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aws-sdk-python-usage

AWS SDK for Python (boto3/botocore) development patterns. You MUST use this skill when writing Python code that uses AWS services via boto3 or botocore. This includes creating service clients or resources, configuring sessions and credentials, handling errors with ClientError, using paginators and waiters, S3 file transfers and presigned URLs, DynamoDB table operations, and any boto3/botocore client configuration. Use this skill whenever Python code imports boto3 or botocore, or when the user asks about AWS operations in Python.

73

Quality

90%

Does it follow best practices?

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Adds up to 20 points to the overall score

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SecuritybySnyk

Passed

No findings from the security scan

SKILL.md
Quality
Evals
Security

Quality

Content

85%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-organized, highly actionable skill body with executable examples and clean one-level-deep progressive disclosure to real reference files. The only notable gap is the absence of explicit validation/feedback-loop checkpoints for destructive or batch AWS operations, which keeps workflow_clarity at 4.

Suggestions

Add an explicit validation/feedback-loop step for destructive or batch operations (e.g. S3 object deletes, DynamoDB writes) — a 'verify before/after' checkpoint — to lift workflow_clarity to 5.

Tighten the Client vs Resource prose by letting the inline code carry the contrast, removing restated lines like 'Understanding which to use and when is essential'.

Convert the bare Common Issues entry into a small 'Wrong/Right' table or fold it into the Error Handling section to avoid a near-empty subsection.

DimensionReasoningScore

Conciseness

The body is lean and largely free of padded concept explanations, though a few phrasings (e.g. 'Understanding which to use and when is essential', the client/resource prose) restate what the code already shows and could be trimmed slightly.

4 / 5

Actionability

Every section gives copy-paste-ready, executable Python covering the common cases (client/resource, sessions, API calls, typed-error handling, paginators, waiters, Config, logging), with concrete import paths and idiomatic patterns.

5 / 5

Workflow Clarity

Sequencing is clear via well-headed sections with do/don't guidance and explicit error-handling flow, but there is no explicit validation checkpoint for risky batch/destructive operations (e.g. S3 deletes, DynamoDB writes) referenced via s3.md/dynamodb.md.

4 / 5

Progressive Disclosure

SKILL.md is a concise overview with well-signaled, one-level-deep references (configuration, credentials, error-handling, pagination, waiters, s3, dynamodb), all verified present in ./references/ and listed in a clean References section.

5 / 5

Total

18

/

20

Passed

Description

96%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 highly specific, well-triggered description that clearly states both capabilities and activation conditions with strong concrete examples. Minor distinctiveness softness comes from the broad 'AWS operations in Python' phrasing, but import-based triggers keep conflict risk low.

DimensionReasoningScore

Specificity

Lists multiple concrete actions (creating clients/resources, configuring sessions/credentials, ClientError handling, paginators, waiters, S3 transfers, DynamoDB ops) with comprehensive coverage of the SDK's surface.

5 / 5

Completeness

Explicitly answers 'what' (the enumerated development patterns) and 'when' with concrete trigger phrases ('You MUST use this skill when...', 'Use this skill whenever Python code imports boto3 or botocore, or when the user asks about AWS operations in Python').

5 / 5

Trigger Term Quality

Covers natural user phrasing ('AWS services via boto3 or botocore', 'AWS operations in Python') plus technical triggers ('imports boto3 or botocore'), spanning the common ways users describe this need.

5 / 5

Distinctiveness Conflict Risk

The boto3/botocore niche and import-based triggers are distinct with minimal conflict risk, but 'AWS operations in Python' is slightly broad and could brush against a generic AWS-CLI skill.

4 / 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.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
aws/agent-toolkit-for-aws
Reviewed

Table of Contents

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