Claude Skills
The open format is called Agent Skills and works in Claude Code, Codex, Cursor and other agents — most people know it as Claude Skills.
Every Agent Skill we could find on GitHub, deduplicated by content. 79 870 files from 1 769 authors, of which 62 217 are unique — the rest is the same skill repackaged into someone else's repository. For each one: what it weighs in tokens, whether it ships runnable scripts, and which MCP servers it needs.
Create and push a new semver release tag. Asks for release type (patch/minor/major), validates commit exists on remote, bumps version, and pushes the tag.
Review C++ code against Google C++ Style Guide. Use when reviewing C++ code, pull requests, or when asked to check code style compliance.
Regenerate and post-process all agentic workflows. Use when gh-aw is updated, workflow .md files change, or when asked to recompile/regenerate workflows.
Debug the AWF firewall by inspecting Docker containers (awf-squid, awf-agent), analyzing Squid access logs, checking iptables rules, and troubleshooting blocked domains or network issues.
Practical Python scripts for debugging awf - parse logs, diagnose issues, inspect containers, test domains
Use the AWF (Agentic Workflow Firewall) to run commands with network isolation and domain whitelisting. Provides L7 HTTP/HTTPS egress control for AI agents.
Orchestrate endgame verification for a GitHub milestone issue. Fetches the issue, parses assigned tasks, delegates each task to a subagent that researches the linked PR/issue and writes a test plan, and saves every plan to com.microsoft.copilot.eclipse.swtbot.test/test-plans/ following the project's standard test-plan format.
Authors and validates SWTBot JSON probe scripts for GitHub Copilot for Eclipse UI flows against a real Eclipse workbench. Use when creating or updating probe-scripts, converting test plans to UI probes, validating end-to-end Eclipse UI behavior, or troubleshooting ProbeRunner failures.
Generate original one-ink or controlled two-ink editorial images from any theme, sentence, article idea, object, or reference photo. Always use this skill when the user asks for 单色海报、双色印刷、单色调视觉、蓝色/绿色孔版印刷、risograph、网点照片、复古或当代编辑排版、zine poster, monochrome editorial poster, duotone print, or asks to use the mono-color style. It uses an adaptive white, gray, or pale-beige substrate, no more than two printing inks, active negative space, terse human language, and strong serif/grotesk/mono typography without making retro styling the default or copying a source composition, wording, logo, or artwork. Produce both the final generation prompt and the generated raster image unless the user explicitly asks for prompt only.
Managing Linear issues, projects, and teams. Use when working with Linear tasks, creating issues, updating status, querying projects, or managing team workflows.
Use this skill whenever the user asks to create, improve, audit, or split prompts for AI video generators (Seedance, Kling, Veo, Runway, Luma, Pika, Sora, any image-to-video system). The skill also covers storyboards, shot lists, director treatments, dynamic montage, multi-clip story structure, camera direction, lighting, blocking, pacing, character continuity, dialogue, and sound design. Trigger even when the user says things like "придумай сцену для видео", "разбей на склейки", "сделай раскадровку", "улучши промпт для Kling", "переведи сценарий в промпты", "как снять X в AI-видео", or shares a prompt and asks to fix it.
> Image prompting skill for Nano Banana (NBP/NB2) and GPT Image 2. Writes ready-to-use картинку", "image prompt", "промпт для картинки", blog covers, slides, posters, product shots, UI mockups, storyboards, character sheets, edit/colorize, style transfer, vision analysis, image-to-prompt, nb, NBP, NB2, gpt-image-2, multi-panel grids, ecommerce product photography, fashion editorial, food/beverage ads, cinematic portraits.
| 在 Ardot 中构建可复用组件库或设计系统时使用此技能。 涵盖从变量/设计令牌创建到使用正确变量绑定构建组件的完整工作流程， 直至最终验证。 触发条件："创建组件库"、"构建设计系统"、 "制作可复用按钮"、"创建 UI 组件"、"构建组件集"、 "设计系统"、"组件库"、"可复用组件"。
| Record and query AI conversation logs — what users asked, how it was solved, and the result. Use when users want to logging conversation, summarize recent work from sessions, or want daily/weekly project summaries from past conversations.
