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aipatterns-mcp-server

by uchit

get_pattern

Retrieve complete details of a specific AI pattern, including implementation guidance and regulatory context, by providing its slug.

Instructions

Retrieve full detail of a specific AI pattern from aipatterns.com.au, including implementation guidance and regulatory context. Use the slug returned by search_patterns.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesPattern slug, e.g. "agentic-ai/agent-checkpoint-and-recovery"
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It mentions the tool retrieves details including 'implementation guidance and regulatory context', but does not discuss side effects, permissions, rate limits, or the exact structure of the response. For a simple read operation, this is adequate but lacks depth.

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?

Two concise sentences: the first conveys purpose and content, the second provides a critical usage hint. No redundant words, and all information is front-loaded.

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?

Despite no output schema, the description hints at the response contents (implementation guidance, regulatory context). For a simple retrieval tool with one parameter, this is sufficient but could be improved by listing expected fields or noting any pagination.

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

Parameters4/5

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

Schema description coverage is 100% for the single parameter 'slug'. The description adds value by specifying 'Use the slug returned by search_patterns', which clarifies the source of the parameter and connects to a sibling tool, exceeding the baseline of 3.

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 a specific verb ('Retrieve') and resource ('full detail of a specific AI pattern'), and distinguishes from siblings by mentioning 'implementation guidance and regulatory context'. It also references the sibling tool 'search_patterns' for obtaining the slug, reinforcing the unique purpose.

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

Usage Guidelines4/5

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

The description explicitly instructs to use the slug from 'search_patterns', indicating when to invoke this tool (after searching). It implies that this is for retrieving details, not for listing or searching. However, it does not explicitly state when not to use it or name alternatives beyond the context.

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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