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aws-messaging-and-streaming

Guides use of AWS messaging and streaming services. Covers Amazon SQS, Amazon SNS, Amazon EventBridge, Amazon MQ, Amazon Kinesis Data Streams, Amazon Data Firehose, Amazon Managed Service for Apache Flink, and Amazon Managed Streaming for Apache Kafka (MSK). Use when implementing messaging and streaming patterns.

64

Quality

77%

Does it follow best practices?

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SecuritybySnyk

Passed

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tessl review fix ./plugins/aws-core/skills/aws-messaging-and-streaming/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

65%

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

The body's core value — dense, concrete AWS integration gotchas and service-selection tables — is excellent and actionable. It loses points for a lengthy messaging/streaming concept primer Claude already knows, the absence of any actual reference files despite mentioning them, and the lack of a sequenced operational workflow.

Suggestions

Trim or remove the 'What Is Messaging?' / 'What Is Streaming?' / 'Key Differences' / use-case primers (lines 26-74); Claude already knows these concepts — keep only the AWS-specific service tables and gotchas that earn their tokens.

Either create the referenced bundle files and link them by name (e.g., 'See [SQS.md](references/SQS.md)') or drop the generic 'see reference files' line (line 23); a dangling reference to nonexistent files fails progressive disclosure.

Move the detailed 'Common Integration Gotchas' into a one-level-deep reference file (e.g., references/gotchas.md) so SKILL.md stays a concise overview with clearly signaled navigation.

DimensionReasoningScore

Conciseness

The 'Common Integration Gotchas' and service tables are lean and high-signal, but roughly the messaging/streaming primer ('Messaging enables decoupled, asynchronous communication...', 'What Is Streaming?') explains concepts Claude already knows, fitting 'mostly efficient but includes some unnecessary explanation'.

2 / 3

Actionability

The gotchas give concrete, specific API surface ("ReceiveMessageWaitTimeSeconds=20", "AttributeNames=[...]", "PutTargets" with "DeadLetterConfig.Arn=<DLQ>", "BatchAssociateScramSecret", exact IAM conditions); as an instruction-only skill with highly actionable guidance, absence of fenced code is not penalized.

3 / 3

Workflow Clarity

The content is well-organized with a verify-from-docs principle ("verify specific numbers... When uncertain, search skills or docs rather than guessing"), but there is no sequenced multi-step workflow with explicit validation checkpoints, so it sits at 'sequence/organization present but checkpoints missing or implicit'.

2 / 3

Progressive Disclosure

Everything is inline in a single ~100-line SKILL.md (the detailed gotchas and concept primer could be split out), and the only reference signal is a generic, dangling "see reference files" (line 23) with no actual bundle files present, matching 'content that should be separate is inline' and 'references present but not clearly signaled'.

2 / 3

Total

9

/

12

Passed

Description

90%

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

The description is strong: it names a clear, specific AWS niche across eight services and includes an explicit 'Use when...' trigger clause answering both what and when. Its only weakness is that the verbs ('Guides use', 'Covers') describe purpose rather than listing concrete actions.

DimensionReasoningScore

Specificity

It names the domain concretely ("Amazon SQS, Amazon SNS, Amazon EventBridge, Amazon MQ, Amazon Kinesis Data Streams...") but the verbs are vague ("Guides use of...", "Covers...") rather than multiple specific concrete actions, matching the 'names domain and some actions, but not comprehensive' anchor.

2 / 3

Completeness

It answers both 'what' ("Guides use of AWS messaging and streaming services. Covers...") and 'when' with an explicit "Use when implementing messaging and streaming patterns." clause, which is not the missing-trigger case that caps completeness at 2.

3 / 3

Trigger Term Quality

It includes the specific service names and acronyms users naturally say ("SQS", "SNS", "EventBridge", "Kinesis Data Streams", "Kafka (MSK)") plus "messaging and streaming patterns", giving good coverage of natural trigger terms.

3 / 3

Distinctiveness Conflict Risk

It carves a clear AWS messaging/streaming niche with distinct service-name triggers, making it unlikely to fire for unrelated skills; it is a 3 rather than a 2 because the named services and pattern focus are specific rather than generic.

3 / 3

Total

11

/

12

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.

Validation15 / 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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