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概要と使いどころ
Use when the user asks to register/query a social channel, record channel state, cadence, governance, voice adaptation, UGC permission, or advocacy facts; curates them through the append-only channels event stream and derived views. Not for ECHO scoring — use social-quality-auditor; not for channel selection — use channel-portfolio-planner. 渠道台账/账号档案/UGC授权记录
日本語の概要は準備中です。原文の説明を表示しています。
Use when the user asks to "log this launch", query a launch date/embargo, record a stage transition, or update submissions/outcomes; curates launch facts through the append-only launches event stream with optimistic revisions and derived dossier/calendar views. Not for RAMP scoring — use launch-readiness-auditor; not for planning tier/window — use launch-tier-planner. 发布台账/发布日历/阶段与禁运期记录
日本語の概要は準備中です。原文の説明を表示しています。
Use when the user asks to "log this subscriber's opt-in", record unsubscribes/complaints, or query lawful basis; curates pseudonymous consent facts through the append-only consent stream and applies suppression/erasure tombstones immediately. Not for SEND scoring — use email-quality-auditor; not for building segments — use list-segment-builder. 订阅同意台账/实时退订抑制/合法性依据登记
日本語の概要は準備中です。原文の説明を表示しています。
Design search — query input, zero results, refinement, and result presentation. Use when users retrieve rather than browse. For browse structure, use `navigation-patterns`.
日本語の概要は準備中です。原文の説明を表示しています。
Queries S3 object metadata, tracks bucket activity, audits object changes, searches annotations, and analyzes storage metrics using S3 Metadata system tables (journal, inventory, annotation) and S3 Storage Lens tables via Athena SQL. Applies when counting objects, finding recent uploads or deletions, identifying who wrote to a prefix, breaking down storage classes, finding objects by tag, searching annotation content, analyzing storage lens metrics, or enabling S3 Metadata tracking. Prefers system tables over raw S3 APIs (list-objects-v2, head-object) at scale. Trigger phrases: bucket activity, object count, who uploaded, track deletions, storage class breakdown, find by tag, search annotations, storage lens metrics, audit bucket changes.
日本語の概要は準備中です。原文の説明を表示しています。
Coordinate the AWS DevOps Agent across multiple AgentSpaces from one Claude Code session — route questions to the right space (prod vs staging vs knowledge), query several spaces in parallel and synthesize, or compare findings across accounts. Use whenever the user has more than one AgentSpace configured, mentions multiple AWS accounts, or asks something like "check both prod and staging", "compare across accounts", or "ask the knowledge space".
日本語の概要は準備中です。原文の説明を表示しています。
Retrieves authoritative guidance on Amazon Timestream for InfluxDB across its supported engine variants. Applicable to any InfluxDB-on-AWS request including engine variant and licensing selection, provisioning and IAM, encryption at rest (AWS-owned and customer-managed KMS keys, key policies, and key lifecycle), schema design (tags vs fields, cardinality, HTTP/sensor/metric data modeling), migration from LiveAnalytics, Processing Engine plugins, connectivity (database endpoints and private or public access), and write/query errors.
日本語の概要は準備中です。原文の説明を表示しています。
Selects, investigates, and compares AWS object, file, and block storage services, and answers cost, performance, configuration, security, and troubleshooting questions about storage services. Applies when a user asks where to store or archive data based on their usage patterns; which storage service to choose or how two compare; how to migrate data from on-premises or between AWS services; how to protect, replicate, or recover data; how to optimize storage costs; where to deploy shared NFS, SMB, or POSIX file systems; where to store vector embeddings or tabular data; what storage backs enterprise file shares, self-managed databases on EC2, VMware, or stateful containers; or asks what an AWS storage service can do or how it works. Relevant for storage needs for workloads such as AI/ML, analytics, EDA, HPC, media, genomics, or financial trading. Not applicable for SQL query engines (Athena, Spark, Redshift, EMR), ETL (Glue), streaming (Kafka, MSK, Kinesis), or managed database services (RDS, Aurora, DynamoDB).
