288 件 ・ 関連度順
概要と使いどころ
Audit an existing Comet expression for correctness and test coverage. Studies the Spark implementation across versions 3.4.3, 3.5.8, 4.0.1, and 4.1.1, reviews the Comet and DataFusion implementations, identifies missing test coverage, and offers to implement additional tests.
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Use when optimizing the performance of an existing native scalar expression in the datafusion-comet-spark-expr crate (native/spark-expr/) — casts, string/JSON/array/math kernels that run per-row or per-batch. Covers benchmarking, keeping output bit-identical, and the no-regression gate. Not for adding new expressions (use implement-comet-expression) or wiring upstream functions (use wire-datafusion-function).
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Use when reviewing a DataFusion Comet pull request that touches memory pools, memory reservations, spilling, the Spark TaskMemoryManager bridge, allocators, or memory-related configuration. Load alongside review-comet-pr.
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Use when reviewing a DataFusion Comet pull request that touches native or JVM columnar shuffle, the shuffle writers and readers, partitioning, the Arrow IPC block format, shuffle compression, or the Celeborn integration. Load alongside review-comet-pr.
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Use when wiring an existing DataFusion or datafusion-spark function into Comet for a Spark expression. Identifies the right wiring pattern (one-line passthrough, datafusion-spark UDF registration, or custom serde with input massaging / restrictions), applies the Scala serde, registers the UDF in jni_api when needed, and adds SQL file tests. Assumes the function already exists upstream — if not, switch to `implement-comet-expression`.
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Use when reviewing a DataFusion Comet pull request that touches Iceberg writes, the split-operator write plan (IcebergWriteStrategy, IcebergWriteExec, IcebergCommitExec), the native Iceberg writer (CometIcebergWriteExec, iceberg_write.rs, iceberg_partition_path.rs), its eligibility gate (CometIcebergNativeWrite), or the iceberg-rust pin. Load alongside review-comet-pr.
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Use when reviewing a DataFusion Comet pull request that adds or changes a Spark expression, its Scala serde, its protobuf message, or its native Rust implementation. Load alongside review-comet-pr, which covers the parts of the review that apply to every PR.
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Expert knowledge for Azure Horizondb development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when tuning pgvector, azure_ai SQL functions, LangChain vector stores, Apache AGE graphs, or hybrid search, and other Azure Horizondb related development tasks. Not for Azure Cosmos DB (use azure-cosmos-db), Azure SQL Database (use azure-sql-database), Azure Table Storage (use azure-table-storage).
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Удаление веб-публикации 1С из Apache. Используй когда пользователь просит убрать публикацию, удалить веб-доступ к базе
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Публикация информационной базы 1С через Apache. Используй когда пользователь просит опубликовать базу, сервисы, настроить веб-доступ, веб-клиент, открыть в браузере
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Entrypoint for managing Volcengine Flink (based on Apache Flink) workloads. Use it for developing and deploying streaming and batch jobs, diagnosing real-time issues (e.g., backpressure, checkpoint failures, OOM), troubleshooting resources, and performing SRE actions (stop/start/restart/scale/config changes). It intelligently routes requests to four specialized sub-skills and leverages flink-mcp for tool execution.
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。
Tell a joke about cat.
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。
Calculate mathematical expressions using shell commands. Use when the user asks to perform arithmetic calculations like addition, subtraction, multiplication, division, or powers.
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Calculate simple mathematical expressions using shell commands. Use when the user asks to perform arithmetic calculations like addition, subtraction, multiplication, division, or more complex math expressions.
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 a new OSGi configuration property to the oak-store-document module. Modifies Configuration.java, DocumentNodeStoreService.java, DocumentNodeStoreBuilder.java, RDBDocumentNodeStoreBuilder.java, Utils.java, and all relevant test files with 90%+ coverage.
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Create Apache Airflow DAGs for construction data pipelines. Orchestrate ETL, validation, and reporting workflows.
