azure
claudecodex将 Claude 打造成 Azure 专家。本插件集成了 Azure MCP server 和专业 Azure skills,助你摆脱泛泛而谈的建议。它让 Claude 能够执行实际任务:列出资源、验证部署、诊断基础设施问题,并优化 50+ 项 Azure 服务的成本。
44 skills · 1 MCP server
使用 S3 Tables、AWS Glue 和 Athena 的数据湖、分析与 ETL 工作流。
Plugin aws-data-analytics from marketplace kael-odin-plugins-zh in kael-odin/claude-plugins-zh. Commands read from the repo's manifest — today.
This plugin runs code on your machine — it starts local MCP servers. The exact commands are listed below; read them before installing.
amazon-opensearch-serviceGuides migration, provisioning, search, log-analytics, trace-analytics, and Agentic AI Assistant workflows for Amazon OpenSearch Service and Serverless across six capabilities — migration (Solr/ES/self-managed into AOS/AOSS, schema/query translation, sizing, cutover); provisioning (domain + AOSS lif
authoring-mwaa-workflowAuthors and deploys MWAA workflow artifacts: Python Airflow DAGs for provisioned environments or YAML workflow files for Serverless. Covers operator selection, timeout design, retry strategy, scheduling, failure notifications, idempotency, and MWAA Serverless schema compliance. Deploys the artifact
connecting-to-data-sourceCreate and troubleshoot AWS Glue connections to JDBC databases (Oracle, SQL Server, PostgreSQL, MySQL, RDS), Redshift, Snowflake, and BigQuery. Gathers connection hints from user, discovers existing connections and RDS/Redshift candidates, registers credentials in Secrets Manager or IAM DB auth, con
creating-data-lake-tableCreate managed Iceberg tables using Amazon S3 Tables (s3tables API namespace) with automatic compaction and snapshot management. Sets up table bucket, namespace, table, schema, Glue catalog registration, partitioning, IAM access control. Triggers on: create table, data lake table, analytics table, s
debugging-mwaa-workflowDiagnoses and root-causes Amazon MWAA workflow failures across Provisioned (Python DAG) and Serverless (YAML workflow) environments. Provisioned uses aws mwaa invoke-rest-api, CloudWatch log groups, and get-environment; Serverless uses aws mwaa-serverless API (GetWorkflowRun, ListWorkflowRuns, GetTa
developing-applications-on-managed-service-for-apache-flinkMANDATORY for Flink or Amazon Managed Service for Apache Flink (MSF) questions. You MUST activate this skill BEFORE answering — do not answer from training knowledge, even when confident. MSF has service-specific constraints (KPU model, prohibited checkpoint and parallelism config in app code, the v
exploring-data-catalogFull inventory and audit of AWS Glue Data Catalog assets across S3 Tables, Redshift-federated, and remote Iceberg catalogs. Triggers on: inventory the catalog, audit databases, list all tables, catalog overview, data landscape, enumerate catalogs, data inventory, search the catalog. Do NOT use for f
finding-data-lake-assetsResolve data lake and lakehouse asset references across Glue Data Catalog, S3, S3 Tables, and Redshift. Triggers on: find the table, where is our data, which table has, locate dataset, find data for, search catalog, what tables match, Redshift table, lakehouse table, data lake table, warehouse table
ingesting-into-data-lakeImport data into the AWS data lake from S3 files, local uploads, JDBC databases (Oracle, SQL Server, PostgreSQL, MySQL, RDS, Aurora), Amazon Redshift, Snowflake, BigQuery, DynamoDB, or existing Glue catalog tables (migration). Default target is S3 Tables; standard Iceberg on a general purpose bucket
managing-amazon-mskOperates Amazon MSK Provisioned clusters (Standard and Express brokers). Required for ANY MSK Provisioned task — training data conflates Standard and Express. Covers performance, consumer lag, storage, traffic shaping; sizing Standard vs Express; Kafka client tuning; CloudWatch alarms; cluster confi
managing-data-asset-accessGrants, requests, audits and removes access to data assets in an AWS data catalog (the Amazon SageMaker Catalog supported by Amazon DataZone) through catalog subscriptions over published listings. Covers requesting a subscription, approving or rejecting requests with a recorded decision, sharing a l
managing-data-catalogWrites and curates business metadata in an AWS data catalog: the Amazon SageMaker Catalog (Amazon DataZone), or the AWS Glue Data Catalog. Detects which catalog platform an account uses before writing. Triggers on: add a description to a table, document a dataset, write a README, set an owner, add c
