数据分析
2,125 个结果
- Social Strategysocial-media-skillsUse to set a brand's overall social media strategy — which channels to focus on (and which to ignore), what to achieve, the angle to win, and a realistic operating cadence. The top-level plan that sits above content pillars and the calendar.
- Threads Growthsocial-media-skillsThe Threads account-growth strategy skill -- the channel layer above threads-post. Use when someone wants to grow a Threads account, understand the Threads algorithm, fix reach, plan cadence, or set a Threads strategy.
- Viral Reverse Engineeringsocial-media-skillsUse to reverse-engineer why a piece of content went viral (or overperformed) — yours or someone else's — and extract the repeatable mechanism to apply to your own content. Run when the user says "why did this go viral," "break down this viral post/video," "reverse engineer," "what made this work," or wants to learn from viral content.
- X Growthsocial-media-skillsThe X/Twitter growth playbook for 2026. Use when someone wants to "grow on X / Twitter," "get more reach/followers/impressions on X," "an X content/posting strategy," "should I get X Premium," "how the X algorithm works," or how to use replies/quote-posts/long-form/video to grow.
- Youtube Long Formsocial-media-skillsThe growth engine for YouTube long-form video in 2026. Use when someone asks to "grow my YouTube channel," "get more views on my videos," "plan/script a YouTube video," "improve my CTR or retention," "why did my video flop," or wants a long-form strategy.
- Youtube Shortssocial-media-skillsThe growth engine for YouTube Shorts in 2026. Use when someone asks to "grow on Shorts," "get views on YouTube Shorts," "write a Shorts script," "why did my Short flop," "make a vertical YouTube video," or wants a Shorts strategy. Drafts the script; the human films/ edits; publishing routes through scheduling-and-queue -> WoopSocial; analytics are read natively in YouTube Studio.
- Net ObservabilitymitkoxImplement observability patterns with OpenTelemetry, structured logging, and distributed tracing
- Agent Observability Eval PipelineDatadog LabsEnd-to-end Agent Observability pipeline for an instrumented ml_app — classify production traces, root-cause failures, bootstrap evaluators, then (optionally) sample + publish a dataset, generate + run an experiment, and analyze results. Six narrated phases with a standardized banner and a "continue" checkpoint between each.
- Agent Observability Experiment BootstrapDatadog LabsBootstrap a reproducible LLM Observability experiment through the Python ddtrace SDK or the Node dd-trace SDK. Use for experiment, dataset, evaluator, benchmark, regression, or LLM-as-a-judge scaffolding. The legacy Python invocation remains supported.
- Dd Browser SdkDatadog LabsDatadog Browser SDK — RUM, Logs, Session Replay, profiling, product analytics, and error tracking setup, configuration, and migration. Use when upgrading Browser SDK versions, setting up RUM or Logs, or troubleshooting browser-side Datadog instrumentation.
- Quantitative Researchomer-metinWorld-class systematic trading research - backtesting, alpha generation, factor models, statistical arbitrage. Transform hypotheses into edges. Use when "backtest, alpha, factor model, statistical arbitrage, quant research, systematic trading, mean reversion, momentum strategy, regime detection, walk forward, " mentioned.
- Technical Analysisomer-metinMaster of price action, chart patterns, and technical indicators - combining classical Wyckoff/Dow theory with modern quantitative validation for edge identificationUse when "technical analysis, chart pattern, indicator, RSI, MACD, support resistance, trend, candlestick, price action, fibonacci, trading, technical-analysis, charts, indicators, price-action, patterns, support-resistance…
- Design Doc MermaidspillwavesolutionsCreate Mermaid diagrams (flowchart, sequence, class, ER, state, C4, architecture) from text or source code. Default for GitHub wiki. Use when asked to create a diagram, generate mermaid, document architecture, or convert code to diagram. PlantUML is only for leftover types. Confluence needs PNG/SVG as well as the fence.
