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Found 2,700 Skills
Optimize MongoDB client connection configuration (pools, timeouts, patterns) for any supported driver language. Use this skill when working/updating/reviewing on functions that instantiate or configure a MongoDB client (eg, when calling `connect()`), configuring connection pools, troubleshooting connection errors (ECONNREFUSED, timeouts, pool exhaustion), optimizing performance issues related to connections. This includes scenarios like building serverless functions with MongoDB, creating API endpoints that use MongoDB, optimizing high-traffic MongoDB applications, creating long-running tasks and concurrency, or debugging connection-related failures.
Generate images or videos using Jimeng Dreamina CLI. Invoke when user needs to generate images or videos using Jimeng (Dreamina).
Text Storyboard: The translation layer from script to screen, which converts abstract literary works into concrete audio-visual descriptions. It is invoked when users need to convert novels or scripts into text storyboards.
Review staged git changes against an issue. Produces a structured improvement plan — no edits applied. Also identifies test file compaction opportunities. Use when asked to check, review, or validate staged work before committing. Part 2 of 3 in the issue-review-two-phases workflow.
Implements JWT SSO authentication for Metabase embedding in a project. Supports all embedding types that use SSO — Modular embedding (embed.js web components), Modular embedding SDK (@metabase/embedding-sdk-react), and Full app embedding (iframe-based). Creates the JWT signing endpoint, configures the frontend auth layer, and sets up group mappings. Use when the user wants to add SSO/JWT auth to their Metabase embedding, implement user identity for embedded analytics, set up JWT authentication for Metabase, or connect their app's authentication to Metabase embedding.
Manage Databricks Model Serving endpoints via CLI. Use when asked to create, configure, query, or manage model serving endpoints for LLM inference, custom models, or external models.
Develop Lakeflow Spark Declarative Pipelines (formerly Delta Live Tables) on Databricks. Use when building batch or streaming data pipelines with Python or SQL. Invoke BEFORE starting implementation.
Compares a single test case's behavior across two branches, analyzing pass/fail status, duration, flakiness, and failure details. Useful for investigating test regressions introduced by a feature branch.
Diagnoses and resolves issues on GuaraCloud — failed deployments, crash loops, health check failures, image pull errors, OOM kills, and CLI errors. Use when the user reports something broken, a deployment failed, a service is unhealthy, or they see an error.
Provides installation guidance for CANN on Ascend NPU. Call this skill when users need to install CANN, configure the Ascend environment, or resolve installation issues.
In-process ClickHouse SQL engine for Python — run ClickHouse SQL queries directly on local files, remote databases, and cloud storage without a server. Use when the user wants to write SQL queries against Parquet/CSV/ JSON files, use ClickHouse table functions (mysql(), s3(), postgresql(), iceberg(), deltaLake() etc.), build stateful analytical pipelines with Session, use parametrized queries, window functions, or other advanced ClickHouse SQL features. Also use when the user explicitly mentions chdb.query(), ClickHouse SQL syntax, or wants cross-source SQL joins. Do NOT use for pandas-style DataFrame operations — use chdb-datastore instead.
Compose Mapbox MCP tools to produce grounded, cited location-aware responses from live data instead of training data