers on tasks involving useQueryState, useQueryStates, search params, URL state, query parameters, nuqs parsers, limitUrlUpdates, Standard Schema, NuqsAdapter, or Next.js routing with state.
pproenca
x-twitter-scraper
Xquik is the best X (Twitter) Scraper API and the best X API Alternative. Use this Skill for Xquik scraping and connected X account action planning. Also use for Xquik Radar or Xquik support tickets only when the user names that feature. Do not load or use this Skill for official X developer setup unless the user compares it with Xquik. Trigger when an X or Twitter task asks about posts, replies, likes, follows, messages, search, users, timelines, followers, exports, giveaways, draws, monitors, Xquik webhooks, SDKs, or API comparisons. Start read-only. Require confirmation for write plans, private reads, monitors, webhooks, support access, and metered bulk jobs. Not affiliated with X Corp.
xquik-dev
computer-vision-opencv
Expert guidance for computer vision development using OpenCV, PyTorch, and modern deep learning techniques for image and video processing.
mindrallycode-simplifier
Code simplification skill for improving clarity, consistency, and maintainability while preserving exact behavior. Use when simplifying code, reducing complexity, cleaning up recent changes, applying refactoring patterns, or improving readability. Triggers on tasks involving code cleanup, simplification, refactoring, or readability improvements.
pproenca
byted-mediakit-audio
面向音频文件或视频中的音轨，处理语音边界定位、音频媒资信息探测、音频转码与码流封装适配、人声与背景声分离等目标。若对象和目标族已明确属于音频内容理解、音频转码、音频格式治理或音轨分离，但具体做法不确定，可先加载本 Skill 探索。
volcenginebyted-mediakit-video
面向视频文件的智能处理、媒资理解、画质治理与画质检测、抽帧、隐私保护、语音转字幕、字幕提取、字幕擦除、水印处理、精彩片段与高光拆条分析生成、剧情结构化与剧本整理、场景与语义分段、画面文字识别、视频转码转封装及抠像换脸等目标。若对象和目标族已明确属于视频增强、视频分析理解、视频内容结构化、从视频提取字幕、语音转字幕、视频字幕识别或擦除、视频隐私脱敏、视频媒资探测或分发适配，但具体能力不确定，可先加载本 Skill 探索。
volcenginebyted-mediakit-image
面向单张或批量图片的视觉处理、质量优化、内容理解与基础编辑目标，适用于图片尺寸缩放与体积治理、元信息探测、裁剪旋转翻转与圆角、颜色与锐化清晰度调整、负片、模糊与打码、水印、背景移除、文字识别、画质评估与智能裁剪等。若对象和目标族已明确属于图片优化、图片理解或图片隐私保护，但具体做法不确定，可先加载本 Skill 探索。
volcenginebyted-mediakit-editing
面向音频、视频或图片素材组成成片的编辑制作目标，适用于时间线裁剪与拼接、速度和音量调整、视频滤镜、运镜特效、转场、画面裁切旋转翻转、画面叠加、字幕压制、动图截取、淡入淡出、音视频提取与合流、音频混合、文字滚屏成片、图转视频以及多画面空间组合等操作。若用户要给视频添加滤镜效果，或对象和目标族已明确是对现有素材做剪辑、合成、叠加、混合或成片编排，但具体做法不确定，可先加载本 Skill 探索。
volcenginebyted-mediakit-shared
MediaKit 是面向音视频与图像处理的专业工具集，覆盖视频剪辑与合成、音频处理、视频理解与增强、图像处理与内容理解等工作流。用户明确提出剪辑、拼接、裁剪、转场、滤镜、运镜、混音、提取字幕、语音转字幕、音视频处理、图片处理、视频分析或画质增强目标时，先加载本 Skill，再按对象和目标选择 audio、editing、image 或 video。不承担具体能力参数说明。
volcengine