Dsql
AWS LabsOfficialPublished by AWS Labs
- Skill
- Tool integration
- Data and AI
- Apache-2.0
- Low risk
- Has scripts
AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
The dsql skill provides a structured framework for interacting with Amazon Aurora DSQL. It encompasses schema management, migration strategies from MySQL and PostgreSQL, performance diagnostics, and bulk data loading. The skill integrates with MCP tools for direct database operations and provides extensive documentation on IAM authentication, multi-tenant patterns, and transaction management to ensure safe and efficient database operations.
What it does
- Executes SQL queries and DDL operations via MCP tools.
- Provides migration paths and type mapping for MySQL and PostgreSQL to DSQL.
- Offers diagnostic workflows for cluster performance and query plan explainability.
- Facilitates bulk data loading using specialized loaders.
- Enforces best practices for IAM authentication and scoped database roles.
- Validates SQL compatibility and provides linting for DSQL-specific constraints.
When to use it
- When building or migrating applications to Aurora DSQL.
- When performing schema changes or complex DDL migrations.
- When troubleshooting performance issues or query plan inefficiencies.
- When setting up multi-tenant database architectures.
- When bulk loading data into a DSQL cluster.
Advantages
- Ensures adherence to DSQL-specific transaction and concurrency limits.
- Promotes secure access patterns through IAM and scoped roles.
- Provides clear, phased workflows for complex tasks like performance tuning.
- Reduces migration friction with automated linting and type mapping guidance.
- Standardizes diagnostic reporting for query plan analysis.
Usage examples
- “How do I migrate my existing PostgreSQL schema to Aurora DSQL?”
- The agent will guide you through pg-migrations/type-mapping.md and schema-objects.md, providing steps to convert indexes, enums, and data types while ensuring compatibility.
- “My query is running slowly on DSQL, can you help?”
- The agent will initiate Workflow 9 (Query Plan Explainability) to analyze the query plan, check for full scans, and provide a structured diagnostic report.
- “How do I set up a multi-tenant table in DSQL?”
- The agent will provide instructions on using tenant_id in your schema design, enforcing it in WHERE clauses, and using separate transact calls for DDL.
- “What are the transaction limits for DSQL?”
- The agent will consult the limits-and-error-codes.md or awsknowledge tool to provide the exact limits for row modifications, data size, and duration.
Install
Download the skill as a ZIP:
https://mp-staging.autogineer.com/agent-skills/awslabs/dsql/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip dsql.zip -d .agents/skills
Documentation by AWS Labs
Amazon Aurora DSQL Skill
Aurora DSQL is a serverless, PostgreSQL-compatible distributed SQL database. This skill covers direct query execution via MCP tools, schema management, migrations, multi-tenant isolation, IAM auth, and bulk data loading via aurora-dsql-loader.
Reference Files
Load these files as needed for detailed guidance:
Core:
| Reference | When to Load | Contains |
|---|---|---|
| development-guide.md | ALWAYS before schema changes or DB operations | Best practices, DDL rules, transaction limits, foreign key constraints |
| foreign-keys.md | MUST load for foreign key operations or migrations | FK syntax, actions, validation, tenant keys |
| language.md | MUST load for language-specific choices | Driver selection, DSQL Connectors, connection code |
| access-control.md | MUST load for roles, grants, or sensitive data | Scoped role setup, IAM-to-database role mapping |
| troubleshooting.md | SHOULD load for errors or unexpected behavior | OCC and 23503, FK, connections, cluster state |
| limits-and-error-codes.md | SHOULD load before sizing batches, keys or indexes, or on 54000/0A000/54011 | Every limit, rejection and quota with SQLSTATE and exact message |
| dsql-examples.md | Load for implementation examples | Multi-tenant access, batch operations, identity and sequences, connection pooling |
| onboarding.md | User requests "Get started with DSQL" | Interactive step-by-step guide |
| occ-retry-patterns.md | MUST load for OCC retry code or conflict mitigation | Connectors, 40001 retry, non-retryable 23503, FK read conflicts, idempotent design |
MCP:
| Reference | When to Load | Contains |
|---|---|---|
| mcp-setup.md | Always for MCP server guidance | Setup instructions, 2 configuration options |
| mcp-tools.md | For MCP tool syntax and examples | Tool parameters, input validation |
