全部能力

Core DQL syntax rules, common pitfalls, and query patterns. Load this skill when you need to write, build, or fix a DQL query — it prevents syntax errors and guides correct usage. Covers fetch commands, data models, field namespaces, time alignment, entity patterns, metric discovery, and smartscape topology navigation. Trigger: "write a DQL query", "build me a query", "DQL syntax", "how do I query logs/spans/metrics in Dynatrace", "create a timeseries", "fix my DQL", "fetch logs", "smartscapeNodes", "query optimization". Do NOT use for explaining an existing query or answering Dynatrace product questions — those do not require query-construction guidance.

A Yahoo Finance (yfinance) powered financial analysis tool. Get real-time quotes, generate high-resolution charts with moving averages + indicators (RSI/MACD/Bollinger/VWAP/ATR), summarize fundamentals, and run a one-shot report that outputs both a text summary and a Pro chart.

Set up and run experiments in LaunchDarkly. Create experiments with metrics and treatments, start iterations to collect data, and monitor results.

Distributed traces, spans, service dependencies, and request flow analysis. Use when investigating span-level details, failures, performance bottlenecks, or trace correlation. Trigger: "trace analysis", "slow requests", "failed spans", "service dependencies", "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).

Updates a presentation with new numbers — quarterly refreshes, earnings updates, comp rolls, rebased market data. Use whenever the user asks to "update the…

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. Trigger: "show hosts", "CPU usage", "memory utilization", "disk space", "high CPU", "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).

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. Trigger: "show EC2 instances", "find RDS databases", "VPC resources", "AWS cost optimization", "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).

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Precision Financial Insights - Analyze stocks, companies, and market sentiment using authoritative data. Powered by Yahoo Finance and enhanced with intelligent…

Creates, manages, and queries Arize datasets and examples. Covers dataset CRUD, appending examples, exporting data, and file-based dataset creation using the…

创建、运行和分析 Arize 实验，用于评估和比较模型性能。涵盖实验的增删改查、导出运行记录、对比结果，以及…

生成指向 Arize UI 的深链接，用于 traces、spans、sessions、datasets、labeling queues、evaluators 和 annotation configs。生成可点击的 URL，用于…

In-process ClickHouse SQL engine for Python — run ClickHouse SQL queries directly on local files, remote databases, and cloud storage without a server. Use when the user wants to write SQL queries against Parquet/CSV/ JSON files, use ClickHouse table functions (mysql(), s3(), postgresql(), iceberg(), deltaLake() etc.), build stateful analytical pipelines with Session, use parametrized queries, window functions, or other advanced ClickHouse SQL features. Also use when the user explicitly mentions chdb.query(), ClickHouse SQL syntax, or wants cross-source SQL joins. Do NOT use for pandas-style DataFrame operations — use chdb-datastore instead.

使用 Python、Jupyter 和现代数据工具实现分析、数据分析和可视化最佳实践。

Betting analysis — odds conversion, de-vigging, edge detection, Kelly criterion, arbitrage detection, parlay analysis, and line movement. Pure computation, no API calls. Works with odds from any source: ESPN (American odds), Polymarket (decimal probabilities), Kalshi (integer probabilities). Use when: user asks about bet sizing, expected value, edge analysis, Kelly criterion, arbitrage, parlays, line movement, odds conversion, or comparing odds across sources. Also use when you have odds from ESPN and a prediction market price and want to evaluate whether a bet has positive expected value. Don't use when: user asks for live odds or market data — use polymarket, kalshi, or the sport-specific skill to fetch odds first, then use this skill to analyze them.

Datadog CLI for searching logs, querying metrics, tracing requests, and managing dashboards. Use this when debugging production issues or working with Datadog…

Improve database query performance through indexing, query optimization, and execution plan analysis. Reduce response times and database load.

Design database schemas with normalization, relationships, and constraints. Use when creating new database schemas, designing tables, or planning data models for PostgreSQL and MySQL.

Calculate risk-based position sizes for long stock trades. Use when user asks about position sizing, how many shares to buy, risk per trade, Kelly criterion,…

ニュースヘッドラインを入力として18ヶ月シナリオを分析するスキル。 scenario-analystエージェントで主分析を実行し、 strategy-reviewerエージェントでセカンドオピニオンを取得。 1次・2次・3次影響、推奨銘柄、レビューを含む包括的レポートを日本語で生成。 使用例: /scenario-analyzer "Fed raises rates by 50bp" トリガー: ニュース分析、シナリオ分析、18ヶ月展望、中長期投資戦略