> 微信公众号文章创作。当用户想把工作流探索、AI 工具测评、产品体验、个人实践、生活感悟等素材整理成公众号文章时使用。即使用户只是说「帮我写篇文章」「整理成推文」「发公众号」，也应当触发此技能。
将技术周报中的文章整理为滴答清单（TickTick）待办事项，同时支持单篇文章直接添加。当用户提供周报 markdown 文档、要求将周报文章添加到滴答清单，或提及"技术周报"、"文章汇总"、"添加到滴答"等关键词时，使用此技能；当用户分享单篇文章链接并希望添加到滴答清单时，同样使用此技能。
| **强制性前置条件** — 每次调用 `batch_edit` 工具之前，必须先调用此技能。 未经加载此技能，绝不能直接调用 `batch_edit`。 当用户想要在 Ardot 设计文件中创建、更新、移动或删除节点时触发 — 例如插入框架、文本、形状、组件；将变量绑定到填充/描边； 构建屏幕、组件或设计库。当涉及 batch_edit DSL 操作时也加载 （I/U/M/D/C/G 操作符）。
| **强制性前置条件** — 每次调用 `create_new_page` 工具之前，必须先调用此技能。 未经加载此技能，绝不能直接调用 `create_new_page`。 当用户想要在 Ardot 设计文件中创建新页面时触发。 关键词：在 Ardot 上下文中的"创建新页面"、"添加页面"、"新画布"。
| 从头设计或为 Ardot 项目应用视觉主题时使用此技能。 涵盖 `search_style_guide` → `build_style_guide` 工作流程，用于发现和应用完整的设计系统（颜色、排版、间距、布局模式）。 触发条件："设计落地页"、"创建仪表板"、"应用深色主题"、 "设置设计系统"、"选择调色板"、"为应用选择字体"、 "样式指南"、"视觉风格"、"外观和感觉"。
| 在 Ardot 中从头构建完整页面、屏幕或多区块 UI 布局时，将此技能与 ardot-use 配合使用。 通过 6 步工作流程编排多个 MCP 工具：初始化 → 样式系统 → 变量 → 骨架 → 逐区块构建 → 验证。 触发条件："在 Ardot 中创建落地页"、"构建登录屏幕"、 "在 Ardot 中设计仪表板"、"制作设置页面"、"创建个人资料屏幕"、 "在 Ardot 中构建此页面"、"将此设计转换为 Ardot"。
Work with Dynatrace dashboards - create, modify, query, and analyze dashboard JSON including tiles, layouts, DQL queries, variables, and visualizations.
End-to-end Dynatrace alerting lifecycle — anomaly detector setup and model selection (static threshold, adaptive baseline, seasonal baseline), alert event storage in Grail, problem grouping and denoising by root cause analysis, and workflow-based notification routing (email, Slack, ServiceNow, webhook). Use when configuring alerting, choosing between detector types, querying alert event history, understanding why alerts merged into a problem, or setting up problem-triggered notifications.
Work with Dynatrace notebooks - create, modify, query, and analyze notebook JSON including sections, DQL queries, and visualizations.
Dynatrace server-side JS runtime — function contract, runtime limits, Web APIs, Node.js modules, fetch with credential vault, and the @dynatrace-sdk/* catalog.
>- Analyze dashboards and notebooks using Davis analyzers — anomaly detection, novelty scoring, and correlation. Use when the user references a specific Dynatrace dashboard or notebook (by URL, UUID, or name) and asks what it shows, which DQL queries it runs, whether a tile looks off, or wants to find anomalies, score novelty, or correlate its metrics. The trigger is a dashboard or notebook as the data source, not a general DQL question. This skill extracts timeseries queries efficiently without reading the full raw document JSON, then optionally runs Davis analyzers on the extracted metrics. "novelty score", "correlate metrics", "extract DQL from dashboard", "dashboard URL", "tile", "run-analyzer", "timeseries extraction", "Davis analyzer".
Migrate Dynatrace classic and Gen2 entity-based DQL to Smartscape equivalents. Covers three scenarios. (1) mass data queries filtered by classic entity conditions — migrate to direct dimension filters first, Smartscape only as fallback; (2) mass data queries using entity subqueries for filtering — same dimension-first strategy; (3) pure entity list queries — migrate fetch dt.entity.* to smartscapeNodes. Also handles entityName, entityAttr, classicEntitySelector, and classic relationship patterns.
