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Db

Organization
oracle
db

Oracle Database guidance for SQL, PL/SQL, SQLcl, ORDS, Oracle Vector SDK, administration, app development, performance, security, migrations, and agent-safe database workflows. Use when the user asks to write, edit, rewrite, review, format, debug, tune, or explain SQL; create or refactor PL/SQL; use Oracle VecDB through the Python SDK, REST API, or DBMS_VECTOR_DATABASE package; use SQLcl, Liquibase, ORDS, JDBC, node-oracledb, Python, Java, .NET, or database frameworks; troubleshoot vector tables, embeddings, vector search, reranking, queries, sessions, locks, waits, indexes, optimizer plans, AWR, ASH, migrations, schemas, users, roles, privileges, backup, recovery, Data Guard, RAC, multitenant, containers, monitoring, auditing, encryption, VPD, or safe agent database operations.

Overview

Publisheroracle
Repositoryskills
Skill namedb
Stars
879
Forks
251
Bundled files
190
LicenseUPL-1.0
Links
Skill sourceRepository
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 190 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by oracle on GitHub. Read the source before you install it.

Installation

Install the Db AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/oracle/skills/tree/main/db
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/oracle/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/db .claude/skills/db
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Db in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Db on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Db is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Oracle Database Skills

This domain contains Oracle Database skills for administration, SQL and PL/SQL development, performance tuning, security, ORDS, SQLcl, migrations, frameworks, VecDB SDK/REST/PL/SQL workflows, OCR container guidance, and agent-safe database workflows.

How to Use This Domain

  1. Start with the routing table below.
  2. Read only the specific file or category you need.

Directory Structure

text
db/
├── admin/
├── agent/
├── appdev/
├── architecture/
├── backup-recovery/
├── containers/
├── design/
├── devops/
├── data-guard/
├── features/
├── frameworks/
├── migrations/
├── monitoring/
├── ords/
├── performance/
├── plsql/
├── security/
├── sql-dev/
├── sqlcl/
└── vecdb/

Category Routing

TopicDirectory
Data Guard, redo/undo logs, usersdb/admin/
Safe DML, destructive operation guards, idempotency, schema discovery, ORA- error handlingdb/agent/
JDBC, JDBC Extensions, Python, .NET, pooling, JSON, XML, spatial, Oracle Text, transactions, MLE, language driversdb/appdev/
RAC, Multitenant, Exadata, In-Memory, OCI database services, Data Guard architecturedb/architecture/
Backup, recovery, RMAN, Autonomous Recovery Service, Cloud Protectdb/backup-recovery/
OCR database-category container images and pull guidancedb/containers/
ERD, data modeling, partitioning, tablespacesdb/design/
Schema migrations, online operations, edition-based redefinition, testing, version controldb/devops/
Guidance and assistance for triaging data guard configuration and environment related issuesdb/data-guard/
AQ, DBMS_SCHEDULER, materialized views, DBLinks, APEX, vector search, SELECT AIdb/features/
SQLAlchemy, Django, Pandas, Spring JPA, MyBatis, TypeORM, Sequelize, Dapper, GORMdb/frameworks/
Migrations from PostgreSQL, MySQL, SQL Server, MongoDB, Snowflake, and moredb/migrations/
Alert log, ADR, health monitor, space management, top SQLdb/monitoring/
ORDS architecture, installation, REST design, authentication, monitoring, ORDS Concert Sample Appdb/ords/
AWR, ASH, explain plan, indexes, optimizer stats, wait events, memorydb/performance/
Package design, error handling, performance, collections, cursors, debuggingdb/plsql/
Privileges, Deep Data Security, VPD, masking, auditing, encryption, network securitydb/security/
SQL tuning, SQL patterns, dynamic SQL, injection avoidancedb/sql-dev/
SQLcl basics, scripting, Liquibase, formatting, DDL generation, data loading, MCP server, scheduler daemon, AWR, background jobs, schema comparison with DIFFdb/sqlcl/
Oracle Vector SDK setup and configuration, including database preparation, Python SDK, REST API, PL/SQL package, version prerequisites, vector tables, ingestion, models, search, reranking, indexes, and jobsdb/vecdb/

Key Starting Points

  • db/sqlcl/sqlcl-mcp-server.md
  • db/migrations/migration-assessment.md
  • db/performance/explain-plan.md
  • db/plsql/plsql-package-design.md
  • db/appdev/java-oracle-jdbc.md
  • db/devops/schema-migrations.md
  • db/security/deep-data-security.md
  • db/agent/schema-discovery.md
  • db/containers/container-selection-matrix.md
  • db/backup-recovery/autonomous-recovery-service.md
  • db/backup-recovery/cloud-protect.md
  • db/vecdb/vecdb-provisioning.md
  • db/vecdb/vecdb-architecture.md

Common Multi-Step Flows

TaskRecommended Sequence
Diagnose a slow queryexplain-plan → wait-events → optimizer-stats → awr-reports
Plan a migrationmigration-assessment → oracle-migration-tools → source-specific migrate-*.md → migration-cutover-strategy
Build RAG on Oracle Databaseai-profiles → vector-search → dbms-vector
Build a Java JDBC servicejava-oracle-jdbc → java-oracle-jdbc/dependencies → java-oracle-jdbc/connections → java-oracle-jdbc/sql → java-oracle-jdbc/pooling-production → java-oracle-jdbc/providers (cloud secrets, tracing, Spring, Pkl)
Perform agent-safe schema changeschema-discovery → destructive-op-guards → idempotency-patterns → schema-migrations
Set up AI-driven database access via MCPsecurity/deep-data-security (end-user authorization) → sqlcl-basics (save connections) → sqlcl-mcp-server (configure + start)
Set up an Oracle Vector SDK database deploymentvecdb-provisioning → Oracle Vector SDK Quick Start → Prepare an AI Database
Build vector-based applications for semantic search, RAG, or recommendations using Oracle Vector SDK's fixed-schema APIs through the Python SDK, REST, or PL/SQLvecdb-architecture → vecdb-api-reference → relevant capability file (vecdb-models, vecdb-vector-tables, vecdb-search, or vecdb-indexes)

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

and 130 more files.

Frequently asked questions

What does the Db AI skill do?

Oracle Database guidance for SQL, PL/SQL, SQLcl, ORDS, Oracle Vector SDK, administration, app development, performance, security, migrations, and agent-safe database workflows. Use when the user asks to write, edit, rewrite, review, format, debug, tune, or explain SQL; create or refactor PL/SQL; use Oracle VecDB through the Python SDK, REST API, or DBMS_VECTOR_DATABASE package; use SQLcl, Liquibase, ORDS, JDBC, node-oracledb, Python, Java, .NET, or database frameworks; troubleshoot vector tables, embeddings, vector search, reranking, queries, sessions, locks, waits, indexes, optimizer plans...

Why use Db on TypingMind?

Because you install it once and use it with any model. Db is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Db in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/oracle/skills/tree/main/db. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Db?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Db?

As many as you like. As long as a model supports skills, you can use Db with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Db AI skill free?

Yes. It is published on GitHub by oracle under the UPL-1.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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