141 skills · sorted by relevance
Azure Resource Manager SDK for Durable Task Scheduler in .NET. Use for MANAGEMENT PLANE operations: creating/managing Durable Task Schedulers, Task Hubs, and retention policies via Azure Resource Manager. Triggers: "Durable Task Scheduler", "create scheduler", "task hub", "DurableTaskSchedulerResource", "provision Durable Task", "orchestration scheduler".
The English summary is being prepared. Showing the original description.
Guide an RxJS 7 project to RxJS Next by testing existing behavior, reviewing how subscriptions start and end, and validating small batches of changes. Record approved behavior choices, verification results, and unresolved blockers in migration reports.
Fix Google Cloud Scheduler silently failing to trigger Cloud Run jobs with status code 7 (PERMISSION_DENIED). Use when: (1) Cloud Run jobs stop running but schedulers show ENABLED, (2) gcloud scheduler jobs describe shows lastAttemptTime but status.code: 7, (3) Jobs worked before but stopped after IAM changes or project updates. The scheduler service account needs roles/run.invoker on the project.
The English summary is being prepared. Showing the original description.
Designing meeting schedulers and booking experiences that qualify leads, set up calls well, and convert at higher rates than a generic Calendly link. Availability logic, qualification gating, prep automation, follow-up sequencing. Honest about any-time-friction (no qualification, just a booking link), interrogation-gate (so much qualification it scares users off), and qualified-fast-path (just enough qualification to set up the call well) patterns. Triggers on scheduler design, meeting booking, demo scheduling, sales call scheduling, calendar tool, booking page, qualification flow. Also triggers when sales team complains about cold demos, when booking conversion is poor, or when scheduler is being scoped for the first time.
The English summary is being prepared. Showing the original description.
Design and review Action Scheduler jobs in WordPress plugins using Action Scheduler 3.9.x public APIs - async, single, recurring, and cron-expression actions; action_scheduler_init load timing; hook/args/group naming; unique and priority parameters; idempotent callbacks; chunked workloads; activation/deactivation cleanup; WooCommerce-bundled or standalone dependency usage; admin and WP-CLI debugging; queue runner limits; and safe operational troubleshooting. Use when a plugin schedules background jobs with as_enqueue_async_action, as_schedule_single_action, as_schedule_recurring_action, as_schedule_cron_action, as_get_scheduled_actions, or integrates with WooCommerce background queues.
The English summary is being prepared. Showing the original description.
Create, debug, and maintain Windows batch scripts for file operations, backups, and scheduled tasks. Covers command arguments, variables, loops, and error handling, with starter templates for command-line tools and reusable functions.
Guide changes and reviews for SGLang’s Scheduler, TokenizerManager, and ModelRunner classes. Keep initialization in small, replaceable helpers and separate computation from coordination so large classes retain clear responsibilities and explicit dependencies.
Use this skill to implement ONE microsoft/apm issue already selected by autopilot-issue-delivery-scheduler. Queue signal is `status/accepted` or a named bounded accept; that is not permission. Requires fresh human-scope evidence from scripts/governance before any mutate. May reproduce a bug, implement the accepted change, and open a fix PR. Not a queue manager and not a triage scheduler. Works in the scheduler's session, a child session, Cloud Agent, Remote Agent, or Agentic Workflow.
The English summary is being prepared. Showing the original description.
Operational knowledge for the daily-brief digest pipeline (this project). RSS/API fetchers, pluggable LLM enrichment (default claude CLI on Max; also anthropic/openai/deepseek/minimax API), trading section, HTML rendering, cross-platform scheduler integration (Windows Task Scheduler / macOS launchd / Linux cron). Load when the user asks about running daily / regenerating sections / debugging a failed run / adding or disabling sources / LLM quota / scheduler / why a tab shows wrong data / why a source failed / switching LLM backend. Always prefer the documented npm commands over re-implementing logic. Diagnose by reading logs/daily-*.log first, then logs/llm-calls.jsonl for LLM-side issues.
The English summary is being prepared. Showing the original description.