Instruments an existing Android project (Kotlin or Java) with the Dynatrace Mobile Agent for basic monitoring. Covers zero-to-first-event setup only: Gradle plugin, agent config, and user privacy opt-in. Do not use for advanced Dynatrace configuration beyond initial instrumentation.
Core DQL syntax, pitfalls, query patterns, and query optimization. Load to write, build, fix, or OPTIMIZE a DQL query — prevents syntax errors and makes queries faster, more efficient, and cheaper (less data scanned = lower query consumption/cost per run). Covers fetch commands, data models, field namespaces, time alignment, entity/smartscape patterns, metric discovery, and performance/cost optimization (filter early, bucket filters, short time ranges, field selection, sampling, cardinality). Trigger: \"write/build/fix a DQL query\", \"DQL syntax\", \"query logs/spans/metrics\", \"create a timeseries\", \"optimize my DQL\", \"make my query faster/cheaper\", \"reduce DQL cost/consumption/scanned data\", \"keep DQL cost under control\". Do NOT use to explain an existing query or answer product questions. For MONITORING a tenant's ACTUAL query consumption/billing (how much queries cost, who scanned most, cost trends) use dt-platform-costs — this tunes the query text, not billing data.
Azure cloud resources including VMs, VMSS, SQL Database, Storage, AKS, App Service, Functions, VNet networking, load balancers, Event Hubs, Container Apps, and Key Vault. Monitor Azure infrastructure, analyze resource usage, audit security posture, and manage organizational hierarchy across subscriptions and resource groups.
Real User Monitoring (RUM) on Dynatrace — web and mobile frontends. Core Web Vitals, user sessions, page performance, mobile crashes, frontend errors, and frontend-backend linking. Query via `user.events`, `user.sessions`, and `dt.frontend.*` metrics. Does NOT cover synthetic monitoring (HTTP/browser/network checks) — that's a separate domain.
>- Integrate the Dynatrace Flutter Plugin into a Flutter project — dependency setup, config, SDK bootstrap, navigation tracking, and verification. "integrate Dynatrace Flutter", "mobile observability Flutter", "dynatrace_flutter_plugin". or Dynatrace server-side configuration.
>- 3rd-party test and monitor result ingestion into Dynatrace Grail via the platform events ingest API (platform/ingest/custom/events/). Use when sending external synthetic test outcomes, CI monitor data, or third-party check results to Dynatrace. Covers token scope, full event schema for external_test_run and external_test_step (including dt.security_context, ci.*, trace correlation, and pipeline-added fields), curl and Java DTO examples, and DQL verification. "external test ingestion", "send synthetic results to Grail", "push external test data to Dynatrace", "external monitor results", "external test run event schema". Do NOT use for Dynatrace-native Synthetic Monitoring browser/HTTP checks, or Real User Monitoring (use dt-obs-frontends for RUM).
>- AWS cloud resource monitoring including EC2, RDS, Lambda, ECS/EKS, VPC networking, load balancers, S3, DynamoDB, SQS/SNS, and cost optimization. Use when analyzing AWS infrastructure, resource inventory, security compliance, capacity planning, or cost savings. "Lambda functions", "ECS services", "security groups", "unattached EBS volumes", "AWS load balancer topology", "publicly accessible databases", "AWS dashboards". Do NOT use for explaining existing queries, product documentation questions, generic host CPU/memory metrics (use dt-obs-hosts), application-level tracing (use dt-obs-tracing), or log analysis (use dt-obs-logs).
GCP cloud resources including Compute Engine, GKE, Cloud Run, Pub/Sub, VPC networking, DNS, IAM, Secret Manager, and monitoring. Monitor GCP infrastructure, analyze resource usage, audit security posture, and manage organizational hierarchy across projects and folders.
