「zat」の検索結果

Generate production code for Dataverse SDK using advanced patterns, error handling, and optimization techniques.

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。

Generate production-ready Python code using Dataverse SDK with error handling, optimization, and best practices

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。

Master modern SQL with cloud-native databases, OLTP/OLAP optimization, and advanced query techniques. Expert in performance tuning, data modeling, and hybrid analytical systems.

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。

Scaffolds eval.yaml test files for agent skills in the dotnet/skills repository. Use when creating skill tests, writing evaluation scenarios, defining assertions and rubrics, or setting up test fixture files. Handles eval.yaml generation, fixture organization, and overfitting avoidance. Do not use for running or debugging existing tests nor for skills authoring.

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。

LEGO Powered Up protocol context for the Megahub project. Use when working on LEGO device communication, lpfuart library, UART parsing, motor control, sensor modes, device initialization, or debugging UART noise/corruption issues.

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。

Ensure designs define trust boundaries, authn/authz responsibilities, and propagation of identity/claims across services.

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。

Detects tables created without ROW LEVEL SECURITY enabled, over-permissive policies (USING (true) / WITH CHECK (true) without owner conditions), and service_role key exposure in client code.

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。

Detects over-permissive Firestore/Storage rules (allow read, write: if true / auth-only without ownership), missing auth checks on writes, and admin SDK private key exposure to client bundles.

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。

Detect i18n/locale keys that are removed from source but remain in locale files, or keys added to locale files without source usage.

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。

Detects patterns that make tests flaky and proposes stabilization steps.

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。

パフォーマンス観点のレビューエージェント。 N+1クエリ、メモリ効率、キャッシュ戦略、可観測性の観点でコード変更を評価する。

Install or synchronize BMS差分 from a beatoraja-compatible difficulty table, optionally download missing parent songs, and place charts into matching music folders without overwriting existing files. Use for 難易度表 URL, header.json, url_diff, or beatoraja差分 installation requests; do not use for ordinary BMS library organization unrelated to a difficulty 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。

Add redaction annotations to sensitive fields in schemas to block or hash PII. Use when configuring GDPR/HIPAA compliance, protecting credentials, or blocking internal fields from materializations. Use when user says "protect PII", "hide sensitive data", "hash field", "redact field", "GDPR compliance", "don't capture field", "remove field from Estuary", or "prevent Estuary from capturing field".

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。

Diagnose and fix SSH tunnel connection issues for Estuary captures and materializations. Use when seeing tunnel failures, connection timeouts, or permission denied errors. Use when user says "SSH tunnel failed", "connection timeout via tunnel", "permission denied SSH", "tunnel not working", "network-tunnel failed", "no pubkey loaded", "bastion host not connecting", or "RSA key format".

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。

Control which fields are included or excluded in materializations using depth modes and field overrides. Use when reducing table width, including nested fields, excluding PII, or optimizing performance. Use when user says "exclude fields", "include nested field", "too many columns", "select specific fields", or "field depth".

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。

Create a BigQuery materialization to stream Estuary collections into BigQuery tables. Use when setting up BigQuery as a destination for captured data. Use when user says "send to BigQuery", "load into BigQuery", "materialize to BigQuery", or "BigQuery destination".

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。

Add or define specific fields in a collection's readSchema. Use when fields are missing from materialization field selection, pruned by complexity limit, need type refinement, need to be protected from future inference changes, or need to be required for downstream consumers. Use when user says "missing fields", "pruned fields", "field not showing up", "complexity limit", "define field in read schema", "restrict field type", or "protect field from inference".

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。

Run a comprehensive health check on a single Estuary task by combining catalog status, data flow stats, recent errors, and publication history. Use when diagnosing a task that seems broken, slow, or stuck. Use when user says "is my task healthy", "something seems wrong", "check my capture", "check my materialization", "why is data not flowing", "task health check", "diagnose my task", or "what's wrong with my pipeline".

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。

Search and analyze Estuary task logs with jq filtering. Use when investigating task failures, debugging connector errors, analyzing behavior patterns, or streaming live logs. Use when user says "check logs", "show me logs", "task failing", "why is my capture failing", "why is my materialization failing", "error messages", "why did it fail", "search task logs", "shard failed", "follow logs", "increase log level", "debug logging", "is this log message normal", "what does this message mean", "connection timeout", or "i/o timeout".

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。

Override default column types in materializations using castToString or custom DDL. Use when column type needs different precision (e.g., NUMERIC(22,6)), VARCHAR length is wrong, need JSONB instead of JSON, integers lose precision, or need to force a string representation. Use when user says "change column type", "wrong precision", "VARCHAR too short", "integer truncated", "cast to string", or "custom DDL".

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。

Create a Snowflake materialization to stream Estuary collections into Snowflake tables. Use when setting up Snowflake as a destination for captured data. Use when user says "send to Snowflake", "materialize to Snowflake", "Snowflake destination", or "load into Snowflake".

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。

Create a Redshift materialization to stream Estuary collections into Amazon Redshift tables. Use when setting up Redshift as a destination for captured data. Use when user says "send to Redshift", "materialize to Redshift", "Redshift destination", or "load into Redshift".

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。

Create a PostgreSQL materialization to stream Estuary collections into PostgreSQL tables. Use when setting up PostgreSQL as a destination for captured data. Use when user says "send to Postgres", "materialize to PostgreSQL", "Postgres destination", or "load into Postgres".

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。

Create a HubSpot materialization to write Estuary collections back into HubSpot CRM objects (Contacts, Companies, Deals, Tickets, etc). Use when setting up HubSpot as a destination for captured data. Use when user says "send to HubSpot", "materialize to HubSpot", "write back to HubSpot", or "HubSpot destination".

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。