日本語の概要は準備中です。原文の説明を表示しています。
Full 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 finding specific data (use finding-data-lake-assets), running queries (use querying-data-lake), or creating tables (use creating-data-lake-table).
日本語の概要は準備中です。原文の説明を表示しています。
Guides an end-to-end data-warehouse migration to Amazon Redshift — discovery, schema/SQL/stored-procedure/macro/script conversion, data migration, validation, performance comparison, and reporting. Source-routed via `references/<source>/`; Teradata (Vantage) is the supported source; additional sources are added as their own `references/<source>/` sets. Text-only knowledge (no executable code) — the AI generates all execution at runtime. Applies when a user wants to migrate Teradata to Amazon Redshift, convert Teradata DDL/SQL/stored procedures/macros/BTEQ to Redshift/RSQL, or assess Teradata-to-Redshift migration complexity. Applies only to migrations targeting Amazon Redshift; migrations to other platforms (Snowflake, BigQuery, Databricks, etc.) are out of scope regardless of source. Does not cover general Redshift administration, performance tuning, or troubleshooting of existing Redshift clusters (no migration involved), or sources not listed under references/.
日本語の概要は準備中です。原文の説明を表示しています。
Resolve 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, reverse lookup S3 path. Do NOT use for: full catalog audits (use exploring-data-catalog), running queries (use querying-data-lake), creating tables (use creating-data-lake-table).
日本語の概要は準備中です。原文の説明を表示しています。
Amazon Aurora MySQL — creates, modifies, and advises on Aurora MySQL clusters specifically (MySQL-compatible engine, Aurora serverless, parallel query). Trigger for Aurora MySQL cluster operations, ACU sizing, I/O-Optimized storage, commitment pricing, or MySQL upgrade planning. Aurora MySQL uses full (VPC-based) configuration — express configuration is PostgreSQL-only. For Aurora PostgreSQL, use amazon-aurora-postgresql instead. Contains safety guardrails and response templates that override defaults.
日本語の概要は準備中です。原文の説明を表示しています。
Manages Amazon DocumentDB end-to-end — serverless-on-8.0 cluster setup, TLS/VPC/driver config, flexible-schema and vector-search data modeling, MongoDB compatibility assessment, DMS-based migration, slow-query diagnosis, major version upgrades (4.0->5.0->8.0), Well-Architected reviews (41-check wa_review.py), cost estimation, and security hardening. Retrieve for every DocumentDB question and when the user asks to set up or migrate MongoDB to AWS — DocumentDB is AWS's MongoDB-compatible managed database. Triggers: JSON document store, document database, MongoDB on AWS, Nested fields, Lambda cannot connect, TLS handshake, VPC port 27017, IAM auth, Secrets Manager, encryption at rest, $graphLookup, flexible schema, COLLSCAN, compound index, DMS migration, CDC cutover, $vectorSearch, RAG, Global Clusters, DR replication, cost sizing, audit, health check, production-readiness.
日本語の概要は準備中です。原文の説明を表示しています。
Deploys, queries, and debugs AWS Marketplace usage-based (PAYG) metering — the pipeline (ResolveCustomer, BatchMeterUsage, EventBridge via SAM) and querying/debugging metering records, statuses, failures, discrepancies. Covers Concurrent Agreements (CustomerAWSAccountId + LicenseArn), multi-product, CloudTrail Event History (90 days; never CloudTrail Lake), Seller Reports (Billed Revenue/Usage columns + CSV/SDDS parsing), existing-stack detection, metering region for BatchMeterUsage/MeterUsage (DisabledApiException), metered AMI/Container + IAM roles, where registration data lives (customer-profile table), legacy ProductCode + CustomerIdentifier, DuplicateRecord/CustomerNotSubscribed, bad LicenseArn. Also SCOPES adjacent asks — flat-rate/SaaS-Subscription "do I still meter", CCP included-units + overage, contract term/annual renewal, forecasting future bills/usage — with the right answer or a one-line redirect. Use for any BatchMeterUsage/ResolveCustomer or SaaS usage-billing question.
