Managing Data Asset Access

Manage Data Asset Access

Access to a catalog data asset is a subscription over a published listing. Request it, decide on it, share it, audit it, remove it. And prove each of those actually took effect.

Overview

You SHOULD execute commands through AWS MCP server tools when connected: they give validation, sandboxed execution and audit logging, which matter more than usual in a skill whose failures are security misstatements. Fall back to the AWS CLI when the MCP server is unavailable; every step here is expressed as CLI calls, so it runs either way. You MUST explain each grant or revoke before executing it, and you MUST report what you verified afterwards.

Runtime requirements, stated before the first command block:

• The AWS CLI v2 and credentials for the target account and region.

• A POSIX shell for the multi-step wait blocks in the references. Nothing here needs jq; every block reads fields with --query.

Check both before running a block, and say so if either is missing rather than improvising around it.

Guardrail: where this skill's own files live (MCP vs local install)

This skill can be loaded two ways, and they resolve the skill's own bundled files from different places. Determine how the skill was loaded before reading a reference:

• Loaded through a skill tool over MCP: the skill is not installed on the local filesystem, so file_read on these paths will fail. Fetch each reference with whatever skill-file tool your runtime exposes, passing the reference path in that tool's own file parameter (e.g. references/auditing-and-revoking.md). Tool names differ between runtimes, so use the one you actually have rather than one you expect to be there. If the only skill tool available takes a skill name and has no file parameter, it cannot fetch a reference at all: do not put a path in its name field, and read the file from the skill's own directory instead.

• Installed locally (e.g. .kiro/skills/managing-data-asset-access/ or ~/.claude/skills/managing-data-asset-access/): Read files from the local skill directory using relative paths.

This distinction applies only to the skill's own packaged files. User data and session artifacts are always read from and written to the user's working directory. Never fetch or write customer data through a skill tool.

references/ is a sibling of this SKILL.md, so resolve reference paths against that directory rather than your working directory. If a skill tool returns this overview instead of the file you asked for, it did not fetch it. Read it from that directory, and do not write API calls from memory because a reference read failed.

Three rules that outrank every chapter

Read these before any chapter. Each one caused failures across several different operations, so no single chapter is where you would meet it in time.

1. The grant is the access. The request is only the decision

Two objects, two stages, and only the second one is access:

So:

• You MUST NOT report access as live, or as removed, from a request's or a subscription's status. Read the grant.

• COMPLETED is the grant's terminal status, and GRANTED is not a value the grant's own status ever takes: it lives one level down, per asset. Polling items[].status for GRANTED waits for a state that never arrives.

• RevokeSubscription returns REVOKED immediately while the grant is still being torn down in the background. The revoke's own response proves nothing.

• A grant that has vanished counts as settled. A grant still present must read COMPLETED, and on a teardown its assets must read REVOKED, because a grant that finished granting also reads COMPLETED.

• The grant's own PENDING and IN_PROGRESS are the same two statuses in both directions, so they do not tell you whether access is arriving or leaving. The per-asset status does, and so does the subscription's own status.

Telling a user access is gone when it is not is a security misstatement, not a cosmetic one. references/auditing-and-revoking.md is the procedure.

2. This vocabulary is the SageMaker Catalog's. Establish that by probe

"Listing", "subscription", "consumer project" and "grant" are also AWS Marketplace, AWS Data Exchange, AWS RAM and non-AWS data-exchange words. Reading the request as one of those, and then reporting a missing permission for that other service, is the single most common way to answer this task wrongly.

aws sts get-caller-identity                    # who am I
aws datazone list-domains --region <region>    # is this a SageMaker Catalog account?

• If list-domains returns a domain, the request is about that domain. Work there, and do not ask the user which product they meant.

• An AccessDenied is this caller cannot see it, not it is not there. Say what you probed and what it answered.

• Substitute a real region. A denial on a call that named no region is not an answer about the domain; references/access-model-detection.md says why and what to do instead.

• You MUST NOT name a permission as the blocker unless the call you were denied is the call this task needs. A Marketplace or Data Exchange permission is never the blocker for a catalog subscription.

• If the account genuinely has no domain, there is no subscription workflow here. Say so and read references/access-model-detection.md for what to offer instead. Do not substitute an IAM, S3 or Lake Formation grant and describe it in the user's words.

3. Every access decision is recorded, or it did not happen properly

The worst failure in this skill is over-granting production data. The measured version of that is not a wild grant. It is a grant nobody can account for.

• An approval or a rejection MUST carry a decision comment (--decision-comment). An empty one leaves an audit trail that records access was granted and nothing about why or by whom.

• A request MUST carry a real justification (--request-reason). The API requires the field and accepts whitespace, so it guarantees presence and guarantees nothing about content.

• A direct share creates access with no consumer-side request at any point, so the reason you write is the only audit record that will ever exist. Say that when you report it.

• You MUST NOT decide on someone else's request without being told the decision. Surface the queue, then execute the decision the user states.

Before anything else

aws sts get-caller-identity
aws datazone list-domains --region <region> --query 'items[].{id:id,name:name}'

Then resolve which project you are acting as, which is discoverable from your own identity in three calls and is not something to ask the user for. references/access-model-detection.md has the chain. Never skip it, and never skip it because the user named a listing: which project holds the subscription is not implied by the listing's name.

Router

Match on meaning. Read the detection chapter first, then exactly the chapters the task needs.

Retiring an asset is not this skill. The ordered teardown that a delete requires (revoke, wait for settlement, unpublish, delete listing, delete asset) belongs to managing-data-catalog, which carries it inline. If the user's goal is to remove a dataset rather than to remove somebody's access, say so and point there. What this skill owns is the revoke as a decision; the revoke as a mechanical step inside a delete is that skill's.

Bulk work: one collective wait, never one per subscription

Removing access for several consumers at once is the common real request, and it is where the cost is. Every revocation first, then one wait covering all of them, polled in short calls that return a verdict. A plan naming every subscription and who loses access, an explicit yes before the first revocation, and a per subscription outcome afterwards. references/bulk-revocation.md has the rules and the two ways the wait goes wrong.

The request is the authorisation. Confirm what was NOT asked

Stopping to ask permission to do the thing you were just asked to do is not caution, it is a failure, and it is the second most common one in this domain. There is one exception, and it comes first:

So a user who says "revoke the analytics team's access to this listing" has already decided: one subscription, so do it, then name it and confirm settlement. A user who says "revoke their access to these three listings" gets the plan first, and the revocations after their yes. A user who names the three subscription ids and the project has written the plan themselves: check it is still the real set, and go. A user who says "show me the pending requests" has not authorised you to approve any of them.

Security considerations

The blast radius of this skill is who can read production data, so the risks are concrete. references/access-safety.md is the full treatment.

AWS guidance behind these controls: Security in Amazon DataZone, encrypting CloudTrail log files with AWS KMS keys, and validating CloudTrail log file integrity.

The credentials this skill uses are whatever the caller already has. It recommends no IAM change, and if an operation is denied it reports the denial rather than proposing a wider policy.

Out of scope

Row and column-level asset filters are a real access-control mechanism and are not covered here. A filter refines a grant that already exists, and there is no request or approval state machine for one, so nothing in this skill implies otherwise, and adding them later is an extension rather than a contradiction.

If the asset the user means is not governed by a catalog listing (a raw S3 prefix, a Glue table in an account with no domain, a Lake Formation-governed table outside the catalog), this skill does not apply. Say which probe told you that, and do not improvise a subscription over something that has no listing.

Writing catalog metadata, glossaries, forms, publishing a listing, curating a data product and deleting an asset all belong to managing-data-catalog.