>- Analyzes observability signals from customer GenAI applications with DQL. Reads OpenTelemetry GenAI spans and LLM evaluation bizevents. (model, provider, tokens); cost/token analytics, usage attribution, and prompt caching; agent signals (tool calls, steps, failures, loop detection, Smartscape topology); conversation/session analytics; guardrails (blocked/truncated responses); and evaluation signals (quality, pass/fail). "cost per conversation", "who is driving token spend", "do I have prompt caching", "failing agent tool calls", "find runaway agents", "responses truncated or blocked", "failed evaluations", "am I hitting rate limits", "token throughput / TPM", "provider throttling or 429s". metrics (dt-obs-services), logs (dt-obs-logs), or non-GenAI tracing (dt-obs-tracing).
>- Host and process metrics including CPU, memory, disk, network, containers, and process-level telemetry. Use when analyzing infrastructure health, resource utilization, process consumption, or host discovery. Also use when building timeseries queries for host metrics that feed into analytical workflows like anomaly detection, forecasting, or seasonality analysis. "host with most free disk", "top hosts by CPU", "top processes by memory", "Linux hosts in AWS", "what databases are running", "infrastructure costs by cost center", "hosts running EOL Java", "container monitoring", "listening ports", "process resource consumption", "CPU forecast", "memory anomaly", "host seasonality". Do NOT use for explaining existing queries, product documentation questions, Kubernetes pod/workload queries (use dt-obs-kubernetes), AWS cloud resource inventory (use dt-obs-aws), or service-level metrics (use dt-obs-services).
Set up the Dynatrace iOS SDK (OneAgent) in an iOS project using Swift Package Manager. Automates adding the SPM dependency, creating a Dynatrace.plist configuration file, adding the import statement, adding privacy opt-in code, and building the project. Use this skill when the user wants to integrate, install, add, or set up Dynatrace monitoring in their iOS app. Keywords: Dynatrace, iOS, SDK, OneAgent, setup, install, integrate, SPM, Swift Package Manager, Info.plist, DTXApplicationID, DTXBeaconURL, mobile monitoring, RUM.
>- Kubernetes cluster, pod, node, and workload monitoring. Use when analyzing K8s health, resource optimization, pod failures, OOMKills, scheduling, or security posture. Also use for Kubernetes operational events like pod restarts, OOM events, evictions, and cluster event history. "namespace resource usage", "over-provisioned pods", "privileged containers", "pod placement", "K8s node capacity", "running containers by cluster", "workload scheduling", "pod evictions", "K8s labels and annotations", "kubernetes events", "pod restart events", "OOM events", "K8s event history". Do NOT use for explaining existing queries, product documentation questions, AWS-specific resource queries, service-level RED metrics, distributed tracing, or log analysis — use the relevant skill instead.
Predictive analytics for Dynatrace — time series forecasting with the timeseries-forecast tool, capacity saturation planning, trend and anomaly detection across hosts, services, and infrastructure.
>- Log querying, filtering, pattern analysis, and error rate calculation. Use when searching application or infrastructure logs, analyzing error patterns, or correlating log data. "logs from last hour", "find log entries", "top error messages", "log patterns", "parse JSON logs", "logs by process group", "log trends over time", "log entry counts per minute". Do NOT use for explaining existing queries, product documentation questions, distributed tracing or span analysis (use dt-obs-tracing).
Suggest and validate semantic dictionary (SD) mappings for audit log integrations using raw vendor log payloads or live ingested events. Use when: mapping a vendor audit log feed, authentication logs, user activity logs to the Dynatrace SD; checking required semantic fields; proposing OpenPipeline processor extraction rules based on DQL; running runtime validation (fetches live logs by log.source, then applies static validation).
>- DAVIS problem analysis including root cause identification, impact assessment, and correlation with other telemetry. Use when querying or investigating detected problems. "list problems", "P-12345 details", "recurring problems", "problem history", "problem trending", "blast radius", "which entity caused the problem", "problems affecting Kubernetes", "problems by service". Do NOT use for explaining existing queries, product documentation questions, generic log searching, distributed tracing, or host-level resource monitoring.
>- Integrate the Dynatrace React Native Plugin into a React Native or Expo project — dependency setup, dynatrace.config.js, Babel registration, npx instrumentation, navigation tracking, user privacy options, and verification. Handles both bare React Native and Expo (babel-preset-expo) Babel configuration automatically. "integrate Dynatrace RN", "mobile observability React Native", "react-native-plugin", "dynatrace react native", "add Dynatrace to Expo", "instrument Expo app", "Dynatrace Expo setup". or Dynatrace server-side configuration.
