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tosin2013

mcp-adr-analysis-server

by tosin2013

create_rule_set

Create machine-readable rule sets in JSON/YAML from ADR and pattern rules to enforce architectural decisions.

Instructions

Create machine-readable rule set in JSON/YAML format

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesName of the rule set
rulesNoAdditional rules to include
authorNoAuthor of the rule setMCP ADR Analysis Server
adrRulesNoRules extracted from ADRs
descriptionNoDescription of the rule setGenerated architectural rule set
outputFormatNoOutput format for rule setjson
patternRulesNoRules generated from code patterns

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.9/5.0
Behavior2/5

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

Annotations provide only non-hints (readOnlyHint, idempotentHint, destructiveHint all false), so the description carries the burden of explaining side effects. It only restates that the tool creates something and mentions formatting, but does not disclose whether repeated calls create duplicates, whether existing rule sets are overwritten, or what persists.

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

Conciseness4/5

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

The description is a single, front-loaded sentence with no filler or redundancy. It is concise, though somewhat under-specified; the brevity is structurally sound but not maximally useful.

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

Completeness2/5

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

With 7 parameters, no output schema, and only generic annotations, the description is too thin. It does not explain how adrRules/patternRules relate to the creation process, what outputFormat 'both' means in behavior, or what the caller should expect after invocation.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already documents all 7 parameters. The description adds no parameter-level meaning beyond the outputFormat concept already present in the schema, making the baseline 3 appropriate.

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 states a clear verb ('Create') and resource ('machine-readable rule set') and includes the output format ('JSON/YAML format'). However, it does not differentiate this tool from similar siblings like generate_rules or configure_custom_patterns, and it omits the rule sources (ADR/pattern) visible in the schema.

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

Usage Guidelines2/5

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

There is no guidance about when to use this tool versus alternatives, no prerequisites, and no exclusions. The description is generic and does not help an agent choose between create_rule_set and similarly named rule-related tools.

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