1,990 件 ・ 関連度順
概要と使いどころ
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 HubSpot Real-Time capture using flowctl to stream CRM data into Estuary collections. Use when setting up a HubSpot source for contacts, companies, deals, tickets, or other HubSpot resources. Use when user says "capture HubSpot", "stream from HubSpot", "HubSpot CDC", or "connect HubSpot to Estuary".
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 projections to collections to rename fields or map nested JSON paths to flat column names. Use when renaming fields for destination conventions, flattening nested paths to columns, or creating field aliases. Use when user says "rename field", "flatten nested JSON", "map JSON path to column", "field alias", or "projection".
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 ClickHouse materialization to stream Estuary collections into ClickHouse tables. Use when setting up ClickHouse as a destination for captured data. Use when user says "send to ClickHouse", "materialize to ClickHouse", "ClickHouse destination", or "load into ClickHouse".
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。
AI-driven Flutter E2E testing via VM Service CLI. Control running Flutter apps in debug mode for smoke tests, regression checks, exploratory testing, and UI automation. Trigger when user mentions E2E testing, UI automation, smoke tests, integration testing, test automation, controlling Flutter apps, VM Service interaction, debugging UI flows, automated regression testing, CI sanity checks, or testing native dialogs/permissions/WebViews. Supports stateful named instances or stateless direct URI connections. Ideal for rapid test feedback, AI agent workflows, element discovery, screenshot capture, log collection, and scriptable UI interactions (tap, scroll, enterText). Use for troubleshooting flaky tests, automating repetitive manual tests, verifying app behavior after merges, or setting up automated QA pipelines.
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。
Dart 3 modern features (through 3.10) and Effective Dart best practices including records, patterns, sealed classes, dot shorthands, null-aware collection elements, and wildcard variables. Use when adopting Dart 3.7+ syntax, using dot shorthands for enums or static members, using null-aware elements in lists or maps, using wildcard _ parameters, improving code quality, or reviewing Dart code conventions.
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 active BIRD daemon incidents across config, runtime, environment, sockets, logs, source, and tooling. Use when BIRD fails to start or reload, crashes, loses sessions/routes, behaves differently after lint passes, or when birdcc and bird -p disagree. Collect read-only evidence first, protect routing secrets, and route isolated config edits to bird-agent or pure implementation research to bird-source-explorer.
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。
Track independent contractor payments, collect W-9s, determine 1099-NEC filing requirements, and avoid penalties. Covers the $600 threshold (2025) and $2,000 threshold (2026), Jan 31 deadline, corporate exceptions, backup withholding, and penalty schedule ($60–$660/form). Trigger on "1099", "contractor payment", "do I need to file a 1099", "W-9", "independent contractor".
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。
Designs and reviews production observability for mobile apps on every stack — Flutter, native Android, native iOS, React Native and Kotlin Multiplatform. Covers crash and error reporting with usable context, breadcrumbs, structured logs, traces and custom metrics, release and cohort segmentation, correlation with backend requests, alerting thresholds, sampling and cost, and what must never be collected. Use when production problems cannot be explained from the available data, when setting up crash reporting or telemetry, or when defining release health alerts.
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。
Pre-scan decision types, collect downstream references, classify contradictions, and write propagation scan report
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 working with Detox — detox React Native testing management and analysis. Covers test configuration review, device and simulator management, build configuration analysis, test result parsing, artifact collection, and test runner integration. Use when managing Detox test suites, investigating mobile test failures, or reviewing React Native E2E testing configurations.
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 working with Coredns — coreDNS server management, zone configuration, plugin chain analysis, query logging, and cache statistics. Covers Corefile inspection, health endpoint monitoring, metrics collection, and forwarding configuration. Read this skill before any CoreDNS operations — it enforces discovery-first patterns, anti-hallucination rules, and safety constraints.
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 working with Anecdotes — anecdotes compliance automation platform for managing security programs, controls, evidence, and multi-framework compliance. Covers control monitoring, evidence automation, plugin integrations, gap analysis, and audit readiness. Use when reviewing compliance status across frameworks, tracking evidence collection, analyzing control gaps, or preparing for security compliance audits.
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 working with Appwrite — appwrite backend platform management covering project inventory, database collections, user authentication stats, storage bucket usage, function deployments, webhook configuration, and platform health. Use for comprehensive Appwrite project assessment and resource monitoring.
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 working with Aws Systems Manager — aWS Systems Manager parameter store management, session management, patch compliance tracking, and Run Command analysis. Covers parameter inventory, managed instance status, automation execution, maintenance windows, and inventory collection.
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 working with Gcp Firestore Deep — google Cloud Firestore document and collection analysis, index management, security rules review, usage monitoring, and performance diagnostics via gcloud CLI.
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 working with Mongodb — mongoDB database analysis, performance tuning, query optimization, and health monitoring. Covers collection analysis, index recommendations, aggregation pipelines, replica set health, Atlas cluster management, and slow query investigation.
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 working with Firestore — google Cloud Firestore collection analysis, index management, security rules review, usage metrics, and query optimization.
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。
A collection of methods in an intelligent software structure allows the user to focus on fine-tuning
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。
Train an OpenAmer-specific small model from the collected brain data (QLoRA on NVIDIA, CPU smoke-test on laptop). 'The organism becomes its own brain' — build a fine-tune dataset, train, eval, export.
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。
Plan and prepare an OpenAmer-specific fine-tune from the collected brain data: data curation, ChatML JSONL, training, evaluation. 'The organism becomes its own brain'.
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。
With this cross-journal Collection, the editors at Nature Communications , Communications Psychology GAP: no mappable capability in latest signal (our
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。
Crawl and extract a bounded set of pages from one website through Tavily. Use for documentation downloads, site-section collection, or semantic multi-page extraction when map plus individual extract calls are insufficient.
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 Vercel cost and performance optimization on deployed projects, especially Next.js, SvelteKit, Nuxt, and limited Astro apps. Collect Vercel metrics, usage, project config, and code scan results first; investigate only metric-backed candidates; produce ranked recommendations grounded in verified files and version-aware Vercel/framework docs. Trigger for Vercel bill reduction, slow or expensive routes, caching opportunities, Function Invocations, Build Minutes, Fast Data Transfer, Core Web Vitals, Bot Management, Fluid compute, or cost breakdown 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。