| dsql-lint.md | MUST load before running dsql_lint or processing external SQL | Tool reference, fix statuses, unfixable error resolution |
DDL Migrations:
| Reference | When to Load | Contains |
|---|---|---|
| ddl-migrations/overview.md | MUST load for ALTER TYPE, SET NOT NULL, MODIFY PRIMARY KEY | Direct ALTER coverage and last-resort table recreation |
| ddl-migrations/column-operations.md | DROP COLUMN, ALTER TYPE, SET/DROP NOT NULL/DEFAULT | Column-level migration patterns |
| ddl-migrations/constraint-operations.md | ADD/DROP CONSTRAINT, VALIDATE CONSTRAINT, MODIFY PRIMARY KEY | Constraint and structural changes |
| ddl-migrations/batched-migration.md | Tables exceeding 3,000 rows | Batching patterns, progress tracking |
MySQL Migrations:
| Reference | When to Load | Contains |
|---|---|---|
| mysql-migrations/type-mapping.md | MUST load for MySQL → DSQL migration | Data type mappings, feature alternatives |
| mysql-migrations/ddl-operations.md | Translating MySQL DDL to DSQL | AUTO_INCREMENT, ENUM, SET, FK patterns |
| mysql-migrations/full-example.md | Complete MySQL table migration | End-to-end example with decision summary |
PostgreSQL Migrations:
| Reference | When to Load | Contains |
|---|---|---|
| pg-migrations/type-mapping.md | MUST load for DSQL NUMERIC or PG type questions | C collation rules, NUMERIC(p,s), JSON/JSONB |
| pg-migrations/index-conversion.md | MUST load for any index conversion or index support question | GIN/GiST/BRIN → btree, operator class removal, partial + expression indexes, sort order |
| pg-migrations/schema-objects.md | MUST load for ENUM, materialized views, extensions, multi-schema, CREATE FUNCTION | ENUM → CHECK, views, role/IAM mapping, LANGUAGE sql functions |
| pg-migrations/multi-region.md | Multi-region, active-active, or HA questions | Architecture, geographic partitioning |
ORM Guides:
| Reference | When to Load | Contains |
|---|---|---|
| orm-guides/overview.md | Migrating an ORM or using ORM locking with DSQL | Adapter names, locking, and key gotchas for Django/EF Core/Hibernate/Rails/SQLAlchemy |
Data Loading:
| Reference | When to Load | Contains |
|---|---|---|
| data-loading.md | Planning or running bulk loads with aurora-dsql-loader | Fresh-vs-warm partitions, resume/retry, --on-conflict semantics, throughput diagnostics |
System Diagnostics:
| Reference | When to Load | Contains |
|---|---|---|
| system-diagnostics/workflow.md | MUST load at Workflow 12 entry — cluster performance diagnostics | Prerequisites, 5 diagnostic phases, temporal comparison, handoff |
| system-diagnostics/wait-events.md | ALWAYS load when interpreting AAS results | Canonical DSQL wait event descriptions and investigation guidance |
| system-diagnostics/promql-patterns.md | Load when constructing PromQL queries | Reusable query templates for AAS breakdown, top-SQL, temporal compare |
Query Plan Explainability:
| Reference | When to Load | Contains |
|---|---|---|
| query-plan/workflow.md | MUST load at Workflow 9 entry — gates all other files | Trigger criteria, context disambiguation, routing, phased workflow |
| query-plan/plan-interpretation.md | MUST load at Workflow 9 Phase 0 | DSQL node types, Node Duration math, estimation-error bands |
| query-plan/catalog-queries.md | MUST load at Workflow 9 Phase 0 | pg_class/pg_stats/pg_indexes SQL, correlated-predicate verification |
| query-plan/guc-experiments.md | MUST load at Workflow 9 Phase 0 | GUC experiment procedures, 30-second skip protocol |
| query-plan/report-format.md | MUST load at Workflow 9 Phase 0 | Required report structure, element checklist, support request template |
| query-plan/query-rewrites-generic.md | SHOULD load at Phase 0; sub-files on-demand | Index of 10 generic rewrite patterns |
| query-plan/query-rewrites-dsql-specific.md | SHOULD load at Phase 0; sub-files on-demand | Index of DSQL-specific rewrite patterns |
Choosing How to Connect: MCP vs CLI/psql
The aurora-dsql MCP server binds a single cluster at startup (--cluster_endpoint), so
using it for another cluster means editing .mcp.json and restarting the session.
Use the
aurora-dsqlMCP tools (readonly_query,transact,get_schema) ONLY when the server already targets the cluster you need.Otherwise — unconfigured, disabled, or bound to a different cluster — do NOT reconfigure it. Use the CLI +
psqlpath instead:scripts/psql-connect.sh<cluster-id> --region <region> --command "SELECT ..."(mints an IAM token and runs viapsql).If you cannot confirm which cluster the MCP targets, confirm first or use the CLI/psql path — running against the wrong cluster is worse than the check.