>- Service performance monitoring with RED metrics (Rate, Errors, Duration) and runtime-specific telemetry for Java, .NET, Node.js, Python, PHP, and Go. Use when analyzing service health, SLA compliance, or runtime issues. "service mesh overhead", "JVM GC", "Java heap", "Node.js event loop", ".NET CLR", "Python threads", "PHP OPcache", "Go goroutines", "service performance", "p95 latency", "request failures", "database response time by name". Do NOT use for explaining existing queries, product documentation questions, infrastructure metrics (use dt-obs-hosts), log analysis (use dt-obs-logs), or distributed tracing workflows (use dt-obs-tracing).
>- Distributed traces, spans, service dependencies, and request flow analysis. Use when investigating span-level details, failures, performance bottlenecks, or trace correlation. "distributed trace", "span details", "HTTP status codes in traces", "database query spans", "messaging spans", "gRPC calls", "Lambda cold starts", "trace ID lookup", "exception analysis", "correlate logs and traces", "request attributes". Do NOT use for explaining existing queries, product documentation or configuration questions, service-level RED metrics (use dt-obs-services), log searching (use dt-obs-logs), or problem analysis (use dt-obs-problems).
Query and analyze a Dynatrace tenant's ACTUAL billing and usage data with DQL against dt.system.events — DPS consumption breakdown, cost-normalized spend ranking, included volume deduction, chargeback/showback, cost drivers, spending trends, cost investigation, metrics ingest optimization, query cost attribution, workflow total cost, and entity-level cost drill-down (RUM, hosts, synthetic, K8s). Also directs licensing/entitlement questions to the right resource (not available via DQL). USE ONLY to query/analyze the tenant's actual consumption. Do NOT use for conceptual 'explain' questions about how DPS billing/pricing works or what units/weights/the rate card mean — those belong to Dynatrace documentation. Also do NOT use for making a DQL query itself faster or cheaper to run (query optimization, reducing scanned data/consumption per run, filter-early best practices) — that belongs to dt-dql-essentials. This skill only MEASURES recorded consumption; it does not tune queries.
>- Hunt threat-intelligence indicators of compromise (IoCs) across Dynatrace logs and spans and produce a 0-100 threat-exposure score. Extracts and normalizes IoCs — IPs, Domains (hostnames included), URLs, Emails, CVEs, File hashes (md5/sha1/sha256), MITRE TTPs — from unstructured reports, advisories, advisory URLs, pasted text, or STIX, then hunts them in fetch check these indicators in my logs and traces, threat exposure report, extract IoCs from this advisory URL, search these hashes/domains/IPs in my environment. Routes CVE-to-vulnerability and IP/MITRE-to-detection legs to dt-sec-insights. compliance, THREAT_REPORT — use dt-sec-insights); general log queries not tied to an IoC hunt (use dt-obs-logs); general span/trace analysis (use dt-obs-tracing); explaining DQL syntax (use dt-dql-essentials).
>- vulnerabilities, threat detections, compliance posture, and scan coverage. Covers Dynatrace-native Runtime Vulnerability Analytics (RVA — CVEs, reachability, exposure, exploit), Runtime Application Protection (RAP), Automated Detections, and Security Posture Management "open critical vulnerabilities", "vulnerable functions in use and publicly exposed", "top vulnerable libraries / K8s workloads", "CIS/DORA compliance pass rate", "SQL injection detections", "map external findings to workloads", "hosts not covered by scanning". Do NOT use for explaining existing DQL (use dt-dql-essentials), Davis problems (dt-obs-problems), logs (dt-obs-logs), distributed tracing (dt-obs-tracing), service RED metrics (dt-obs-services), or platform usage/audit telemetry (dt-platform).