Baut und betreibt ein anbieterneutrales Self-Care-Kernset für geplante LLM-Aufgaben und Desktop-App-Automationen. Ergänzt deterministisches Policy-Linting, Lock- und Modell-Governance, semantische Prompt-Prüfung, konsistente Mehrflächen-Updates, Mini-Checks und Regeldatei-Hygiene. Nutzen, wenn ein Agent seinen nativen Scheduler entdecken oder eine bestehende Automations-Flotte mit Rollback, Readback und Löschschutz kontinuierlich verbessern soll. Löst aus bei automation self-care, Scheduler-Task-Pflege, Desktop-App-Automations-Wartung, Automations-Flotten-Audit, selbstheilende Zeitpläne, core-set-textautomations, basic-text-automations, textbased-automation-core, textbased-automation-drivers, textbased-governance-automations oder textbased-desktopapp-automations.
The English summary is being prepared. Showing the original description.
Summarize the past 24 hours of Notion document edits, comments, mentions, and database row changes in a Notion-style briefing page. It runs through Orbit's daily scheduler using an authenticated Notion connection and a fixed page structure.
Inspect CPU, memory, disk, and accelerator information alongside container and scheduler limits. Produce a JSON snapshot with identifying details removed and conservative worker and memory estimates for planning local workloads, without running stress tests.
Implement scheduled data updates for dashboard panels with separate refresh intervals. Pause timers while the browser tab is hidden, stagger eligible updates on return to reduce request bursts, and prevent overlapping requests for the same panel.
Drive ONE already selected open pull request in microsoft/apm to mergeable. Classifies copilot-pull-request-reviewer[bot] inline review, runs autopilot-pr-review-worker, folds (by default) every recommendation inside the PR's stated scope, pushes to the head branch or a superseding PR that preserves authorship via commit trailers, watches CI to green (`agent-merge` when that skill or `<agent_merge_state>` is present; otherwise `gh pr checks --watch`), and iterates under fixed caps until ready-to-merge, advisory-with-deferred, superseded, or blocked. Plan before any fold, push, or reviewer request. Never spawned by autopilot-pr-review-scheduler. That scheduler is advisory only. Invoke this skill by name when the caller asked to drive a PR to merge.
The English summary is being prepared. Showing the original description.
Extend / continue a video temporally with Pusa 2.2 in ComfyUI. Temporal flowmatching (the flowmatch_pusa scheduler + WanVideoAddPusaNoise) on the WanVideoWrapper stack with WAN 2.2 T2V A14B (HIGH/LOW) models and the Pusa V1 LoRAs, conditioning on the loaded clip via WanVideoEncode so the existing motion carries into the continuation. Covers the kijai wanvideo_2_2_14B_Pusa_extension graph, model/LoRA slots + downloads, noise/length/scheduler settings, chaining multiple extensions, VRAM tiers, gotchas, and the extend→upscale handoff.
The English summary is being prepared. Showing the original description.
Schedules meetings with internal and external stakeholders by parsing natural language requests, resolving time zones, checking calendar availability, proposing optimal slots, and managing invitations and RSVPs. Use when the user requests meeting scheduler or provides relevant inputs for this workflow.
The English summary is being prepared. Showing the original description.