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Apache Iceberg tables on Databricks — Managed Iceberg tables, External Iceberg Reads (fka Uniform), Compatibility Mode, Iceberg REST Catalog (IRC), Iceberg v3, Snowflake interop, PyIceberg, OSS Spark, external engine access and credential vending. Use when creating Iceberg tables, enabling External Iceberg Reads (uniform) on Delta tables (including Streaming Tables and Materialized Views via compatibility mode), configuring external engines to read Databricks tables via Unity Catalog IRC, integrating with Snowflake catalog to read Foreign Iceberg tables
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Push records from apps, services, devices, or scripts directly into Unity Catalog Delta tables with Zerobus Ingest: SDKs (Python, TypeScript, Go, Java, Rust, C++, .NET), REST, OTLP, MQTT, Arrow Flight, or Apache Kafka-compatible producer APIs, with no message bus to run. Use to stream events, telemetry, logs, IoT data, CDC, or columnar batches into Databricks in near real time; connect existing collectors and log shippers (OpenTelemetry, Debezium, Vector, Telegraf, Cribl); replace a message bus that only feeds the lakehouse; or debug Zerobus auth, schema, throughput, or delivery issues.
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Build custom Python data sources for Apache Spark using the PySpark DataSource API — batch and streaming readers/writers for external systems. Use this skill whenever someone wants to connect Spark to an external system (database, API, message queue, custom protocol), build a Spark connector or plugin in Python, implement a DataSourceReader or DataSourceWriter, pull data from or push data to a system via Spark, or work with the PySpark DataSource API in any way. Even if they just say "read from X in Spark" or "write DataFrame to Y" and there's no native connector, this skill applies.
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RCE hunting - template injection, YAML/XML deserialization, dependency confusion, Kubernetes surfaces, CVE-specific exploits (Apache CVE-2021-41773, Spring CVE-2022-22963). OOB-mandatory for blind cases. Wiki-first, FIND schema output.
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Build production Apache Airflow DAGs with best practices for operators, sensors, testing, and deployment. Use when creating data pipelines, orchestrating workflows, or scheduling batch jobs.
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Generate configuration files for applications, services, and infrastructure. Use when: (1) Setting up new projects (package.json, requirements.txt, tsconfig.json), (2) Creating Docker or Kubernetes configurations, (3) Configuring CI/CD pipelines (GitHub Actions, GitLab CI, CircleCI), (4) Setting up web servers (Nginx, Apache), (5) Defining infrastructure as code (Terraform, CloudFormation), (6) Generating linter/formatter configs (ESLint, Prettier, Black). Provides templates and custom-generated configs for diverse tech stacks.
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Think and work like an expert Critical Care Researcher. Use when a task calls for Critical Care Researcher judgment. Reasons from acute physiology trajectories, modular organ dysfunction, and cluster-aware trial design through APACHE/SAPS/SOFA scoring, Berlin/Sepsis-3/KDIGO definitions, MIMIC-IV phenotyping, and target-trial emulation with clone-censor-weighting while treating immortal-time bias, cluster contamination, competing risks from early death, and sepsis-phenotype cohort inflation as first-class failure modes.
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Local and self-hosted text-to-speech with Kokoro, the ~82M-parameter open-weight (Apache 2.0) model by hexgrad. Use when synthesizing speech offline, on-device, in the browser, or on your own server without per-character API cost — for high-volume narration, audiobooks, privacy-constrained pipelines, and prototyping. Covers running Kokoro via the Python `kokoro` package, ONNX / kokoro-js in the browser, and the OpenAI-compatible Kokoro-FastAPI wrapper; picking voices and language codes; blending voices; chunking long text; controlling pronunciation via misaki/espeak-ng; and judging when Kokoro is the right tool versus when its lack of voice cloning, narrow emotional range, and weaker non-English quality mean you should reach for a hosted or larger model instead. Not for voice cloning, expressive/emotional character performance, or high-fidelity multilingual work — say so and route elsewhere.
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。