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AkM-2018
by AkM-2018

GetAwsSolutionsConstructPattern

Search and discover vetted AWS architecture patterns that combine multiple services to implement common use cases with built-in AWS Well-Architected best practices.

Instructions

Search and discover AWS Solutions Constructs patterns.

AWS Solutions Constructs are vetted architecture patterns that combine multiple
AWS services to solve common use cases following AWS Well-Architected best practices.

Key benefits:
- Accelerated Development: Implement common patterns without boilerplate code
- Best Practices Built-in: Security, reliability, and performance best practices
- Reduced Complexity: Simplified interfaces for multi-service architectures
- Well-Architected: Patterns follow AWS Well-Architected Framework principles

When to use Solutions Constructs:
- Implementing common architecture patterns (e.g., API + Lambda + DynamoDB)
- You want secure defaults and best practices applied automatically
- You need to quickly prototype or build production-ready infrastructure

This tool provides metadata about patterns. For complete documentation,
use the resource URI returned in the 'documentation_uri' field.

Args:
    ctx: MCP context
    pattern_name: Optional name of the specific pattern (e.g., 'aws-lambda-dynamodb')
    services: Optional list of AWS services to search for patterns that use them
             (e.g., ['lambda', 'dynamodb'])

Returns:
    Dictionary with pattern metadata including description, services, and documentation URI

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pattern_nameNo
servicesNo
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes what the tool does (provides metadata about patterns), mentions key benefits of Solutions Constructs, and explains the return format. However, it doesn't specify whether this is a read-only operation, if there are rate limits, or authentication requirements.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with clear sections (overview, benefits, usage guidance, parameters, returns) and every sentence adds value. It's appropriately sized for a tool with 2 parameters and no annotations, with no redundant or unnecessary information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (2 optional parameters, no output schema, no annotations), the description is quite complete. It explains purpose, usage, parameters, and return format. The only minor gap is the lack of explicit behavioral details like read-only status or error conditions, but overall it provides sufficient context for effective use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 0%, so the description must fully compensate. It provides an 'Args' section that clearly explains both parameters with concrete examples: 'pattern_name' as an optional specific pattern identifier and 'services' as an optional list to search for patterns using those services. This adds substantial value beyond the bare schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose as 'Search and discover AWS Solutions Constructs patterns' and provides specific context about what Solutions Constructs are. It distinguishes this tool from siblings by focusing on pattern metadata retrieval rather than guidance, rule explanation, or other CDK-related functions.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description includes a dedicated 'When to use Solutions Constructs' section with three explicit scenarios, providing clear context for when this tool is appropriate. It also mentions that for complete documentation, users should use the returned 'documentation_uri' field, giving practical guidance on next steps.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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