数据工程 — 数据平台从业者的认知操作系统, 覆盖把数据从源系统搬运成可靠 / 可查询 / 可信赖形态供分析 / ML / 数据产品消费的全生命周期 (生成 → 摄取 → 存储 → 转换 → 服务 + 安全/数据管理/DataOps/数据架构/编排/软件工程 六条暗流, Reis & Housley 框架): 摄取与集成 (批 + CDC 变更数据捕获 Debezium + EL 工具 Fivetran/Airbyte/Meltano/dlt + Kafka Connect + schema drift) / 存储与文件表格式 (对象存储数据湖 + 列存 Parquet/ORC/Arrow/Avro + 开放表格式 Apache Iceberg/Delta Lake/Apache Hudi + lakehouse + 分区/compaction) / 转换与建模 (ELT dbt/SQLMesh + Spark + 维度建模 Kimball + Inmon + Data Vault + 大宽表 OBT + 渐变维 SCD + 增量模型 + 语义/指标层) / 编排与工作流 (Apache Airflow/Dagster/Prefect/Mage/Kestra/Apache DolphinScheduler + DAG + 幂等 + 回填 backfill + 数据资产调度) / 批流与实时 (Apache Kafka/Apache Flink/Spark Structured Streaming/Kinesis/Pulsar/Redpanda + Lambda vs Kappa + watermark/窗口/exactly-once + 流式 SQL Materialize/RisingWave + 实时 OLAP ClickHouse/Apache Druid/Apache Pinot/StarRocks/Apache Doris) / 数仓与查询引擎 (Snowflake/BigQuery/Redshift/Databricks SQL/Trino/Presto/DuckDB/Polars + 存算分离 + MPP) / 数据质量测试与可观测性 (dbt tests/Great Expectations/Soda + 数据契约 + Monte Carlo data downtime + 新鲜度/量/schema 异常检测) / 数据治理编目与血缘 (DataHub/Amundsen/OpenMetadata/Unity Catalog + 列级血缘 + PII 分类 + 访问控制 + GDPR) / DataOps 与可靠性 (数据 CI/CD + 转换版本控制 + 环境隔离 + 幂等重处理 + 数据 SLA/SLO + 计算存储 FinOps) / 数据架构范式 (现代数据栈 + lakehouse + data mesh + data fabric + 去中心化 vs 中心化所有权) / 分析工程角色 (dbt 时代连接数据工程与分析的桥) — 不含 数据科学/ML 建模本身 (是下游消费者) / BI 仪表盘制作 (serving 下游) / 数据分析报表为终点 / 'data engineer = 跑 Hadoop 的' 过时窄化 / 通用后端应用开发 (平行学科) (Data Engineering — the cognitive operating system of practitioners who design, build, and operate the data platform: moving data from source systems into reliable, queryable, trustworthy form for analytics / ML / products, covering (a) the data engineering lifecycle (generation → ingestion → storage → transformation → serving, with the undercurrents security / data management / DataOps / data architecture / orchestration / software engineering — Reis & Housley framing), (b) ingestion & integration (batch + CDC change-data-capture with Debezium, EL tools Fivetran / Airbyte / Meltano / dlt, Kafka Connect, API + file + database sources, schema drift handling), (c) storage & file/table formats (object storage data lakes, columnar formats Parquet / ORC / Arrow / Avro, open table formats Apache Iceberg / Delta Lake / Apache Hudi, lakehouse architecture, partitioning / compaction / Z-ordering), (d) transformation & modeling (ELT with dbt / SQLMesh, Spark, dimensional modeling Kimball, Inmon CIF, Data Vault, One Big Table / wide tables, normalization vs denormalization, slowly changing dimensions, incremental models, the semantic / metrics layer), (e) orchestration & workflow (Apache Airflow, Dagster, Prefect, Mage, Kestra, Apache DolphinScheduler, DAGs, idempotency, backfills, data-aware / asset-based scheduling), (f) batch vs streaming & real-time (Apache Kafka, Apache Flink, Spark Structured Streaming, Kinesis / Pulsar / Redpanda, the Lambda vs Kappa debate, watermarks / windowing / exactly-once, streaming SQL Materialize / RisingWave, real-time OLAP ClickHouse / Apache Druid / Apache Pinot / StarRocks / Apache Doris), (g) warehouses & query engines (Snowflake, BigQuery, Redshift, Databricks SQL, Trino / Presto, DuckDB, Polars, decoupled storage & compute, MPP), (h) data quality, testing & observability (dbt tests, Great Expectations, Soda, data contracts, Monte Carlo / data downtime, freshness / volume / schema anomaly detection, unit / integration testing of pipelines), (i) data governance, catalog & lineage (DataHub, Amundsen, OpenMetadata, Unity Catalog, column-level lineage, PII / data classification, access control, GDPR / data privacy), (j) DataOps & reliability (CI/CD for data, version control of transformations, environments, idempotent reprocessing, SLAs / SLOs for data, cost / FinOps for compute & storage), (k) data architecture paradigms (modern data stack, data lakehouse, data mesh, data fabric, decentralized vs centralized ownership), (l) the analytics engineering role (the dbt-era bridge between data engineering and analysis); N
The English summary is being prepared. Showing the original description.