>- Resolve security signals, IoC matches, or Smartscape nodes to runtime Dynatrace entities and connect findings on different entity levels through a shared runtime entity. Covers identity-to-Smartscape mapping (incl. container-image digest/ID to workload), cross-level topology (K8s pod detection vs. node CVE via pod-to-node), per-entity risk summarization, and to workloads/hosts", "which workload does this container image run as", "do these findings relate through the same runtime entity", "enrich this IoC match with entity context", "which threat report mentions this IoC". Queries security.events ONLY for THREAT_REPORT IoC enrichment (matched IoC to attributing reports); Do NOT use for broad security.events posture/overview (use dt-sec-insights), general DQL (use dt-dql-essentials), IoC hunting in logs/spans (use dt-sec-ioc-hunting), or K8s observability outside the security cross-level context (use dt-obs-kubernetes).
Suggest and validate semantic dictionary (SD) mappings for new security integrations using vendor API samples or live events. Use when: mapping a new security vendor data to Dynatrace SD; checking required fields; validating namespaces; highlighting discrepancies vs the semantic dictionary; proposing mapping improvements; running runtime validation against live tenant data.
Validate data quality in market analysis documents and blog articles before publication. Use when checking for price scale inconsistencies (ETF vs futures), instrument notation errors, date/day-of-week mismatches, allocation total errors, and unit mismatches. Supports English and Japanese content. Advisory mode -- flags issues as warnings for human review, not as blockers.
Generate Minervini-style breakout trade plans from VCP screener output with worst-case risk calculation, portfolio heat management, and Alpaca-compatible order templates (stop-limit bracket for pre-placement, limit bracket for post-confirmation). Use when user has VCP screener results and wants actionable trade plans with entry/stop/target levels and position sizing.
Fetch upcoming economic events and data releases using FMP API. Retrieve scheduled central bank decisions, employment reports, inflation data, GDP releases, and other market-moving economic indicators for specified date ranges (default: next 7 days). The script outputs raw JSON or text; the assistant filters, assesses impact, and generates the Markdown report.
Provide US dividend tax and account-location workflow for Kanchi-style income portfolios. Use when users ask about qualified vs ordinary dividends, 1099-DIV interpretation, REIT/BDC distribution treatment, holding-period checks, or taxable-vs-IRA account placement decisions for dividend assets.
Convert Kanchi-style dividend investing into a repeatable US-stock operating procedure. Use when users ask for かんち式配当投資, dividend screening, dividend growth quality checks, PERxPBR adaptation for US sectors, pullback limit-order planning, or one-page stock memo creation. Covers screening, deep dive, entry planning, and post-purchase monitoring cadence.
Comprehensive portfolio analysis using Alpaca MCP Server integration to fetch holdings and positions, then analyze asset allocation, risk metrics, individual stock positions, diversification, and generate rebalancing recommendations. Use when user requests portfolio review, position analysis, risk assessment, performance evaluation, or rebalancing suggestions for their brokerage account.
Screen US equities for parabolic exhaustion patterns and generate conditional pre-market short plans, then evaluate intraday trigger fires from live 5-min bars. Phase 1 daily 5-factor scorer (MA extension / acceleration / volume climax / range expansion / liquidity), Phase 2 per-candidate plans for ORL break / first-red 5-min / VWAP fail with explicit borrow / SSR / manual-confirmation gating, Phase 3 one-shot intraday FSM that detects trigger fires and resolves concrete share counts. Covers Phase 1 + Phase 2 + Phase 3.
This skill should be used when analyzing weekly price charts for stocks, stock indices, cryptocurrencies, or forex pairs. Use this skill when the user provides chart images and requests technical analysis, trend identification, support/resistance levels, scenario planning, or probability assessments based purely on chart data without consideration of news or fundamental factors.
Detect and analyze trending market themes across sectors. Use when user asks about current market themes, trending sectors, sector rotation, thematic investing, what themes are hot or cold, or wants to identify bullish and bearish market narratives with lifecycle analysis.
>- Recommend the right trading workflow, skillset, API profile, and setup path from a natural-language goal. Use this as the on-ramp when a user expresses a trading or investing goal and needs to know which skill/workflow to use, where to start, or whether something works without paid API keys — e.g. "where do I start", "which skill should I use", "I want to swing trade only when the market is favorable", "what works without API keys", "どれを使えばいい", "API キー無しで 使えるものは". Routes and explains only; it never executes trades or auto-runs other skills, and it is honest when no workflow has shipped yet.
Claude Skills — questions
Answers built from the skills we actually parsed.