The doc-only MCP tools (dsql_lint, dsql_*_documentation, dsql_recommend) need no cluster.
The CloudWatch MCP (Workflow 12) takes region/cluster_id per call, so one running server can
query clusters in any PromQL-enabled region (pass each cluster's region on the call). Details:
connectivity-tools.md.
MCP Tools Available
The aurora-dsql MCP server provides these tools:
Database Operations:
readonly_query - Execute SELECT queries (returns list of dicts)
transact - Execute DDL/DML statements in transaction (takes list of SQL statements)
get_schema - Get table structure for a specific table
SQL Validation:
dsql_lint - Validate SQL for DSQL compatibility and optionally auto-fix issues. Use before executing externally-sourced SQL.
Documentation & Knowledge:
dsql_search_documentation - Search Aurora DSQL documentation
dsql_read_documentation - Read specific documentation pages
dsql_recommend - Get DSQL best practice recommendations
Note: There is no list_tables tool. Use readonly_query with information_schema.
See mcp-setup.md for detailed setup instructions. See mcp-tools.md for detailed usage and examples.
AWS Knowledge MCP (awsknowledge)
Consult for verifying DSQL service limits before advising users. The numeric limits below are defaults that may change — when a user's decision depends on an exact limit, verify it first:
| Limit | Default | Verify query |
|---|---|---|
| Max row modifications per transaction | 3,000 | aurora dsql transaction limits |
| Max data size per transaction | 10 MiB | aurora dsql transaction limits |
| Max transaction duration | 5 minutes | aurora dsql transaction limits |
| Max connections per cluster | 10,000 | aurora dsql connection limits |
| Auth token expiry | 15 minutes | aurora dsql authentication token |
| Max connection duration | 60 minutes | aurora dsql connection limits |
| Max indexes per table | 24 incl. PK | aurora dsql index limits |
| Max columns per index | 8 | aurora dsql index limits |
| IDENTITY/SEQUENCE CACHE values | 1 or >= 65536 | aurora dsql sequence cache |
| Supported column data types | See docs | aurora dsql supported data types |
When to verify: Before recommending batch sizes, connection pool settings, or schema designs where hitting a limit would cause failures; any time the exact number can affect user decision. For the full limit set with each SQLSTATE and its exact error message, see limits-and-error-codes.md; where it marks a value observed and the docs differ, use the observed value.
Fallback: If awsknowledge is unavailable, use the defaults above and flag that limits should be verified against DSQL documentation.
CLI Scripts Available
Bash scripts in scripts/ for cluster management (create, delete, list, cluster info), psql connection, and bulk data loading from local/s3 csv/tsv/parquet files. See scripts/README.md for usage and hook configuration.
Quick Start
Pick a connection path: confirm the
aurora-dsqlMCP targets your cluster; if not, use the CLI/psqlpath instead — see Choosing How to Connect. The steps below name MCP tools; the equivalent SQL runs the same way throughpsql-connect.sh --command "...".Explore: Use
readonly_querywithinformation_schemato list tables. Useget_schemafor table structure.Query: Use
readonly_queryfor SELECT queries. MUST includetenant_idin WHERE for multi-tenant apps. MUST build SQL withsafe_query.build().Schema changes: Use
transactwith one DDL per transaction. MUST batch DML under 3,000 rows. MUST useCREATE INDEX ASYNCin a separate call. Usedsql_lintto validate first.Bulk load data: Use
aurora-dsql-loaderfor CSV/TSV/Parquet. Load data-loading.md for details. Use--dry-runfirst.
Performance Routing
When the user reports a performance problem, use this table to select the correct workflow:
| User signal | Route to |
|---|---|
| General performance complaint, "cluster is slow", "something changed", latency regression, no specific query identified | Workflow 12 (System Diagnostics) — observe via CloudWatch first |
| Specific query or query_id to investigate, "explain this plan", "why is this query slow" | Workflow 9 (Query Plan Explainability) — direct EXPLAIN analysis |
| OCC conflicts, commit errors, retry storms | Workflow 12 (System Diagnostics) — confirm via CW metrics before investigating |
| Cost optimization, "where is compute time spent" | Workflow 12 (System Diagnostics) — identify top contributors first |
Rule: When in doubt, start with Workflow 12. It identifies specific queries to investigate and routes to Workflow 9 with context.
