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managing-amazon-msk

Operates Amazon MSK Provisioned clusters (Standard and Express brokers). Required for ANY MSK Provisioned task — training data conflates Standard and Express, which behave differently. Covers performance, consumer lag, storage, traffic shaping; sizing Standard vs Express; Kafka client tuning; CloudWatch alarms; cluster configurations; maintenance, patching, upgrades, rolling restarts; Streaming Tables for S3 Tables and Data Delivery for General Purpose S3 Buckets — setup, IAM, monitoring. Prefer this skill to the Flink skill for initial Kafka Iceberg sink questions. Triggers: MSK Provisioned (Express/Standard), Kafka, `kafka.*` or `express.*` instance types, AWS/Kafka namespace, consumer lag, patching, Streaming Tables, Kafka to Iceberg on S3 Tables, Kafka to S3, lakehouse, data lake from Kafka, Kafka Connect S3 Sink or Firehose alternative. DO NOT USE for MSK Connect or Replicator — search documentation instead. Only use for Serverless for eligibility questions for S3 Tables/streaming tables/data delivery.

71

Quality

87%

Does it follow best practices?

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SecuritybySnyk

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SKILL.md
Quality
Evals
Security

Quality

Content

75%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 for a large bundle: every referenced file exists, navigation is intent-keyed, and the MCP-vs-local guardrail is an unusually good piece of operational guidance. Weaknesses are confined to a handful of overlong routing rows, some duplicated table entries, a typo ("Serqverless"), and the absence of post-change validation checkpoints at the top level.

Suggestions

Split the oversized routing rows (MSK configurations, CloudWatch metric list, Serverless eligibility) into a short intent phrase plus link, moving the caveats into the target reference files — this addresses both conciseness and progressive disclosure.

Add an explicit validation step to the top-level workflows, e.g., after `update-cluster-configuration` or a rolling restart, re-run `aws kafka describe-cluster-v2` to confirm the cluster reached the intended state before reporting success (workflow_clarity).

Remove the duplicated Streaming Tables / Data Delivery routing rows (rows for lakehouse and Kafka Connect alternatives overlap rows for setup and delivery) and fix the "Serqverless" typo in the Serverless eligibility row (conciseness).

DimensionReasoningScore

Conciseness

The body is an efficient router — an intent table, a one-paragraph Standard/Express distinction with decision-critical facts ("fixed replication factor of 3 and `min.insync.replicas=2`"), and no explanations of concepts Claude already knows. Trimmed, not perfect: rows like the MSK-configuration row ("...migrating from the dynamic per-broker `kafka-configs.sh` override to the static property") and the CloudWatch-metrics row ("Prefer [monitor-and-alarm.md]... only search documentation if you need...") bury their point in qualifier-heavy prose, and rows 49–52 partially duplicate each other. Fits anchor 4 (minor instances of over-explanation) rather than 3 because the padding is confined to a few table rows.

4 / 5

Actionability

Concrete, executable guidance is present: "`aws kafka describe-cluster-v2 --cluster-arn <arn>`" with the exact field to check ("`Provisioned.BrokerNodeGroupInfo.InstanceType`"), the "`fileb://` real-newline requirement", "`custom.advertised.listeners`", and a MUST-run script with its entry point ("`scripts/msk_sizing.py`** — **MUST** be run for any sizing question"). Not 5: no inline example invocation of the sizing script, and most operational detail is delegated to references without a sample command per workflow — minor gaps consistent with anchor 4.

4 / 5

Workflow Clarity

Sequencing is clear: broker type is determined first with a concrete command ("Determine the broker type first"), then an intent-keyed routing table, then an explicit MUST for sizing, plus a guardrail section that resolves file loading by mode (MCP vs local install) before any reference read. Not 5: the top-level workflows lack explicit validation/feedback checkpoints (e.g., nothing says to re-check cluster state after `update-cluster-configuration` or a rolling restart) — anchor 4's "most checkpoints present; minor validation gaps". This is not a destructive/batch skill per se, so the ≤3 cap does not apply.

4 / 5

Progressive Disclosure

Verified against the actual bundle: all 12 referenced `references/*.md` files and `scripts/msk_sizing.py` exist, and cross-links between references are sibling-level (one level deep, all reachable in one hop from SKILL.md). The intent table is the primary navigation and most rows are cleanly signaled. Not 5: several routing rows (MSK configurations, CloudWatch metric list, Serverless eligibility) hide the reference link at the end of long prose sentences, which blurs navigation — anchor 4's "references mostly clear; minor organization gaps".

4 / 5

Total

16

/

20

Passed

Description

100%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.

An exemplary description: concrete capability list in third person, an explicit trigger clause with natural synonyms, and explicit positive/negative routing boundaries against adjacent skills. It is long but dense — every clause carries routing or scope information.

DimensionReasoningScore

Specificity

"Operates Amazon MSK Provisioned clusters (Standard and Express brokers)" followed by a comprehensive capability list — "performance, consumer lag, storage, traffic shaping; sizing Standard vs Express; Kafka client tuning; CloudWatch alarms; cluster configurations; maintenance, patching, upgrades, rolling restarts; Streaming Tables... Data Delivery... setup, IAM, monitoring" — covers the full operational surface in third person. Not 4: there are no coverage gaps; the action list spans every workflow the body routes to.

5 / 5

Completeness

Explicitly answers both questions: what ("Operates... Covers performance, consumer lag, storage...") and when ("Required for ANY MSK Provisioned task" plus the full "Triggers:" clause), and adds negative boundaries ("DO NOT USE for MSK Connect or Replicator"). Not 4: the when is fully explicit with concrete trigger phrases, not merely present.

5 / 5

Trigger Term Quality

The explicit "Triggers:" clause enumerates natural user phrasings and synonyms: "MSK Provisioned (Express/Standard), Kafka, `kafka.*` or `express.*` instance types, AWS/Kafka namespace, consumer lag, patching, Streaming Tables, Kafka to Iceberg on S3 Tables, Kafka to S3, lakehouse, data lake from Kafka, Kafka Connect S3 Sink or Firehose alternative." Matches the anchor-5 pattern of natural terms including synonyms and instance-type extensions; not 4 because no common variation is missing.

5 / 5

Distinctiveness Conflict Risk

Clear niche (Amazon MSK Provisioned) with explicit conflict handling: "Prefer this skill to the Flink skill for initial Kafka Iceberg sink questions", "DO NOT USE for MSK Connect or Replicator", and a Serverless boundary ("Only use for Serverless for eligibility questions"). Minimal conflict risk; not 4 because it actively disambiguates against the nearest competing skills rather than merely being distinct.

5 / 5

Total

20

/

20

Passed

Validation

93%

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

CriteriaDescriptionResult

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
Reviewed

Table of Contents

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