- C NotionDaxManage Notion pages and databases from the CLI using notion-cli. Create, read, search, and update pages. Query databases, add entries, and manage blocks and properties.
- NotionOpenHandsCreate, search, and update Notion pages/databases using the Notion API. Use for documenting work, generating runbooks, and automating knowledge base updates.
- D3 VisualizationlyndonklUse when creating custom, interactive data visualizations with D3.jsâbuilding bar/line/scatter charts from scratch, creating network diagrams or geographic maps, binding changing data to visual elements, adding zoom/pan/brush interactions, animating chart transitions, or when chart libraries (Highcharts, Chart.js) don't support your specific visualization design and you need low-level control…
- Redis ClusteringRedisRedis Cluster and replication guidance covering hash tags for multi-key operations, avoiding CROSSSLOT errors, and reading from replicas to scale read-heavy workloads. Use when designing keys for a sharded Redis Cluster, debugging CROSSSLOT errors on MGET / SDIFF / pipelines, configuring a multi-key transaction in a cluster, or routing reads to replicas for caches, analytics, or dashboards.
- DeslopifyjuliusbrusseeDe-slop pass for any text. Scans for the statistical fingerprints of AI writing (negative parallelism / "not X but Y", em-dash density, rule-of-three, false ranges, puffery vocabulary, uniform cadence, hedged both-sidesing), rewrites by meaning, then re-scans until the text is clean and sits in the right register for its genre: academic article, tweet, reddit post, email, blog, docs, marketing.
- Fuck SlopjuliusbrusseeDe-slop pass for any text: detects and erases the statistical fingerprints of AI writing (negative parallelism / "not X but Y", em-dash abuse, rule-of-three, false ranges, puffery vocabulary, uniform cadence, hedged both-sidesing) and rewrites the text into its target register — academic article, tweet, reddit post, email, blog, anything between.
- Time Series Forecasteranton-abyzovTime series forecasting with ARIMA, Prophet, LSTM, and statistical methods. Activates for "time series", "forecasting", "predict future", "trend analysis", "seasonality", "ARIMA", "Prophet", "sales forecast", "demand prediction", "stock prediction". Handles trend decomposition, seasonality detection, multivariate forecasting, and confidence intervals with SpecWeave increment integration.
- Cn Statsaahl中国国家统计局公开数据查询技能，当用户想查询经济、CPI、GDP、人口、房价指数等数据时触发。
- Langsmith Datasetlangchain-aiINVOKE THIS SKILL when creating evaluation datasets, uploading datasets to LangSmith, or managing existing datasets. Covers dataset types (final_response, single_step, trajectory, RAG), CLI management commands, SDK-based creation, and example management. Uses the langsmith CLI tool.
- Xiaohongshu Ai Creator Masterswaylq小红书 AI 自媒体博主 (小红书 AI 自媒体博主 (从业者视角) — 在小红书做『AI 赛道』内容的自媒体博主，重点是**怎么写文案、怎么制作内容**。覆盖: (a) AI 赛道选题 — AI 工具测评 / AI 绘画 / AI 教程与 prompt / AI 副业变现 / AI 资讯解读 / AI 效率，按小红书用户(偏年轻女性 + 泛知识)重构选题; (b) 文案与内容结构(核心) — 封面(第一眼/大字报/对比图)、标题(数字/痛点/好奇缺口/关键词前置)、正文(钩子开头/分点/口语化/emoji/利他价值)、标签与 SEO 关键词、CTA 与互动引导、人设 voice; (c) 内容制作工作流 — 选题(对标爆款/找选题)→标题封面→脚本或正文→制作(图文/口播/录屏/数字人)→标签发布→数据复盘迭代; (d) AI 工具用于内容生产 —…
- Miro Code Explain On BoardMiroUse when the user wants to explain or visualize a codebase on a Miro board — produces a minimal, notation-correct set of architecture / structure / behavior diagrams (flowchart, UML class, UML sequence, ERD) plus a short companion document, grounded in real repo artifacts.