Common Workflows
Workflow 1: Create Multi-Tenant Schema
Create tenant-owned tables with
tenant_idusing separatetransactcallsUse composite tenant FKs for tenant-owned parents and ordinary FKs for shared parents
Create tenant and query-pattern indexes with separate
CREATE INDEX ASYNCcallsVerify with
get_schema
MUST issue each DDL in its own transact call:
transact(["CREATE TABLE ..."])MUST serialize arrays into a single-column representation — DSQL has no array column type; PREFER
JSONB(operators work directly); MAY useTEXTwhen the column is opaque to the database; ASK the user. ForJSONBarrays, expand at query time withjsonb_array_elements_text(data)
Workflow 2: Safe Data Migration
MUST validate every DDL with dsql_lint(fix=true) before executing. DML does not require linting.
Validate DDL with
dsql_lint(sql=..., fix=true)— handle diagnostics per dsql-lint.mdExecute the reviewed
fixed_sqlwhen present, otherwise the reviewed source statementAdd column in its own
transactcallPopulate existing rows with UPDATE (batched under 3,000 rows)
Verify with readonly_query COUNT
Create an index if needed: validate then execute the reviewed DDL in its own
transactcall
MUST issue each
ALTER TABLEin its owntransactcall — DSQL rejects multi-DDL transactions withmultiple ddl statements not supported in a transactionMUST add column with only name and type; apply DEFAULT via separate UPDATE
MUST batch updates under 3,000 rows in separate transact calls
Recovery: Resume failed batches by filtering WHERE new_column IS NULL.
Workflow 3: Bulk Data Loading
Use aurora-dsql-loader for CSV, TSV, or Parquet loads. MUST load data-loading.md before advising on throughput or diagnosing slow loads.
Validate with
--dry-runfirstRun with
--manifest-diron persistent storage (not/tmp— tmpfs on AL2023, lost on crash) and--headerif file has a header rowOn failure: resume with
--resume-job-id; for duplicates use--on-conflict do-nothingFor large tables: create secondary indexes after load using
CREATE INDEX ASYNC
Workflow 4: Foreign Key Constraints
MUST load and follow foreign-keys.md before creating, altering, dropping, or migrating foreign keys.
Workflow 5: Query with Tenant Isolation
MUST authorize the caller against the tenant — format validation does not establish authorization
MUST build SQL with
safe_query.build()— useallow()/regex()for values (emits'v'),ident()for table/column names (emits"v"). See input-validation.mdMUST include
tenant_idin the WHERE clause; reject cross-tenant access at the application layer
Workflow 6: Set Up Scoped Database Roles
MUST load access-control.md for role setup, IAM mapping, and schema permissions.
Workflow 7: Table Recreation DDL Migration
For ALTER COLUMN TYPE, SET NOT NULL, or MODIFY PRIMARY KEY, MUST
load ddl-migrations/overview.md. Use a direct ALTER form
when supported; otherwise, present a user-approved table-recreation plan.
Workflow 8: Validate and Migrate to DSQL
MUST load dsql-lint.md before running dsql_lint. Run dsql_lint(sql=source_sql, fix=true) to validate and auto-convert. For MySQL-origin SQL, MUST cross-check against mysql-migrations/type-mapping.md even when lint returns clean. On parse_error, fall back to manual conversion then re-lint.
Workflow 9: Query Plan Explainability
Explains why the DSQL optimizer chose a particular plan. Triggered by slow queries, high DPU, unexpected Full Scans, or plans the user doesn't understand. REQUIRES a structured Markdown diagnostic report as the deliverable.
MUST load query-plan/workflow.md at entry — it defines trigger criteria, context disambiguation, routing, and the full phased workflow (Phase 0–4). Workflow.md specifies which reference files to load at each phase.
Safety. Plan capture uses readonly_query exclusively. Rewrite DML to SELECT for plan capture. MUST NOT use transact --allow-writes for plan capture.
Workflow 10: Full PostgreSQL → DSQL Schema Migration
MUST load pg-migrations/type-mapping.md, pg-migrations/index-conversion.md, pg-migrations/schema-objects.md, and foreign-keys.md. Run dsql_lint(fix=true) first for mechanical fixes, preserve foreign-key relationships, translate unsupported source syntax or options, then apply semantic conversions from the pg-migrations references for unfixable diagnostics and patterns the linter cannot handle. Re-lint the final output before deploying.
Workflow 11: ORM Migration and Locking (Django/EF Core/Hibernate/Rails/SQLAlchemy)
Load orm-guides/overview.md for adapter names, locking guidance, and framework-specific gotchas.
