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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.

72

Quality

88%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

SKILL.md
Quality
Evals
Security

Quality

Content

87%

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

A well-structured, actionable, token-efficient reference with excellent progressive disclosure. The weakest dimension is workflow clarity, since it is a patterns guide rather than a sequenced multi-step process with validation checkpoints.

Suggestions

For the Script Structure section, add an explicit validate-then-proceed checkpoint (e.g., verify the bucket/args exist before do_the_work) to model a feedback loop and lift workflow clarity toward 3.

Add a short ordered workflow for the most common end-to-end task (e.g., create client -> handle ClientError -> paginate results) so the patterns cohere into a sequenced process rather than standalone sections.

When the skill mandates loading references/s3.md or references/dynamodb.md, state the trigger condition as a concrete step in a short checklist so the load-when-needed flow is unambiguous.

DimensionReasoningScore

Conciseness

The body is lean and assumes Claude's competence; nearly every token earns its place, and the client/resource distinction plus the list of services that expose resources is genuinely non-obvious domain knowledge rather than padding.

3 / 3

Actionability

It provides fully executable, copy-paste-ready code throughout (clients/resources, sessions, paginators, waiters, Config, error handling) with specific API names and parameter casing.

3 / 3

Workflow Clarity

The Script Structure section gives a clear sequence (arg parsing and exit codes in main(), no sys.exit in business logic) but there are no explicit validation checkpoints or feedback loops, which is the differentiator from a level-3 workflow.

2 / 3

Progressive Disclosure

SKILL.md is an overview that signals one-level-deep references to real files (references/error-handling.md, pagination.md, waiters.md, configuration.md, s3.md, dynamodb.md, credentials.md), both inline and in a dedicated References section.

3 / 3

Total

11

/

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.

A strong, specific description with explicit trigger guidance and good natural-term coverage. Its only issue is second-person voice ('You MUST use this skill'), which violates the third-person guideline and caps specificity.

DimensionReasoningScore

Specificity

The description lists many concrete actions ('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'), which would normally rate a 3, but it uses second-person voice ('You MUST use this skill'), which the guidelines penalize by reducing specificity by 1.

2 / 3

Completeness

It explicitly answers both what ('AWS SDK for Python (boto3/botocore) development patterns... This includes...') and when ('You MUST use this skill when... Use this skill whenever Python code imports boto3 or botocore').

3 / 3

Trigger Term Quality

It surfaces natural terms a user would actually say — 'boto3', 'botocore', 'AWS services', 'S3', 'DynamoDB', 'AWS operations in Python' — with good coverage of common variations.

3 / 3

Distinctiveness Conflict Risk

It carves a clear niche (boto3/botocore AWS Python SDK) with distinct import- and service-based triggers, making conflict with other skills unlikely.

3 / 3

Total

11

/

12

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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