Browse reusable Agent Skills, each with a clear purpose and practical guidance.
Continuous Agentation annotation handling. Use when the user says "watch mode", asks you to watch for Agentation annotations, process feedback as it arrives, or keep fixing annotation-driven changes until told to stop or a timeout is reached.
Periodically audit the LLM model catalog in src/schema/models.py against what each provider currently ships: add newly released models, remove/flag ones the provider has deprecated or discourages, and re-point DEFAULT_MODEL fallbacks at a current model. Use when asked to "check for new models", "update the model list", "refresh the model catalog", or on the scheduled model-refresh trigger.
Expert guide for defining, creating, and invoking custom subagents in Gemini CLI. Trigger this skill when the user wants to create a new specialist agent, define a custom subagent, or learn how to delegate tasks to specialist agents within the Gemini CLI environment.
Evaluate verified findings from merge-ready, Greptile, pull-request, CI, security, billing, and other code reviews, then promote durable review gaps into the version-controlled .greptile configuration. Use when a review uncovers a recurring or high-risk repository invariant that Greptile does not capture, when Greptile repeatedly produces a false positive, or when asked to audit or update OpenSEO's Greptile rules and context.
Top-level router for the build-paths skill set. Asks the user one question (which path?), then dispatches to beginner/, intermediate/, or advanced/. Use when the user wants to scaffold an Oracle-AI-DB project but hasn't picked a difficulty yet.
Scaffold an agent system where Oracle AI DB is the *only* state store, composed from the build-paths/skills/ building-block library. Stack — langchain-oracledb + oracle-database-mcp-server + in-DB ONNX embeddings + OCI GenAI Grok 4 + Open WebUI. Three projects — production-feeling NL2SQL+RAG hybrid analyst, self-improving research agent, conversational schema designer. For users who want a real DB-as-only-store agent demo.
Scaffold a small RAG chatbot on Oracle 26ai Free + langchain-oracledb + OCI Generative AI Grok 4 + sentence-transformers MiniLM-L6-v2 (Python-side embeddings, same model intermediate/advanced register inside Oracle) + Open WebUI. Three flavors that share one skeleton — PDF / Markdown / Web. For users new to Oracle who want a polished demo running in an afternoon.
Scaffold a Grok-4 tool-calling agent over an Oracle schema using langchain-oracledb + oracle-database-mcp-server + in-DB ONNX embeddings (registered MiniLM model, no external embedding API) + Open WebUI. For users who've built RAG before and want to rebuild it on the production-feeling Oracle stack.
Soccer analytics agent toolbelt. Gives Claude Code direct access to the Oracle-backed match data, ML predictions, and three-tier memory. Use when answering questions about football matches, building on the soccer agent, or exploring the World Cup dataset.
Bootstrap the soccer analytics agent workshop. Starts the Oracle AI Database Free container, applies schema, loads the FIFA dataset, optionally trains models, populates LangChain OracleVS hybrid retrieval plus semantic memory, applies LangGraph OracleDB observability, and verifies OCI GenAI access. Use when starting the workshop or resetting a stale environment.