112 个 ・ 集成工具: Snowflake · 按人气排序
Data leadership advisor on data strategy, governance, quality, and platform decisions. Use when defining a data strategy, scoring data maturity, auditing data governance, evaluating a data platform, or designing the data org.
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用于公开资料检索、社交媒体分析、地理定位、DNS、用户名枚举、反向图片搜索、历史快照、公开记录与坐标识别等 OSINT 类 CTF 题;触发名:ctf-osint
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Expert knowledge for Azure Data Factory development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when configuring IR/SSIS/SHIR, mapping data flows, SAP/SaaS connectors, CI/CD deployments, or secure VNets/Key Vault, and other Azure Data Factory related development tasks. Not for Azure Data Explorer (use azure-data-explorer), Azure Synapse Analytics (use azure-synapse-analytics), Azure Stream Analytics (use azure-stream-analytics), Azure Databricks (use azure-databricks).
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Expert knowledge for Azure Energy Data Services development including troubleshooting, decision making, architecture & design patterns, security, configuration, integrations & coding patterns, and deployment. Use when configuring ADME metrics/CORS, choosing tiers, using DDMS/RAFS/Seismic APIs, securing legal tags/ACLs, or deploying GCZ on AKS, and other Azure Energy Data Services related development tasks. Not for Azure Data Explorer (use azure-data-explorer), Azure Synapse Analytics (use azure-synapse-analytics), Azure Data Factory (use azure-data-factory), Azure Databricks (use azure-databricks).
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Generate a Disaster Recovery plan with RTO/RPO targets. Use when someone asks to "create a DR plan", "disaster recovery", "business continuity", or "RTO RPO". Do NOT use for step-by-step restoration runbooks — use /pmstudio-recovery instead. Designed for SaaS platform products where Coco Inc is the customer — focuses on service continuity, data recovery, and vendor dependency management rather than infrastructure rebuild.
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Build cost-safe geospatial SQL for BigQuery, DuckDB, Snowflake, Wherobots, and Postgres and/or render results on an interactive Dekart map.
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Core distributed systems patterns - load balancing, caching, sharding, consistent hashing, message queues, rate limiting, CDN, Bloom filters, ID generation, replication, conflict resolution, CAP theorem
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Data architecture patterns (warehouse, lake, lakehouse, mesh), ETL/ELT pipelines, streaming architectures, scaling strategies, and schema design patterns
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Transform raw data into analytical assets using ETL/ELT patterns, SQL (dbt), Python (pandas/polars/PySpark), and orchestration (Airflow). Use when building data pipelines, implementing incremental models, migrating from pandas to polars, or orchestrating multi-step transformations with testing and quality checks.
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Strategic guidance for designing modern data platforms, covering storage paradigms (data lake, warehouse, lakehouse), modeling approaches (dimensional, normalized, data vault, wide tables), data mesh principles, and medallion architecture patterns. Use when architecting data platforms, choosing between centralized vs decentralized patterns, selecting table formats (Iceberg, Delta Lake), or designing data governance frameworks.
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Strategic guidance for operationalizing machine learning models from experimentation to production. Covers experiment tracking (MLflow, Weights & Biases), model registry and versioning, feature stores (Feast, Tecton), model serving patterns (Seldon, KServe, BentoML), ML pipeline orchestration (Kubeflow, Airflow), and model monitoring (drift detection, observability). Use when designing ML infrastructure, selecting MLOps platforms, implementing continuous training pipelines, or establishing model governance.
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SQL query review for correctness, performance, and best practices. Activate when a query needs review before production use, shows unexpected results, or runs too slowly.
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Learn from public breach disclosures — extract the audit question each one implies and check your own stack. Capital One IMDS abuse, LastPass vault exfiltration, Okta Lapsus$, Snowflake credential reuse, MOVEit, SolarWinds, Equifax, Target POS, Codecov, Uber, Twilio — what would you check now if your boss said 'could that happen to us?' Use when the user mentions 'breach analysis,' 'lessons learned,' 'security postmortem,' 'breach patterns,' 'breach lessons,' 'has this happened to us,' 'apply breach lessons,' 'preempt breaches,' 'security retrospective,' 'real-world security incidents,' or wants to harden against known attacker playbooks.
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Secure authentication patterns (OWASP, NIST). Use for login, registration, password reset, sessions, JWT, OAuth, MFA, passkeys.
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Pre-deployment security audit organized by OWASP Top 10. Use when reviewing code before shipping or going to production.
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Build managed ingestion pipelines into Databricks using Lakeflow Connect. Use when ingesting from SaaS apps (Salesforce, Workday Reports, ServiceNow, Google Analytics 4, HubSpot, Confluence) or databases (SQL Server cloud and on-prem; PostgreSQL/MySQL CDC in PuPr) into Unity Catalog with serverless pipelines.
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Apache Iceberg tables on Databricks — Managed Iceberg tables, External Iceberg Reads (fka Uniform), Compatibility Mode, Iceberg REST Catalog (IRC), Iceberg v3, Snowflake interop, PyIceberg, OSS Spark, external engine access and credential vending. Use when creating Iceberg tables, enabling External Iceberg Reads (uniform) on Delta tables (including Streaming Tables and Materialized Views via compatibility mode), configuring external engines to read Databricks tables via Unity Catalog IRC, integrating with Snowflake catalog to read Foreign Iceberg tables
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主要データウェアハウス方言で正確かつ高性能なSQLを記述するスキル。 「SQLを書いて」「クエリを最適化して」「BigQueryで集計」等のリクエストで発動。
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BigQuery/Snowflake接続、EDA、可視化、Marimoノートブック作成を行うサブエージェント。 データ分析関連の4つのルール（data_analysis, visualization, notebook, marimo_variable_naming）を統合。 「データ分析して」「BigQueryに接続」「EDAを実行」「Marimoで分析」等のリクエストで発動。
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This skill should be used when the user asks to "create a plot arc", "story structure", "add a plot point", "story timeline", "track foreshadowing", "pacing", "sagging middle", "act structure", "story arc", "plot outline", "snowflake method", or wants to plan and manage the narrative structure of a story. It owns book-level pacing; NOT for the craft of scene outcomes or chapter hooks, which this skill only plans in the outline (use scene-craft), or a pacing check as a revision pass (use revision-continuity).
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Generate or improve a company-specific data analysis skill by extracting tribal knowledge from analysts. BOOTSTRAP MODE - Triggers: "Create a data context skill", "Set up data analysis for our warehouse", "Help me create a skill for our database", "Generate a data skill for [company]" → Discovers schemas, asks key questions, generates initial skill with reference files ITERATION MODE - Triggers: "Add context about [domain]", "The skill needs more info about [topic]", "Update the data skill with [metrics/tables/terminology]", "Improve the [domain] reference" → Loads existing skill, asks targeted questions, appends/updates reference files Use when data analysts want Claude to understand their company's specific data warehouse, terminology, metrics definitions, and common query patterns.
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Write correct, performant SQL across all major data warehouse dialects (Snowflake, BigQuery, Databricks, PostgreSQL, etc.). Use when writing queries, optimizing slow SQL, translating between dialects, or building complex analytical queries with CTEs, window functions, or aggregations.
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Generate tailored sales assets (landing pages, decks, one-pagers, workflow demos) from your deal context. Describe your prospect, audience, and goal — get a polished, branded asset ready to share with customers.
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Master modern SQL with cloud-native databases, OLTP/OLAP optimization, and advanced query techniques. Expert in performance tuning, data modeling, and hybrid analytical systems.
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