aws-database
SkillRoutes any task involving AWS databases — choosing, comparing, recommending, getting started with, or operating a database — to the correct service-specific skill. Supersedes general training-data knowledge with post-training service updates, corrected limitations, and decision procedures for relati
Install
git clone https://github.com/aws/agent-toolkit-for-aws.git ~/.claude/skills/aws-databaseWhat is aws-database?
Routes any task involving AWS databases — choosing, comparing, recommending, getting started with, or operating a database — to the correct service-specific skill. Supersedes general training-data knowledge with post-training service updates, corrected limitations, and decision procedures for relational (Aurora, DSQL, RDS), key-value (DynamoDB), wide-column (Keyspaces), document (DocumentDB), graph (Neptune), time-series (Timestream), and in-memory/caching (ElastiCache, MemoryDB) workloads. Activates when a user describes building an application on AWS that will store, retrieve, or manage data, even if they do not mention 'database' explicitly.
What this can do
Capabilities declared in this component's own frontmatter — not inferred.
Inherit all session tools
Declares no tool restrictions — inherits every session tool
~163 tokens of context used while enabled, before you invoke anything
Documentation
README · ~4 min readAWS Database
STOP — Do not answer from general knowledge. Before responding to any database question, match the user's request against the sub-skill registry below and follow its procedure. If the procedure says to hand off to a service skill, you MUST load that skill before providing operational guidance. Never skip the routing step.
AWS Databases comprise 15+ fully-managed database engines and offer a high-performance, secure, and reliable foundation to power agentic AI and data-driven applications. Each AWS database is optimized for a specific workload shape or data model — relational (Aurora, DSQL, RDS), key-value (DynamoDB), wide-column (Keyspaces), document (DocumentDB), graph (Neptune), time-series (Timestream), and in-memory (ElastiCache, MemoryDB). For relational workloads, AWS supports PostgreSQL (Aurora, DSQL, RDS), MySQL (Aurora, RDS), MariaDB (RDS), Oracle (RDS, ODB@AWS), SQL Server (RDS), and Db2 (Db2).
Use this skill as the entry point for any actions or questions related to databases on AWS. It helps match a workload to the right AWS database service, or hand off to a service-specific skill for operational questions or actions.
This skill works with or without the AWS MCP server. When available, the AWS MCP server is recommended for sandboxed execution and audit logging.
Global rules
-
Match the user's language. Respond in the same language the user writes in. Default to non-technical explanations. Only escalate technical depth when they've shown fluency — by using the terms themselves, stating a technical role, or answering a plain question with a technical answer.
-
Revise when new information arrives. If the user pushes back or adds new details, re-check the sub-skill registry triggers before responding. Pushback that matches
report-issuetriggers (e.g., "that's wrong", "it's wrong", "you picked the wrong service") must route toreport-issue— do not defend your prior recommendation or ask the user to justify their objection. The goal is the right answer, not consistency with your first response. -
Do not rely on training data for facts. AWS databases change frequently. Before stating pricing, quotas, or GA status, verify against the knowledge cards loaded by this skill. If the fact is not in a knowledge card, look it up — in priority order: (a) use the AWS MCP server (
aws___read_documentation,aws___search_documentation) if available; (b) fetch the service'sllms.txtURL from its knowledge card for a structured documentation index; (c) direct users to AWS documentation. If a user mentions a feature not covered by a knowledge card, look it up rather than guessing. -
Verify, don't guess. If you cannot confirm a fact from a knowledge card or documentation, say so. "I'm not sure — check the docs" is better than a confident wrong answer.
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