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testland/sqs-tests

Use whenever code that sends or receives AWS SQS messages needs tests: Standard vs FIFO semantics, visibility timeouts, dead-letter queues for poison messages and retention, using LocalStack, aws-sdk-client-mock for TypeScript or moto for Python.

Quality

92%

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Overview
Quality
Evals
Security
Files

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, highly actionable testing skill: executable examples in both languages, a clear decision procedure for mock vs LocalStack vs real SQS, and a genuine one-level-deep reference bundle that keeps the main file lean. The remaining polish is minor: trim a few explanations of concepts Claude already knows and add a brief recovery path for LocalStack/real-SQS divergence.

DimensionReasoningScore

Conciseness

The body is code- and table-driven with little padding, but a few trims are available: the sentence explaining how moto's '@mock_aws' intercepts boto3, the textbook definition of visibility timeout in Step 5, and Step 8's retention section which itself concedes 'Tests rarely verify retention directly.'

4 / 5

Actionability

Fully executable, copy-paste-ready examples cover the common cases: TypeScript and Python mock tests, a docker-compose LocalStack setup with client wiring, a working visibility-timeout test sequence, and a CI service config; DLQ and FIFO recipes are complete in the referenced file.

5 / 5

Workflow Clarity

Steps 1-9 are clearly sequenced with an explicit decision rule in Step 1 ('For pure logic tests... use mocks. For semantic tests... use LocalStack. For pre-prod smoke, use real SQS') and an anti-patterns table, but there are no explicit error-recovery feedback loops (e.g., what to do when LocalStack diverges from real SQS beyond the Limitations note), so it falls short of the anchor-5 validation-and-recovery pattern.

4 / 5

Progressive Disclosure

The split is appropriate and verified: mock tests and the visibility recipe stay inline while DLQ-routing and FIFO recipes are offloaded to references/localstack-recipes.md, which exists, is one level deep, and is clearly signaled from Steps 6 and 7 with markdown links; no nested references.

5 / 5

Total

18

/

20

Passed

Description

95%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 description: it states a precise trigger condition, enumerates the concrete SQS behaviors it tests, and names the exact tooling per language. The only shortcoming is slight under-coverage of test concerns the body handles (long-polling, CI), which keeps specificity just below comprehensive.

DimensionReasoningScore

Specificity

The description enumerates concrete test targets — 'Standard vs FIFO semantics, visibility timeouts, dead-letter queues for poison messages and retention' — plus named tooling (LocalStack, aws-sdk-client-mock, moto), but has minor coverage gaps: long-polling and CI integration are test concerns covered in the body yet absent here.

4 / 5

Completeness

Explicitly answers both questions: 'when' via 'Use whenever code that sends or receives AWS SQS messages needs tests' and 'what' via the enumerated behaviors and tools. Not a 4 because the 'when' clause is concrete and phrased as a direct trigger, matching the anchor-5 example structure.

5 / 5

Trigger Term Quality

Natural terms a user would actually say are comprehensively present: 'SQS', 'FIFO', 'visibility timeouts', 'dead-letter queues', 'poison messages', 'LocalStack', 'moto', 'aws-sdk-client-mock', covering both Python and TypeScript ecosystems.

5 / 5

Distinctiveness Conflict Risk

Tightly scoped to AWS SQS message testing with SQS-specific triggers (FIFO, visibility timeout, DLQ, LocalStack); it would not fire for generic testing, document, or non-SQS queue skills, keeping conflict risk minimal.

5 / 5

Total

19

/

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.

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