Work with the @upstash/qstash TypeScript/JavaScript SDK, an HTTP-based message queue, task scheduler, and background job system for serverless and edge runtimes (Next.js, Vercel, Cloudflare Workers, Deno, Node.js). Use when publishing messages to HTTP endpoints or URL groups, running background jobs without a long-running worker process, scheduling with cron expressions, delaying messages, building FIFO queues with parallelism and flow control, configuring retries and callbacks, handling a dead letter queue (DLQ), deduplicating messages, fanning out to multiple endpoints, verifying QStash webhook signatures (Next.js App Router, Pages Router, and Edge Runtime), running a local QStash dev server, or migrating regions. Also use when the user asks for a serverless cron job, async task queue, job scheduler, delayed delivery, webhook delivery with retries, or event-driven messaging between services.
The English summary is being prepared. Showing the original description.
北原さんのYouTube動画からナレッジを生成したいとき、URL単発・厳格全量・scheduler無人差分のいずれかで文字起こしを取り込み根拠付き依存グラフまで更新したいときに使う。
The English summary is being prepared. Showing the original description.
Safely integrate with WooCommerce Subscriptions renewal, next-payment scheduling, Action Scheduler events, and retry flow. Shows when to use WC_Subscription::update_dates, update_status, wcs_create_renewal_order, wcs_renewal_order_created, woocommerce_scheduled_subscription_payment, woocommerce_scheduled_subscription_payment_{gateway_id}, woocommerce_subscription_renewal_payment_complete, and payment retry hooks. Use when changing next payment dates, forcing/rescheduling renewals, reacting to failed renewals, building gateway recurring charge logic, or debugging missing/duplicate renewal orders.
The English summary is being prepared. Showing the original description.
Designs and reviews scheduled/background work in WordPress plugins: wp_schedule_event, wp_schedule_single_event, cron_schedules, wp_next_scheduled guards, activation scheduling, deactivation cleanup, WP-Cron pseudo-cron timing, DISABLE_WP_CRON/system cron, multisite per-blog cron, idempotent callbacks, chunking, and Action Scheduler graduation. Use when adding scheduled jobs, debugging late/duplicate cron events, or deciding between WP cron and Action Scheduler.
The English summary is being prepared. Showing the original description.
Use when working with Apache Airflow Deep — apache Airflow deep management covering DAG inventory, task instance monitoring, scheduler health, executor status, pool and variable management, connection auditing, and SLA miss tracking. Use when investigating DAG failures, analyzing task duration trends, monitoring scheduler performance, or auditing Airflow configurations.
The English summary is being prepared. Showing the original description.
Operação de aplicação Laravel em produção — Horizon, queue, scheduler, Octane, Redis, Supervisor, PHP-FPM, cache e deploy. Use quando o usuário disser "laravel", "horizon", "queue", "fila travada", "job falhando", "octane", "artisan", "php-fpm", "supervisor", "scheduler não roda".
The English summary is being prepared. Showing the original description.
Migrates legacy AEM (6.x, AMS, on-prem) to AEM as a Cloud Service using BPA CSV or cache, CAM/MCP target discovery, and a one-pattern-per-session workflow. Use for BPA/CAM findings, Cloud Service blockers, or fixes for scheduler, ResourceChangeListener, replication, EventListener, OSGi EventHandler, DAM AssetManager, HTL data-sly-test lint. OSGi configs → Cloud Manager — scan ui.config, .cfg.json, secrets, $[secret:]/$[env:] — agent follows references/osgi-cfg-json-cloud-manager.md when prompted. After BPA/CAM discovery, migration hands off each (pattern, file) pair to the code-assessment skill — code-assessment owns the five pattern guides (scheduler/, resource-change-listener/, replication/, event-migration/, asset-manager/) and the shared references for SCR→DS, ResourceResolver/SLF4J, HTL lint, and prerequisites.
The English summary is being prepared. Showing the original description.