validating-ai-ethics-and-fairness
This skill enables Claude to validate the ethical implications and fairness of AI/ML models and datasets. It is triggered when the user requests an ethics…
Find an Agent Skill for your task. Read the guide and copy the install command.
Updated 11-09 00:13
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This skill enables Claude to validate the ethical implications and fairness of AI/ML models and datasets. It is triggered when the user requests an ethics…
Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express…
Enter explore mode - a thinking partner for exploring ideas, investigating problems, and clarifying requirements. Use when the user wants to think through…
Use when an agent's memory needs to be built, audited, or maintained — the user asks to set up a memory system, complains the agent keeps forgetting or…
Instructions when acting as an Advisor to another Agent
Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking…
Guides agents and users to define a clear Definition of Done for agentic tasks, ensuring outcomes are recognized and satisfying.
Create and manage Databricks Agent Bricks: Knowledge Assistants (KA) for document Q&A, Genie Spaces for SQL exploration, and Multi-Agent Supervisors (MAS) for…
Evaluates whether the agent selected appropriate MCP tools instead of shell workarounds. Load when the trace contains Bash tool calls that could have used MCP…
Analyzes an MLflow session — a sequence of traces from a multi-turn chat conversation or interaction. Use when the user asks to debug a chat conversation,…
Create and manage Databricks Agent Bricks: Knowledge Assistants (KA) for document Q&A, Genie Spaces for SQL exploration, and Supervisor Agents (MAS) for…
Onboards users to MLflow by determining their use case (GenAI agents/apps or traditional ML/deep learning) and guiding them through relevant quickstart…
Guides the creation of new Agent Skills following the AgentSkills.io specification. Covers required frontmatter (name, description), optional metadata,…
Transforms the assistant into a Senior Databricks Solutions Architect Agent that designs, implements, and reviews production-grade Databricks solutions…
Spark Declarative Pipeline (SDP, formerly DLT) expectations patterns for data quality with Unity Catalog Delta table storage. Use when implementing Silver…
Canonical pattern for building an agentic tool-calling loop using a Databricks-hosted Foundation Model. Use when creating agent_loop.py or any backend that…
End-to-end orchestrator for implementing production-grade Databricks GenAI agents using MLflow 3.0 ResponsesAgent, Genie Spaces, Lakebase memory, and…
Patterns for setting up Databricks Genie Spaces with comprehensive agent instructions, data assets, and benchmark questions. Use when creating Genie Spaces,…
Lakebase memory patterns for stateful agents - CheckpointSaver for short-term conversation continuity, DatabricksStore for long-term user preferences, graceful…
MLflow 3 GenAI evaluation patterns with LLM judges, MemAlign judge alignment, GEPA prompt optimization, custom scorers with _extract_response_text() helper,…
Core MLflow 3.0 GenAI patterns for Databricks agents - model signatures, tracing fundamentals, evaluation basics, prompt registry basics. Foundational patterns…
Multi-agent orchestration patterns with Genie Spaces for structured data access. Includes Conversation API integration, parallel domain queries, intent…
Continuous production monitoring for GenAI agents - registered scorers with sampling, on-demand assess(), scorer lifecycle, trace archival, metric backfill.…
MLflow Prompt Registry for versioned prompt management - Unity Catalog storage, MLflow artifact versioning, A/B testing with champion/challenger, lazy loading,…