Skip to main content
Glama
tosin2013

mcp-adr-analysis-server

by tosin2013

generate_rules

Generate architectural rules from ADRs and code patterns to codify decisions. Specify source, paths, and output format to produce consistent, non-duplicative rules.

Instructions

Generate architectural rules from ADRs and code patterns

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sourceNoSource for rule generationboth
projectPathNoPath to project for pattern analysis.
adrDirectoryNoDirectory containing ADR filesdocs/adrs
outputFormatNoOutput format for rulesjson
existingRulesNoExisting rules to avoid duplication

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 indicate this is not read-only and not idempotent, but the description does not clarify what side effects occur: whether rules are persisted, returned, or written to files. It also does not mention prerequisites like existing ADRs or whether the tool modifies the project. No contradiction with annotations, but the behavioral detail is thin.

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, focused sentence with no filler words. It front-loads the main action and source material. It could be slightly more structured to include output behavior, but as a concise statement it is well-formed and readable.

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 five parameters, two enums, and no output schema, the description should clarify what the tool returns or writes and how the parameters relate to the outcome. It does not mention the output format behavior, the meaning of 'source', or whether existingRules are merged or merely respected. Significant context is missing.

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 every parameter already has a meaningful description. The tool description itself adds little beyond the schema, but with complete schema coverage this is acceptable. It does not introduce any parameter-specific nuance beyond what the schema provides, hence the baseline 3.

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 clearly states the action (generate), the resource (architectural rules), and the inputs (ADRs and code patterns). It is specific enough to convey the core purpose, though it does not explicitly differentiate from the sibling tool 'create_rule_set', which may overlap in function.

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?

The description implies a use case but provides no explicit guidance on when to use this tool versus alternatives like create_rule_set, validate_rules, or generate_adrs_from_prd. There are no stated conditions, exclusions, or references to sibling tools, leaving the agent to infer appropriateness.

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