Workflow 12: System Diagnostics (CloudWatch AAS)
Diagnose cluster performance by querying db.active_sessions.avg via PromQL. Detects temporal anomalies in wait event distribution, identifies regressed queries, and routes to Workflow 9 for per-query investigation.
Requires: CloudWatch MCP server (awslabs.cloudwatch-mcp-server) enabled and configured with PromQL access in the same region as the cluster — see mcp/mcp-setup.md for enabling it, region requirements, and the session restart needed for its tools to register.
MUST load system-diagnostics/workflow.md at entry — it defines prerequisites, 5 diagnostic phases, temporal baselines, and the routing to Workflow 9 for identified queries.
Error Scenarios
awsknowledgereturns no results: Use the default limits in the table above and note that limits should be verified against DSQL documentation.dsql_lintunavailable or timing out: See the Error Handling section of dsql-lint.md. Do not silently skip validation — inform the user and require explicit confirmation before proceeding with manual rules from development-guide.md.OCC serialization error (
40001): Retry with backoff, and keep(OC001)in the loop too — see occ-retry-patterns.md.Foreign key violation (
23503): Correct the relationship or referential action; MUST NOT send it through the40001retry loop — see troubleshooting.md.Transaction exceeds limits: Split batches under 3,000 rows and 10 MiB; size is checked at
COMMIT— see limits-and-error-codes.md to size them and batched-migration.md for the pattern.Token expiration mid-operation: Generate a fresh IAM token — see authentication-guide.md. See troubleshooting.md for other issues.
Additional Resources
Files
- ATTRIBUTION.mdAdded by AutoGineer868 B
- LICENSELicence file added by AutoGineer9.9 KiB
- NOTICELicence file added by AutoGineer89 B
- SKILL.md27.9 KiB
- mcp/mcp-setup.md6.7 KiB
- mcp/mcp-tools.md2.0 KiB
- mcp/platforms/claude-code.md3.6 KiB
- mcp/platforms/codex.md1.6 KiB
- mcp/platforms/gemini.md2.1 KiB
- mcp/platforms/kiro.md2.8 KiB
- mcp/tools/database-tools.md4.6 KiB
- mcp/tools/documentation-tools.md1.3 KiB
- mcp/tools/input-validation.md3.3 KiB
- mcp/tools/safe_query.pyScript10.4 KiB
- mcp/tools/workflow-patterns.md3.1 KiB
- references/access-control.md5.0 KiB
- references/auth/authentication-guide.md4.6 KiB
- references/auth/connectivity-tools.md8.7 KiB
- references/auth/scaling-guide.md3.9 KiB
- references/data-loading.md6.0 KiB
- references/ddl-migrations/batched-migration.md2.5 KiB
- references/ddl-migrations/column-operations.md5.2 KiB
- references/ddl-migrations/constraint-operations.md6.7 KiB
- references/ddl-migrations/overview.md4.8 KiB
- references/development-guide.md9.6 KiB
- references/dsql-examples.md1.5 KiB
- references/dsql-lint.md10.8 KiB
- references/examples/connection.md2.5 KiB
- references/examples/data-operations.md2.9 KiB
- references/examples/migrations.md1.6 KiB
- references/examples/patterns.md5.5 KiB
- references/examples/schema.md1.6 KiB
- references/foreign-keys.md6.0 KiB
- references/language.md8.6 KiB
- references/limits-and-error-codes.md19.2 KiB
- references/mysql-migrations/ddl-auto-increment.md4.3 KiB
- references/mysql-migrations/ddl-batching.md1.0 KiB
- references/mysql-migrations/ddl-column-changes.md1.3 KiB
- references/mysql-migrations/ddl-constraints.md782 B
- references/mysql-migrations/ddl-operations.md1.5 KiB
- references/mysql-migrations/ddl-structural.md3.7 KiB
- references/mysql-migrations/ddl-type-alternatives.md4.5 KiB
- references/mysql-migrations/full-example.md7.3 KiB
- references/mysql-migrations/type-mapping.md14.3 KiB
- references/occ-retry-patterns.md9.6 KiB
- references/onboarding.md13.8 KiB
- references/orm-guides/overview.md10.9 KiB
- references/pg-migrations/index-conversion.md15.7 KiB
- references/pg-migrations/multi-region.md2.9 KiB
- references/pg-migrations/schema-objects.md15.0 KiB
- references/pg-migrations/type-mapping.md5.3 KiB
- references/query-plan/catalog-queries.md8.0 KiB
- references/query-plan/guc-experiments.md7.5 KiB
- references/query-plan/plan-interpretation.md15.0 KiB
- references/query-plan/query-rewrites-dsql-specific.md900 B
- references/query-plan/query-rewrites-generic.md1.9 KiB
- references/query-plan/query-rewrites/cte-late-materialization.md1.4 KiB
- references/query-plan/query-rewrites/flatten-union-all.md946 B
- references/query-plan/query-rewrites/left-join-to-inner.md794 B
