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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. Covers performance, consumer lag, storage, traffic shaping; sizing Standard vs Express; Kafka client tuning; CloudWatch alarms; cluster configs; maintenance, patching, rolling restarts; topic management; MSK Replicator setup for DR and active-active/active-passive replication (same-/cross-account), including throughput and partition sizing; Streaming Tables for S3 Tables and Data Delivery for General Purpose S3 — setup, IAM, monitoring. Prefer Flink for Kafka Iceberg sink questions. Migrations: use migrate-to-msk. Triggers: MSK Provisioned, Kafka, `kafka.*`/`express.*` types, AWS/Kafka namespace, cross-cluster replication, 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 — search docs instead. Serverless: only S3 Tables/data delivery eligibility.

Quality

91%

Does it follow best practices?

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SecuritybySnyk

Passed

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SKILL.md
Quality
Evals
Security

Quality

Content

78%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.md: an accurate Express-vs-Standard overview with verifiable product facts, a concrete broker-type detection step, and an intent-to-reference table where every referenced bundle file exists. Weaknesses are minor: the MCP/local-install guardrail section is verbose, and inline executable examples are sparse because detail is delegated to references.

Suggestions

Tighten the Guardrail section (~20 lines) into a short two-case bullet list; most of the MUST/Do-NOT repetition adds tokens without adding information.

Add one or two copy-paste-ready inline command examples for the most common operations (e.g., a sample msk_sizing.py invocation or a describe-cluster-v2 output snippet) so the top-level file is actionable without a reference hop.

Fix the typo "Serqverless" in the Serverless eligibility routing row and split the routing table so strategic references and external doc links are visually distinct.

DimensionReasoningScore

Conciseness

The body is mostly lean routing content with no explanation of concepts Claude already knows (no Kafka/MSK primer), and the Express-broker facts (3x ingress, 20x faster scaling, 180x faster rebalancing, RF=3/min.insync.replicas=2) are product-specific data that earns its tokens. It falls short of level 5 because the ~20-line MCP-vs-local "Guardrail" section is wordy with repetitive MUST/Do-NOT emphasis, and the Overview partially restates the frontmatter description.

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`), a runnable script with its credential/fallback behavior described, and per-intent routing into detailed references. It stops short of level 5 because the body itself contains few copy-paste-ready command examples — the executable detail largely lives one level down in the reference files — leaving minor gaps in the inline guidance.

4 / 5

Workflow Clarity

The sequence is clear and well-ordered: determine broker type first (with a concrete command), then route via the intent table, with a Common Workflows section repeating the key entry points. This matches level 4 (clear sequence, minor gaps) rather than level 5, since the body has no explicit validation/recovery checkpoints of its own — those are delegated to the reference files — and the routing table mixes strategic routing with doc-link rows.

4 / 5

Progressive Disclosure

The body is a lean overview that routes to 14 one-level-deep reference files and one script, all of which exist in the bundle (verified: every referenced `references/*.md` path and `scripts/msk_sizing.py` is present). Each table row signals intent clearly and points to a named section where relevant, matching the level-5 anchor of a clear overview with well-signaled, one-level-deep, easy-to-navigate references.

5 / 5

Total

17

/

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: third-person, specific, and comprehensive in scope, with an explicit trigger list, clear routing of edge cases to adjacent skills (MSK Connect, Serverless, Flink, migrate-to-msk), and explicit negative boundaries. All four dimensions sit at the top anchors with no fluff or over-claims.

DimensionReasoningScore

Specificity

The description enumerates many concrete, specific capabilities — "performance, consumer lag, storage, traffic shaping; sizing Standard vs Express; Kafka client tuning; CloudWatch alarms; cluster configs; maintenance, patching, rolling restarts; topic management; MSK Replicator setup... Streaming Tables... setup, IAM, monitoring" — giving comprehensive, non-generic coverage of the MSK operations domain. It fits the anchor "Lists multiple specific concrete actions; comprehensive coverage" rather than the level-4 anchor, which requires minor gaps in coverage; no significant MSK Provisioned operational area is missing.

5 / 5

Completeness

It explicitly answers both questions: the "what" is "Operates Amazon MSK Provisioned clusters (Standard and Express brokers)" with an enumerated scope, and the "when" is explicit via "Required for ANY MSK Provisioned task" plus a dedicated concrete Triggers list. This is the level-5 pattern (clear what AND when with concrete trigger phrases), not level 4, since the when-clause is fully explicit rather than merely present.

5 / 5

Trigger Term Quality

The "Triggers:" clause covers natural user phrasings and their synonyms: "MSK Provisioned, Kafka, `kafka.*`/`express.*` types, AWS/Kafka namespace, cross-cluster replication, Kafka to Iceberg on S3 Tables, Kafka to S3, lakehouse, data lake from Kafka, Kafka Connect S3 Sink or Firehose alternative". This matches the level-5 anchor (comprehensive natural terms including synonyms and type patterns); the level-4 anchor would require noticeable missing natural terms, and none are apparent.

5 / 5

Distinctiveness Conflict Risk

It carves out a clear niche with explicit boundary disambiguation: "DO NOT USE for MSK Connect — search docs instead", "Serverless: only S3 Tables/data delivery eligibility", "Migrations: use migrate-to-msk", and "Prefer Flink for Kafka Iceberg sink questions". These explicit exclusions reduce conflict risk with adjacent skills to a minimum, matching the level-5 anchor of a clear niche with distinct triggers.

5 / 5

Total

20

/

20

Passed

Validation

100%

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

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

aws/agent-toolkit-for-aws

Path

skills/specialized-skills/analytics-skills/managing-amazon-msk/SKILL.md

Reviewed

Table of Contents

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