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Found 1,409 Skills
Query, monitor, and analyze jobs on IBM i using SQL table functions via ibmi-mcp-server. Use when user asks about: (1) finding jobs by status, user, subsystem, or type, (2) monitoring active job performance (CPU, I/O, memory), (3) detecting long-running SQL statements, (4) analyzing lock contention, (5) checking job queues, (6) replacing WRKACTJOB, WRKUSRJOB, WRKSBSJOB, WRKSBMJOB commands, or (7) any IBM i work management task.
Design Prisma 7 + PostgreSQL schemas with correct relations, constraints, indexes, naming conventions, and migration-safe patterns.
Full-stack development skill with six-layer architecture, supporting cross-layer modifications initiated from any layer. It automatically coordinates the collaboration of six layers: UI Layer/Frontend Service Layer/Frontend API Layer/Backend API Layer/Backend Service Layer/Data Layer, enabling cross-layer consistent code generation and refactoring. Suitable for Vue3+FastAPI+PostgreSQL tech stack
Interact with the learning system: show stats, list/search accumulated knowledge, and graduate mature entries into agents/skills. Backed by learning.db (SQLite + FTS5). Use when user says "retro", "retro list", "retro search", "retro graduate", "check knowledge", "what have we learned", "knowledge health", "graduate knowledge".
Comprehensive guide to implementing Syncfusion React Query Builder component. Use this skill when building advanced filter interfaces, creating complex data query systems, or implementing dynamic rule-based filtering. This skill covers query builder configuration, SQL query conversion, drag-and-drop filtering, customization, and state management.
Alibaba Cloud DMS Database Read/Write Skill. Use this skill to search for target databases in DMS and execute SQL queries and data modifications. Triggers: "DMS query", "database query", "execute SQL", "search database", "DMS SQL", "insert data", "update data".
Hot-reload Go apps with cosmtrek/air during development. Use when setting up dev workflows for Go HTTP servers, configuring .air.toml, or debugging hot-reload issues with SQLite, port binding, or file watchers.
Activate when the user asks Claude to talk like a caveman, use caveman mode, say "less tokens please", or invoke "/elastic-caveman". Also activate when the user wants faster, terser responses while still working with Elasticsearch, Kibana, Elastic Security, Elastic Observability, or any part of the Elastic stack. In caveman mode all Elasticsearch-specific technical terms, API names, field names, index patterns, query DSL structures, ESQL syntax, and error messages are preserved verbatim — only filler words and pleasantries are removed. Stop caveman mode when the user says "stop caveman" or "normal mode".
Record transaction flow in accordance with unified rules. Save records by individual stock in Markdown format, and simultaneously write to SQLite for statistics and quantitative review.
Connect SaaS data (HubSpot, Stripe, Salesforce, GitHub, Slack, etc.) to Wren Engine for SQL analysis. Guides the user through the full flow: install dlt, pick a SaaS source, set up credentials, run the data pipeline into DuckDB, then auto-generate a Wren semantic project from the loaded data. Use this skill whenever the user mentions: connecting SaaS data, importing data from an API, dlt pipelines, loading HubSpot/Stripe/Salesforce/GitHub/Slack data, querying SaaS data with SQL, or setting up a new data source from a REST API. Also trigger when the user already has a dlt-produced DuckDB file and wants to create a Wren project from it.
Write spatial SQL against the connected warehouse — dialect-specific guidance, performance defaults, and CARTO's query/job execution model.
Python backend for Databricks Apps — FastAPI (default), Flask, Dash, Streamlit, Gradio, Reflex. **Default for a new Databricks App is `databricks-apps` (AppKit — Node/TypeScript/React) — reach for it first.** Use this skill only when the user asks for a Python backend, extends an existing Python app, or the team is Python-only. Covers OAuth auth, app resources, SQL warehouse and Lakebase connectivity, foundation-model / Vector Search / model-serving APIs (via `databricks-python-sdk`), and deployment via CLI or DABs.