oracle-devrel

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.

Senior UI/UX Engineer. Architect digital interfaces overriding default LLM biases. Enforces metric-based rules, strict component architecture, CSS hardware acceleration, and balanced design engineering.

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.

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 a langchain-oracledb store layer — multi-collection OracleVS wrapper, metadata-as-string monkeypatch, embedder-dim assertion, OracleChatHistory subclass (langchain-oracledb does not ship one). Use when a project needs Oracle as its LangChain vector store and chat-history backend.

Maintain, extend, validate, package, and functionally test the OKE DevOps Starter Resource Manager stack. Use when changing its Terraform, Resource Manager schema, OCI DevOps repositories, build or deployment pipelines, Helm charts, cluster-administration workflow, documentation, or release archive.

Use when enhancing Oracle Cloud Infrastructure Log Analytics dashboards, saved searches, visualizations, widget layouts, tile-in-link layouts, drilldowns, app/APM log queries, or detection-rule-backed alerting. Apply this skill whenever dashboards have overlapping widgets, query fields need source/parser validation, saved-search visualization metadata is changing, or detection rules and dashboard widgets need to be correlated. Also use when extending the Microsoft Sentinel KQL → Logan QL converter — operator extractions, canonicalizer or tier-classifier changes, mapping-allow-list edits, or designing a similar source-language converter (Splunk SPL, Elastic ES|QL) on top of the same `scripts/kql/` + OPERATOR_REGISTRY scaffolding.

generate and safely execute oracle autonomous ai lakehouse data loading and oci object storage lakehouse access workflows using dbms_cloud. use when the user wants to list oci object storage files, choose files or prefixes to load, create conservative csv staging tables, generate or run copy_data or copy_collection, tune dbms_cloud format options, load json documents into soda collections, create external tables to query apache iceberg data stored in oci object storage using direct metadata.json or hadoop catalog patterns, monitor user_load_operations or dba_load_operations, inspect logfile_table or badfile_table, troubleshoot rejected rows, reconcile loads, or profile staged data after loading. this skill is mcp-first with generate-only fallback and is scoped to oci object storage and dbms_cloud-based workflows.

inspect sql-observable operational evidence for one connected oracle autonomous ai lakehouse. use when users ask for maintenance notifications, patch identifiers or patch details, client errors, lockdown profile errors, operator access audit evidence, unified audit highlights, active or blocking sessions, invalid objects, compile errors, table or partition access statistics, or an operations summary based only on sql evidence. this skill is read-only, sql/mcp-first, and does not use oci apis, oci events, console, cli, lifecycle actions, resource principal views, or external schedulers.

Create or update a Codex MCP server entry for Oracle Autonomous Database, refresh ADB bearer token, and optionally bootstrap default DB tools (LIST_SCHEMAS, LIST_OBJECTS, GET_OBJECT_DETAILS, EXECUTE_SQL).