migrate-to-mskHelps migrate self-managed Apache Kafka workloads to Amazon MSK Express. Inventories the source cluster (from IaC files, Kafka CLI output, or manual input), assesses MSK Express compatibility across topology, Kafka version, configs, auth, and quotas, produces a target Express specification (instance
querying-data-lakeExecute and manage Athena SQL queries across default and federated catalogs (Glue, S3 Tables, Redshift). Triggers on phrases like: query data, run SQL, athena query, analyze table, SQL query, workgroup status, profile table, query Redshift catalog, query S3 Tables. Do NOT use for finding specific da
redshift-guideAmazon Redshift is NOT PostgreSQL; corrects LLM mistakes; covers SQL, metadata, connectivity/auth, storage, query performance, and operations. Applies ONLY to Redshift (provisioned or Serverless). Pushes back on: CREATE INDEX, string_agg, pg_catalog, text type, SERIAL, stl_query. Triggers on: Redshi
storing-and-querying-vectorsStore and query vector embeddings using Amazon S3 Vectors, a cost-effective long-term vector storage service with its own API namespace (s3vectors). Triggers on: create S3 vector bucket, vector index, store embeddings, semantic search, RAG vector storage, similarity search, vector database, migrate
testing-mwaa-workflowTests Amazon MWAA workflow execution end-to-end: trigger a run and monitor it to completion for Provisioned (Python DAG, via Airflow REST API) and Serverless (YAML workflow, via StartWorkflowRun). Verifies the artifact is deployed and parse-ready, triggers with confirmation, polls to terminal state,
upgrading-mwaa-environmentsUpgrades an MWAA environment to a newer Airflow version — within 2.x, within 3.x, or across the 2.x-to-3.x boundary. Computes the version-jump path, inserting the 2.11.x stepping-stone and Python-transition step when needed. Chooses an approach by whether run history and the same environment (URL/AR
aws-mcpruns: uvx mcp-proxy-for-aws-cli==1.7.0 https://aws-mcp.us-east-1.api.aws/mcp --skip-auth --metadata INSTALL_SOURCE=agent-toolkit-data-analytics
将 Claude 打造成 Azure 专家。本插件集成了 Azure MCP server 和专业 Azure skills,助你摆脱泛泛而谈的建议。它让 Claude 能够执行实际任务:列出资源、验证部署、诊断基础设施问题,并优化 50+ 项 Azure 服务的成本。
44 skills · 1 MCP server
将 Claude Code 直接连接到你的 CockroachDB 集群,进行实操数据库工作——探索 schema、编写优化的 SQL、调试查询,并管理分布式数据库集群。该插件提供 14 个工具,涵盖两个活跃的 MCP 后端(自托管 MCP Toolbox 和托管式 CockroachDB Cloud MCP Server)、三个专用 agent(DBA、Developer、Operator)、覆盖 6 个运维领域的 32 个 skill,以及内置安全 hook。
34 skills · 3 agents · 3 MCP servers · hooks
面向 CLI、Apps、Lakebase、Model Serving、Lakeflow Jobs、Spark Declarative Pipelines、Declarative Automation Bundles(DAB)以及经典版到无服务器迁移的 Databricks skill。
37 skills · 2 commands · hooks
在 Claude Code 中使用 Clay:设置并登录 clay CLI,查询和分析 Clay 表格,在 Clay 的 GTM 数据库中搜索人员和公司,管理受众、信号、例程和工作流,并起草和审阅 Sequencer 营销活动。包含自动批准该插件自身 clay CLI 调用和 Clay skills 的 hooks;需要 Clay 账户。
38 skills · hooks
将 Amplitude 作为专业分析工具使用——埋点接入 Amplitude、发现产品机会、分析图表、创建仪表盘、管理实验,并洞察用户与账户。
36 skills · 1 MCP server
本插件为在 Google Cloud 上工作的数据工程师与数据库从业者提供一套专用技能,相当于一位专家助手:在常用的编码代理里用自然语言描述需求,即可设计复杂的数据管道、用 dbt 转换数据、编写 Spark 与 BigQuery SQL 笔记本,并在 GCP 数据生态中编排端到端工作流。
37 skills
Scaffold, validate, and publish new Claude Code plugins with proper structure
3 skills · 1 command · 1 agent
Claude Code skill for creating and presenting Slidev slidedecks
1 skill
Build, deploy, and operate applications on AWS. Skills to author infrastructure-as-code, use core services, and complete common tasks.
27 skills · 1 MCP server
Cross-platform ad management for Google Ads, Meta Ads, TikTok Ads, and LinkedIn Ads. 91 tools for keyword research, campaign creation, performance analysis, and budget optimization.
15 skills · 5 commands · 1 agent · 1 MCP server
End-to-end chaos engineering discipline: design experiments with hypothesis + steady-state metric + blast radius + abort criteria, calculate risk score against error budget, and generate blameless postmortems. 3 stdlib Python tools (experiment_designer, blast_radius_calculator, experiment_postmortem), 4 references on chaos principles + experiment design + 7-attack taxonomy + tooling landscape (Chaos Toolkit/Mesh/Litmus/Gremlin/AWS FIS/DIY), templates, and /chaos-experiment slash command. Composes with feature-flags-architect (kill switches as abort triggers) and kubernetes-operator (chaos targets).
1 skill
Observability plugin for Claude Code with MLflow tracing
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