analyzing-release-read…
Trigger a pre-merge release readiness review on a GitHub PR, GitLab MR, or local branch. Use when the user wants to analyze code changes for risk, correctness,…
Resolve data lake and lakehouse asset references across Glue Data Catalog, S3, S3 Tables, and Redshift. Triggers on: find the table, where is our data, which table has, locate dataset, find data for, search catalog, what tables match, Redshift table, lakehouse table, data lake
$ npx -y skills add aws/agent-toolkit-for-aws --skill finding-data-lake-assets --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/finding-data-lake-assetsContext preview
The summary Claude sees to decide when to auto-load this skill.
Resolve data lake and lakehouse asset references across Glue Data Catalog, S3, S3 Tables, and Redshift. Triggers on: find the table, where is our data, which table has, locate dataset, find data for, search catalog, what tables match, Redshift table, lakehouse table, data lake
name: finding-data-lake-assets description: >- Resolve data lake and lakehouse asset references across Glue Data Catalog, S3, S3 Tables, and Redshift. Triggers on: find the table, where is our data, which table has, locate dataset, find data for, search catalog, what tables match, Redshift table, lakehouse table, data lake table, warehouse table, reverse lookup S3 path. Do NOT use for: full catalog audits (use exploring-data-catalog), running queries (use querying-data-lake), creating tables (use creating-data-lake-table). metadata: version: "2" argument-hint: "'[table-name|keyword|column-name|s3://path]'"
Resolves data lake asset references to concrete catalog entries. Acts as a resolver for other skills and direct user requests. Covers Glue, S3, S3 Tables, and Redshift. Optimized for low token usage — return the answer fast and get out of the way.
**Constraints for parameter acquisition:**
You MUST execute commands using AWS MCP server tools when connected — they provide validation, sandboxed execution, and audit logging. Fall back to AWS CLI only if MCP is unavailable. You MUST explain each step before executing.
Check for required tools and AWS access before searching.
**Constraints:**
The customer may publish **context skill assets** in the Glue Data Catalog that map their business language to the real tables — canonical names and aliases, join keys, metrics, usage notes, descriptions — that the raw schema does not carry. When present, this catalog is often enough to answer the request on its own.
These are the **Glue Discovery** operations (`SearchAssets` / `GetAsset` / `ListIterableForms` / `BatchGetIterableForms`) — a distinct metadata-search surface, NOT the legacy `glue search-tables` used in Step 5. They are **experimental** — not available in every CLI build. Gate the lookup on two checks first:
1. **Availability.** Confirm the `GetAsset` operation exists in the caller's Glue CLI model (redirect output so the CLI pager cannot block a non-interactive agent):
aws glue get-asset help > /dev/null 2>&1 # exit 0 = available. exit 2 (with "Invalid choice" in stderr) = not in this CLI (skip). # any other non-zero (network/credential error) = inconclusive; treat as unavailable.
If it is not available, skip this step and go to the normal search workflow (Steps 3-7). 2. **User opt-in.** If available, ask the user: "I can check the Glue Data Catalog for customer-authored context using an experimental SearchAssets/GetAsset API. Use it? (yes/no)". Proceed only on an explicit yes; otherwise skip to Steps 3-7.
**How this model differs:** Discovery indexes **assets** (not databases/tables). Every asset has an `Id` that is an **ARN**, and every lookup after `SearchAssets` keys off that ARN via the identifier — there is no `--database-name`/`--table-name`. CLI flags are kebab-case (`--search-text`, `--max-results`, `--filter-clause`); top-level response fields are PascalCase (`Id`, `AssetName`, `Forms`). NOTE: a `*.Content` value is itself a JSON STRING with its own camelCase schema (e.g. `dataLocation`, `dataFormat`, `isPartitionKey`) — parse it as embedded JSON, do not expect PascalCase inside. The operations you need:
| Operation | Input → Output | |---|---| | `search-assets` | `--search-text` (+ optional `--filter-clause`) → `Items[]` of `{Id, AssetName, Type, Namespace, AssetTypeId, UpdatedAt}` (NOTE: search items do NOT include a description — call `get-asset` for `Description`/`Forms`) | | `get-asset` | `--identifier <Id, an ARN>` → one asset's `{Description, Forms, IterableForms}`. `Forms."amazon::Table".Content` is JSON `{dataLocation, dataFormat, type}`; advertises column availability via `IterableForms: {"columns": {...}}` | | `list-iterable-forms` | `--asset-identifier <table ARN> --iterable-form-name columns` → that table's columns `Items[]` of `{ItemId, ItemName, Description}` (ItemId = `<table-ARN>#<columnName>`) | | `batch-get-iterable-forms` | `--asset-identifier <table ARN> --iterable-form-name columns --item-identifiers <id1> <id2> ...` (space-separated) → `Items[]` of `{ItemName, Forms}` where `Forms.Column.Content` is JSON `{"type": "...", "isPartitionKey": ...}` |
aws glue search-assets --search-text '<user request terms>' --max-results 5 # Id is a full ARN, e.g. arn:aws:glue:us-west-2:123456789012:table/<db>/<table> aws glue get-asset --identifier "arn:aws:glue:<region>:<account>:table/<db>/<table>"
`search-assets` returns only identity fields (no description), so to judge relevance you MUST `get-asset` the top candidates (up to ~5) and read their `Description` / `Forms` — do NOT pick by rank alone. Only pass ARNs whose `Type` is a Glue table (`amazon.glue::GlueTable`) to `list-iterable-forms`.
**Narrow with `--filter-clause`** when the request names a database or asset type (filterable: `type`, `amazon.glue::GlueTable.databaseName`, `dataFormat`, `createdAt`):
aws glue search-assets --search-text 'sales' --max-results 5 \
--filter-clause '{"AttributeFilter": {"Attribute": "amazon.glue::GlueTable.databaseName", "Operator": "equals", "Value": {"StringValue": "<database-name, e.g. sales>"}}}'**Column name
Help AI coding agents build, deploy, and manage applications on AWS. The Agent Toolkit for AWS gives AI coding agents the tools, knowledge, and guardrails they need to work with AWS services.
Repo: aws/agent-toolkit-for-aws
Trigger a pre-merge release readiness review on a GitHub PR, GitLab MR, or local branch. Use when the user wants to analyze code changes for risk, correctness,…
Have a fast, conversational analysis with the AWS DevOps Agent. Use for cost optimization, architecture review, topology mapping, knowledge / runbook…
Coordinate the AWS DevOps Agent across multiple AgentSpaces from one Claude Code session — route questions to the right space (prod vs staging vs knowledge),…
Run a fast AWS Security Agent diff scan on only the changed code since a git ref. Use when the user asks to scan changes, run a diff scan, check what changed…
Run a deep root-cause investigation on the AWS DevOps Agent. Use when the user describes an incident, alarm, outage, or unexplained behavior — keywords like…
Run an AWS Security Agent penetration test against a live web application — registers and verifies the target domain, exercises the supplied endpoints with the…