- references/query-plan/query-rewrites/not-in-to-not-exists.md1.4 KiB
- references/query-plan/query-rewrites/or-to-in.md889 B
- references/query-plan/query-rewrites/propagate-filter.md1.0 KiB
- references/query-plan/query-rewrites/push-computation-to-constant.md1.0 KiB
- references/query-plan/query-rewrites/push-group-by-into-subquery.md1.6 KiB
- references/query-plan/query-rewrites/reltuples-estimate.md1.2 KiB
- references/query-plan/query-rewrites/split-large-joins.md2.2 KiB
- references/query-plan/query-rewrites/subquery-unnesting-correlated.md1.6 KiB
- references/query-plan/query-rewrites/subquery-unnesting-scalar.md1.4 KiB
- references/query-plan/query-rewrites/subquery-unnesting-uncorrelated.md1.4 KiB
- references/query-plan/report-format.md10.9 KiB
- references/query-plan/workflow.md9.4 KiB
- references/system-diagnostics/promql-patterns.md8.6 KiB
- references/system-diagnostics/wait-events.md13.7 KiB
- references/system-diagnostics/workflow.md19.4 KiB
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references/onboarding.md
Aurora DSQL Get Started Guide
Overview
This guide provides steps to help users get started with Aurora DSQL in their project. It sets up their DSQL cluster with IAM authentication and connects their database to their code by understanding the context within the codebase.
Use Case
These guidelines apply when users say "Get started with DSQL" or similar phrases. The user's codebase may be mature (with existing database connections) or have little to no code - the guidelines should apply to both cases.
Contents
Overview
Use Case
Agent Communication Style
Get Started with DSQL (Interactive Guide) — 10-step linear walkthrough
DSQL Best Practices
Additional Resources
Agent Communication Style
Keep all responses succinct:
ALWAYS tell the user what you did.
Responses MUST be concise and concrete.
ALWAYS contain descriptions to necessary steps.
ALWAYS remove unnecessary verbiage.
Example:
"Created an inventory table with 4 columns"
"Updated the product column to be NOT NULL"
Ask direct questions when needed:
ALWAYS ask clarifying questions to avoid inaccurate assumptions
User ambiguity SHOULD result in questions.
MUST clarify incompatible user decisions
Example:
"What column names would you like in this table?"
"What is the column name of the primary key?"
"Should this column be JSON, JSONB, or TEXT? (PREFER JSONB for
@>/?queries; JSON for write-heavy or byte-exact paths; TEXT for columns the database never inspects.)"
Examples:
Good: "Generated auth token. Ready to connect with psql?"
Bad: "I'm going to generate an authentication token using the AWS CLI which will allow you to connect to your database. This token will be valid for..."
Get Started with DSQL (Interactive Guide)
TRIGGER PHRASE: When the user says "Get started with DSQL", "Get started with Aurora DSQL", or similar phrases, provide an interactive onboarding experience by following these steps:
Before starting: Let the user know they can pause and resume anytime by saying "Continue with DSQL setup" if they need to come back later.
RESUME TRIGGER: If the user says "Continue with DSQL setup" or similar, check what's already configured (AWS credentials, clusters, MCP server, connection tested) and resume from where they left off. Ask them which step they'd like to continue from or analyze their setup to determine automatically.
Step 1: Verify Prerequisites
Check AWS credentials:
aws sts get-caller-identityIf not configured:
Guide them through
aws configureMUST verify IAM permissions include
dsql:CreateCluster,dsql:GetCluster,dsql:DbConnectAdminRecommend
AmazonAuroraDSQLConsoleFullAccessmanaged policy
Check PostgreSQL client:
psql --version**If missing OR version <=14:** DSQL requires SNI support from psql >=14.
macOS:
brew install postgresql@17Linux (Debian/Ubuntu):
sudo apt-get install postgresql-clientLinux (RHEL/CentOS/Amazon Linux):
sudo yum install -y https://download.postgresql.org/pub/repos/yum/reporpms/EL-9-x86_64/pgdg-redhat-repo-latest.noarch.rpm sudo yum install -y postgresql17
Step 2: Check for Existing Clusters
Set region (uses AWS_REGION or REGION if set, defaults to us-east-1):
REGION=${AWS_REGION:-${REGION:-us-east-1}}
echo $REGIONList clusters in the region:
aws dsql list-clusters --region $REGIONIf they have NO clusters:
Ask: "Would you like to create a new DSQL cluster in $REGION or a different region?"
