Querying Data Lake
by aws0d6167ad2e6dNo license2.8K starsListed Oct 8, 2026Updated Oct 8, 2026Repository updated today
Execute and manage Athena SQL queries across default and federated catalogs (Glue, S3 Tables, Redshift). Triggers on phrases like: query data, run SQL, athena query, analyze table, SQL query, workgroup status, profile table, query Redshift catalog, query S3 Tables. Do NOT use for finding specific data assets (use finding-data-lake-assets), full catalog audits (use exploring-data-catalog), importing data (use ingesting-into-data-lake).
Add to a SourceWeft workspace
- Open the skill in your dashboard and add it to a workspace.
- Enable it for the chats that should use it.
This skill is instructions only: it ships no scripts to execute.
Add to SourceWeftYou will be asked to sign in first, then taken straight to this skill.
Ask your agent to install it
Paste this prompt into Claude Code, Codex, Cursor or another agent that can run commands — or into SourceWeft chat. The agent reads this skill's install guide, shows you its source, license and scripts, and installs it with the SourceWeft CLI once you agree.
Read https://sourceweft.com/skills/gh-aws-agent-toolkit-for-aws-querying-data-lake/install.md and install the skill it describes. Before installing, show me its source, license and whether it ships scripts, and wait for my OK. Ask me before changing anything else on my machine.Install it yourself from a terminal
For Claude Code, Codex, Cursor and other local agents. The SourceWeft CLI fetches the skill from its source repository at the commit scanned here, and verifies every file against the hashes recorded when the skill was scanned. If anything differs, nothing is written.
npx @sourceweft/cli skills install gh-aws-agent-toolkit-for-aws-querying-data-lakeAdd --agent claude-code, codex, cursor or universal to choose which agent gets it (Claude Code by default).
Upstream installer — not verified by SourceWeft
The open-source skills installer fetches the same pinned commit, but does not check the files against the hashes SourceWeft recorded.
npx skills add https://github.com/aws/agent-toolkit-for-aws/tree/0d6167ad2e6dfb858098c4162fe74d04c975532f/plugins/aws-data-analytics/skills/querying-data-lakeSource and attribution
Source:aws/agent-toolkit-for-awsinplugins/aws-data-analytics/skills/querying-data-lakeat commit0d6167a
License: No license
Content belongs to its original authors. SourceWeft indexes it from a public repository.
More from aws/agent-toolkit-for-aws
Signing In To Aws
aws
Guides developers through obtaining short-term AWS CLI/SDK credentials with the aws login command.
Aws Well Architected Review
aws
Reviews AWS workloads against the live Well-Architected Framework, evaluating every best practice and producing an evidence-backed report.
Aws Storage
aws
Advises on selecting, comparing, and operating AWS object, file, and block storage services.
Aws Serverless
aws
Routes AWS serverless requests to a compute form factor and the specialized skill that owns it.
Aws Security
aws
Reviews AWS security service configuration and summarizes findings across GuardDuty, Inspector, Security Hub, Macie, Detective and Security Lake.
Aws Sdk Swift Usage
aws
Reference patterns for writing Swift code with the AWS SDK for Swift package.
More in Data & Analytics
Spanner Basics
Guides Google Cloud Spanner administration, schema design, querying and performance diagnosis.
Gke Cost Analysis
Answers natural-language questions about GKE cluster and workload costs using BigQuery billing exports and live cluster metrics.
Datalineage Bigquery Asset Impact Analysis
Guides an agent through downstream impact (blast radius) analysis for a BigQuery table or view using Data Lineage.
Bigquery Troubleshooting
Diagnoses failing, slow, or unexpectedly expensive BigQuery jobs through structured root-cause workflows.
Bigquery Optimization
Guides BigQuery cost and performance optimization across capacity editions, storage layout, and SQL queries.
Bigquery Bigframes
Guides writing Python code with BigQuery DataFrames (BigFrames) for data processing, analysis, and machine learning.