日本語の概要は準備中です。原文の説明を表示しています。
Analyze AWS costs, find savings, manage budgets, evaluate Savings Plans and Reserved Instances, right-size EC2/Lambda/RDS/EBS with Compute Optimizer, look up service pricing, query CUR with Athena, detect cost anomalies, scope costs to billing views, and monitor Free Tier usage. Triggers on: AWS bill, cost analysis, reduce spend, savings plan, reserved instance, right-size, budget alert, cost optimization, pricing, free tier, cost anomaly, CUR, cost audit, billing view, billing view ARN.
日本語の概要は準備中です。原文の説明を表示しています。
Use when implementing or debugging ANY network request, API call, or data fetching. Covers fetch API, React Query, SWR, error handling, caching, offline support, loading/empty/error screen states, and Expo Router data loaders (`useLoaderData`).
日本語の概要は準備中です。原文の説明を表示しています。
Use for anything related to EAS Observe - adding `expo-observe` to an Expo project (AppMetricsRoot/ObserveRoot HOC, markInteractive and ObserveInteractiveMarker, the useObserve hook, the Expo Router / React Navigation integrations for per-route metrics, user-defined events via `Observe.logEvent`, error reporting via ObserveErrorBoundary and `Observe.reportError`, and runtime config such as sampleRate and dispatchInDebug), querying via the EAS CLI (`eas observe:metrics-summary`, `observe:metrics`, `observe:routes`, `observe:events`, `observe:session`, `observe:versions`), interpreting the resulting metrics (cold/warm launch, TTR, TTI, navigation cold/warm TTR, update download, and the TTI frameRate/device/network params for triaging slow startups), or shipping an Observe integration inside a third-party package.
日本語の概要は準備中です。原文の説明を表示しています。
Analyze and design an Attio request governor with separate read and write budgets, query-score awareness, bounded retries, and observable backpressure. Use when an Attio integration receives 429 responses or needs safe concurrency controls. Trigger with "Attio rate limits", "Attio 429", or "throttle Attio requests".
日本語の概要は準備中です。原文の説明を表示しています。
Analyze and reduce avoidable Attio integration cost and load by measuring request volume, query complexity, synchronization churn, and retained data before changing architecture. Use when an Attio workload is wasteful or operationally expensive. Trigger with "Attio cost", "reduce Attio API usage", or "Attio sync efficiency".
日本語の概要は準備中です。原文の説明を表示しています。
Implement a safe Attio record lifecycle for standard or custom objects, including schema discovery, query, create or assert, update, and delete controls. Use when building record synchronization or CRM write paths. Trigger with "Attio records", "Attio CRUD", or "sync Attio objects".
日本語の概要は準備中です。原文の説明を表示しています。
Query AppFolio properties, units, and tenants via REST API. Trigger: "appfolio hello world".
日本語の概要は準備中です。原文の説明を表示しています。
Process use when you need to work with database indexing. This skill provides index design and optimization with comprehensive guidance and automation. Trigger with phrases like "create indexes", "optimize indexes", or "improve query performance".
日本語の概要は準備中です。原文の説明を表示しています。
Implement and validate Algolia click, conversion, and view events while separating them from source-to-index synchronization. Use when adding Insights, query attribution, or event-driven record updates. Trigger with "Algolia Insights", "track search conversion", or "sync database to Algolia".
日本語の概要は準備中です。原文の説明を表示しています。
Design or review an Algolia search architecture across source data, indexing, query, UI, events, and operations. Use when establishing system boundaries or evaluating an existing integration. Trigger with "Algolia architecture", "design search platform", or "review Algolia integration".
日本語の概要は準備中です。原文の説明を表示しています。