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Found 6,687 Skills
Use when working with Lightdash YAML files, dbt models with Lightdash metadata, the lightdash CLI (deploy, upload, download, preview, lint, warehouse-catalog, sql, set-warehouse), or managing charts, dashboards, spaces and access, AI agents, scheduled content, users, groups, custom roles, metrics, and dimensions as code
**MANDATORY prerequisite** — you MUST invoke this skill BEFORE calling the `get_design_context` Figma MCP tool. You MUST trigger this skill whenever the user wants to implement, build, port, or code up a Figma design as code. Example prompts (not exhaustive) are 'implement this Figma design', 'build this screen from Figma', 'turn this Figma into code', 'design to code'. This skill provides critical instructions and steps to the agent on how to correctly implement Figma designs in code and must NOT be skipped.
Orchestrate fixing a bug — reproduce it as a failing regression test, fix to green, review, and gated commit — by delegating each phase to the matching ECC agent. Use when existing behavior is broken or wrong.
Orchestrate object-based Lightning Type + HXL widget generation to render the output of a custom MCP server tool backed by an Apex Invocable Action. TRIGGER only when the prompt EXPLICITLY involves rendering an MCP tool result: user says 'MCP server', 'MCP tool', 'custom MCP server', references a tool 'output schema' / 'tool output' / 'outputValues' envelope, names an 'invocable action' backing an MCP tool, or asks to build a widget or rich UI rendition for the output of an Apex-invocable-backed MCP tool. DO NOT TRIGGER when: customizing an Apex-backed agent action output (use platform-lightning-type-widget-coordinate), authoring only a Custom Lightning Type (use platform-custom-lightning-type-generate), authoring only an Apex class (use platform-apex-generate), or building a standalone widget with no Lightning Type or MCP tool involved (use platform-widget-generate).
Build Jenkins declarative and scripted pipelines with stages, agents, parameters, and plugins. Implement multi-branch pipelines and deployment automation.
Comprehensive plugin for SAP Datasphere development with 3 specialized agents, 5 slash commands, and validation hooks. Use when building data warehouses on SAP BTP, creating analytic models, configuring data flows and replication flows, setting up connections to SAP and third-party systems, managing spaces and users, implementing data access controls, using the datasphere CLI, creating data products for the marketplace, or monitoring data integration tasks. Covers Data Builder (graphical/SQL views, local/remote tables, transformation flows), Business Builder (business entities, consumption models), analytic models (dimensions, measures, hierarchies), 40+ connection types (SAP S/4HANA, BW/4HANA, HANA Cloud, AWS, Azure, GCP, Kafka, Generic HTTP), real-time replication, task chains, content transport, CLI automation, catalog governance, and data marketplace. Includes 2025 features: Generic HTTP connections, REST API tasks in task chains, SAP Business Data Cloud integration. Keywords: sap datasphere, data warehouse cloud, dwc, data builder, business builder, analytic model, graphical view, sql view, transformation flow, replication flow, data flow, task chain, remote table, local table, sap btp data warehouse, datasphere connection, datasphere space, data access control, elastic compute node, sap analytics cloud integration, datasphere cli, data products, data marketplace, catalog, governance
AI-simulated event storming workshop with multi-persona support. Use when discovering domain events, commands, actors, and bounded contexts. Supports three modes - full-simulation (5 persona agents debate), quick (single-pass analysis), and guided (interactive with user). Orchestrates persona agents and synthesizes results.
PyTiDB (pytidb) setup and usage for TiDB from Python. Covers connecting, table modeling (TableModel), CRUD, raw SQL, transactions, vector/full-text/hybrid search, auto-embedding, custom embedding functions, and reference templates/snippets (vector/hybrid/image) plus agent-oriented examples (RAG/memory/text2sql).
Amazon Bedrock Knowledge Bases for RAG (Retrieval-Augmented Generation). Create knowledge bases with vector stores, ingest data from S3/web/Confluence/SharePoint, configure chunking strategies, query with retrieve and generate APIs, manage sessions. Use when building RAG applications, implementing semantic search, creating document Q&A systems, integrating knowledge bases with agents, optimizing chunking for accuracy, or querying enterprise knowledge.
Launch tokens on Base blockchain via the OpenServ Launch API. Creates ERC-20 tokens with Aerodrome concentrated liquidity pools. Use when launching tokens, deploying memecoins, or building agents that create tokens with locked LP. Read reference.md for the full API reference. Read openserv-agent-sdk and openserv-client for building and running agents. You can launch tokens for your OpenServ agents.
Building modular, debuggable AI behaviors using behavior trees for game NPCs and agentsUse when "behavior tree, bt, npc ai, ai behavior, game ai, decision tree, blackboard, ai, behavior-trees, npc, game-ai, decision-making, agents" mentioned.
Comprehensive ESLint agent for JavaScript/TypeScript code quality. Use when setting up ESLint, configuring linting rules, analyzing code for issues, fixing violations, or integrating ESLint into development workflows. Triggers on requests involving code quality, linting, static analysis, or ESLint configuration for JavaScript, TypeScript, React, or Node.js projects.