aws-cleanrooms

Troubleshoots and debugs AWS Clean Rooms collaboration issues related to IAM roles, S3 bucket policies, KMS keys, Lake Formation permissions, and CloudWatch logging for custom ML model training and inference jobs. Use when a customer reports permission failures, access errors, or log publishing issues in Clean Rooms.

Quality

86%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide

Securityby

Passed

No findings from the security scan

Quality

Content

86%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A well-structured router skill: concise overview, clear decision-tree triage pointing to real one-level-deep procedure files, and a tidy external-resources list. The body delegates executable diagnostics and validation loops to the referenced procedures, which keeps actionability and workflow_clarity at 4 rather than 5.

Dimension	Reasoning	Score
Conciseness	Lean overview with no padding or explanation of concepts Claude already knows; the 'Covers ...' lines serve routing decisions rather than restating knowledge, and every line earns its place.	5 / 5
Actionability	Provides a concrete failure-type decision tree with named procedure links, but the executable diagnostic commands themselves live in the referenced files rather than inline in the body.	4 / 5
Workflow Clarity	The triage sequence (determine failure type, then branch to a procedure) is clear and unambiguous, but validation/checkpoint loops are delegated to the reference procedures rather than surfaced in the body.	4 / 5
Progressive Disclosure	Clear overview with two well-signaled one-level-deep references (references/permission-debugging.md and references/custom-model-logging-debugging.md) that both exist as real files, plus a separate external-resources section; content is appropriately split and easy to navigate.	5 / 5
	Total	18 / 20 Passed

Description

87%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong, third-person description that clearly states what it does and when to use it with concrete, natural trigger terms and a well-scoped niche. Its only mild weakness is relying on two verbs ('troubleshoots/debugs') rather than a richer action list, which keeps specificity and trigger_term_quality at 4 rather than 5.

Dimension	Reasoning	Score
Specificity	Names the domain and concrete scope (IAM roles, S3 bucket policies, KMS keys, Lake Formation permissions, CloudWatch logging, ML training/inference) with two concrete verbs ('Troubleshoots and debugs'), but the action vocabulary is limited to those two verbs rather than a broad set of distinct actions.	4 / 5
Completeness	Explicitly answers both 'what' (troubleshoots/debugs Clean Rooms issues across named permission and logging surfaces) and 'when' ('Use when a customer reports permission failures, access errors, or log publishing issues'), with concrete trigger phrases.	5 / 5
Trigger Term Quality	Natural user-reported phrases ('permission failures, access errors, or log publishing issues') align with what a customer would actually say, but coverage stops short of comprehensive synonyms or file/extension-style variations.	4 / 5
Distinctiveness Conflict Risk	A narrow AWS Clean Rooms niche with custom ML model specifics and named AWS services gives it distinct triggers and minimal overlap risk with other skills.	5 / 5
	Total	18 / 20 Passed

Validation

93%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 15 / 16 Passed

Validation for skill structure

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	15 / 16 Passed

Repository: aws/agent-toolkit-for-aws
Path: skills/specialized-skills/analytics-skills/aws-cleanrooms/SKILL.md
Commit: 8ea26bd

Reviewed: 5 days ago

Table of Contents

Discovery Implementation Validation

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.