Skip to main content
Glama
mateusdcc

Pattern Intelligence MCP

by mateusdcc

Write a pattern ADR

write_pattern_adr
Read-onlyIdempotent

Transform a design case into a proposed architecture decision record, capturing options, uncertainty, validation metrics, open questions, and reversal triggers.

Instructions

Generate a proposed architecture decision record from a case. It records considered options, uncertainty, validation metrics, open questions, and reversal triggers rather than pretending the decision is final.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
caseYes
titleYes
Behavior4/5

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

Annotations already establish read-only, idempotent, non-destructive behavior. The description adds meaningful context by clarifying the output is a proposed, non-final ADR and by listing the kind of content it records, which shapes agent expectations beyond the annotations.

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?

A single front-loaded sentence with no filler; every clause contributes either the action, the input source, or the output character.

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

Completeness3/5

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

The main purpose and output contents are covered, and no output schema exists to document the return shape. However, the description does not clarify the ADR's format/representation or how the large nested `case` object maps into the generated record, leaving some practical gaps for a complex input schema.

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

Parameters2/5

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

Schema description coverage is 0%, and the description only indirectly refers to `case` with 'from a case'; `title` receives no semantic explanation. The description does not compensate for the absence of schema descriptions on the two required parameters.

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

Purpose4/5

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

The description uses a specific verb ('Generate') and resource ('architecture decision record'), and states what the output captures: considered options, uncertainty, validation metrics, open questions, and reversal triggers. It is clear, but it does not explicitly name or differentiate against sibling tools like analyze_design_case or plan_pattern_adoption.

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

Usage Guidelines3/5

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

Use is implied: call this when a proposed ADR should be produced from a case. There is no explicit when/when-not guidance or mention of alternatives, so an agent must infer how this differs from the sibling planning/analysis tools.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/mateusdcc/pattern-intelligence-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server