If yes, proceed to create single-region cluster
If they want different region, ask which one and update REGION variable
If they have ANY clusters:
List ALL cluster identifiers with creation dates and status
Ask: "Would you like to use one of these clusters or create a new one?"
If using existing, proceed to Step 3.
If creating new:
"Which region would you like to create a enw cluster in?"
Immediately update REGION variable
Confirm all selections before proceeding.
Create cluster command (if needed):
aws dsql create-cluster --region $REGION --tags '{"Name":"my-dsql-cluster","created_by":"<model-id>"}'Wait for ACTIVE status (takes ~60 seconds):
aws dsql get-cluster --identifier CLUSTER_ID --region $REGIONStep 3: Get Cluster Connection Details
Construct cluster endpoint:
CLUSTER_ID="<selected-cluster-id>"
CLUSTER_ENDPOINT="${CLUSTER_ID}.dsql.${REGION}.on.aws"
echo $CLUSTER_ENDPOINTStore endpoint for their project environment:
Check for
.envfile or environment configAdd or update:
DSQL_ENDPOINT=<endpoint>Add region:
AWS_REGION=$REGIONALWAYS try reading
.envfirst before modifyingIf file is unreadable, use:
echo "DSQL_ENDPOINT=$CLUSTER_ENDPOINT" >> .env
Step 4: Set Up MCP Server (Optional)
Would the user like to be guided through setting up the MCP server?
If so, follow the steps detailed in mcp-setup.md
MCP server provides:
Direct query execution from agent
Schema exploration tools
Simplified database operations
Step 5: Test Connection
Generate authentication token and connect:
export PGPASSWORD=$(aws dsql generate-db-connect-admin-auth-token \
--region $REGION \
--hostname $CLUSTER_ENDPOINT \
--expires-in 3600)
export PGSSLMODE=require
export PGAPPNAME="<app-name>/<model-id>"
psql --quiet -h $CLUSTER_ENDPOINT -U admin -d postgresVerify with test query:
SELECT current_database(), version();If connection fails:
Check token expiration (regenerate if needed)
Verify SSL mode is set
Confirm cluster is ACTIVE
Check IAM permissions
Step 6: Understand the Project
First, check if this is an empty/new project:
Look for existing source code, routes, or application logic
Check if it's just minimal boilerplate
If empty or near-empty project:
Ask briefly (1-2 questions): What are they building? Any specific tech preferences?
Remember context for subsequent steps
If established project:
Skip questions - infer from codebase
Check for existing database code or ORMs
Update relevant code to use DSQL
ALWAYS reference ./development-guide.md before making schema changes
Step 7: Install Database Driver
Based on their language, install appropriate driver (some examples):
JavaScript/TypeScript:
npm install @aws-sdk/credential-providers @aws-sdk/dsql-signer pg tsx
npm install @aws/aurora-dsql-node-postgres-connectorPython:
pip install psycopg2-binary
pip install aurora-dsql-python-connectorGo:
go get github.com/jackc/pgx/v5Rust:
cargo add sqlx --features postgres,runtime-tokio-native-tls
cargo add aws-sdk-dsql tokio --features fullFor implementation patterns, reference ./dsql-examples.md and ./language.md
Step 8: Schema Setup
Check for existing schema:
Search for
.sqlfiles, migration folders, ORM schemas (Prisma, Drizzle, TypeORM)
If existing schema found:
Show what you found
Ask: "Found existing schema definitions. Want to migrate these to DSQL?"
If yes, MUST verify DSQL compatibility:
No SERIAL types (use
GENERATED AS IDENTITYwith sequences, or UUID)Preserve foreign-key relationships; load
foreign-keys.mdfor DSQL-specific ALTER, validation, and tenant-key guidanceArrays must be serialized into a single column — PREFER
JSONBwhen querying inside the value (@>,?,jsonb_array_elements_text(data), indexed JSONB paths); MAY useTEXTfor columns the database never inspects;JSONis also valid for write-heavy or byte-exact paths. ASK the user.SHOULD keep existing
JSONcolumns asJSON; MAY upgrade toJSONBif JSONB-only operators or indexed paths are neededVerify column types against the supported data types list
Reference
./development-guide.mdfor full constraints
If no schema found:
Ask if they want to:
Create simple example table
Design custom schema together
Skip for now
If creating example table:
Use MCP server or psql to execute:
CREATE TABLE users (
id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
email VARCHAR(255) UNIQUE NOT NULL,
name VARCHAR(255),
created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
);
CREATE INDEX ASYNC idx_users_email ON users(email);For custom schema:
Ask about their app's needs
Design tables following DSQL constraints
Reference
./dsql-examples.mdfor patternsALWAYS use
CREATE INDEX ASYNCfor all indexes
Step 9: Set Up Scoped Database Roles
Recommend creating scoped roles before application development begins.
Ask: "Would you like to set up scoped database roles for your application? This is recommended over using
admindirectly."If yes, follow access-control.md for detailed guidance
At minimum, guide creating one application role:
-- As admin
CREATE ROLE app_user WITH LOGIN;
AWS IAM GRANT app_user TO 'arn:aws:iam::<account-id>:role/<AppIAMRole>';
GRANT USAGE ON SCHEMA public TO app_user;
GRANT SELECT, INSERT, UPDATE, DELETE ON ALL TABLES IN SCHEMA public TO app_user;If the application handles sensitive user data, recommend a separate schema:
CREATE SCHEMA users_schema;
GRANT USAGE ON SCHEMA users_schema TO app_user;
GRANT SELECT, INSERT, UPDATE ON ALL TABLES IN SCHEMA users_schema TO app_user;
GRANT CREATE ON SCHEMA users_schema TO app_user;After setup, application connections should use
generate-db-connect-auth-token(not the admin variant)
Step 10: What's Next
Let them know you're ready to help with more:
"You're all set! Here are some things I can help with - feel free to ask about any of these (or anything else):
Schema design and migrations following DSQL best practices
Writing queries with proper tenant isolation
Connection pooling and token refresh strategies
Multi-region cluster setup for high availability
Performance optimization with indexes and query patterns
Setting up additional scoped roles for different services"
Important Notes:
ALWAYS be succinct - guide step-by-step without verbose explanations
ALWAYS check
./development-guide.mdbefore schema operationsALWAYS use MCP tools for queries when available (with user permission)
ALWAYS track MCP status throughout the session
ALWAYS validate DSQL compatibility for existing schemas
ALWAYS provide working, tested commands
MUST handle token expiration gracefully (15-minute default, 1-hour recommended)
MCP Server Workflow:
If MCP enabled: Use MCP tools for database operations, continuously update user on cluster state
If MCP not enabled: Provide CLI commands and manual SQL queries
Agent must adapt workflow based on MCP availability
DSQL Best Practices
Critical Constraints
ALWAYS follow these rules:
Indexes: Use
CREATE INDEX ASYNC- synchronous index creation not supportedSerialization: Arrays must be serialized into a single column — PREFER
JSONB(operators work directly); MAY useTEXTfor columns the database never inspects. For document columns,JSONis also a valid choice (write-heavy or byte-exact paths). ASK the user.Referential Integrity: Use foreign key constraints; add post-creation constraints with
NOT VALIDand validate withALTER TABLE ASYNCDDL Operations: Execute one DDL per transaction, no mixing with DML
Transaction Limits: Maximum 3,000 row modifications, 10 MiB data size per transaction
Token Refresh: Regenerate auth tokens before 15-minute expiration
SSL Required: Always set
PGSSLMODE=requireorsslmode=require
DSQL-Specific Features
Leverage Aurora DSQL capabilities:
Serverless: True scale-to-zero with consumption-based pricing
Distributed: Active-active writes across multiple regions
Strong Consistency: Immediate read-your-writes across all regions
IAM Authentication: No password management, automatic token rotation
PostgreSQL Compatible: Supports 12 Database Drivers, 4 ORMs, and 4 Adapters/Dialects as listed.
For detailed patterns, see ./development-guide.md
Additional Resources
Requirements and compatibility
Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta
“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.
Needs: Needs an MCP server, Needs Python, Needs Node.js
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Attribution and licence
- Published by
- AWS Labs
- Publisher
- AWS Labs (Official)
- Source
- awslabs/agent-plugins · plugins/databases-on-aws/skills/dsql · commit fbefb37
- Licence
- Apache License 2.0 (redistribution allowed)
- LICENSE (added by AutoGineer from LICENSE)
- NOTICE (added by AutoGineer from NOTICE)
- ATTRIBUTION.md (written by AutoGineer)
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