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memoriant-architecture-review-skill

Version License Platform

A Claude Code plugin for structured, repeatable AI-assisted architecture reviews. Accepts a brief YAML file or inline description, produces a narrative review with risk table, tradeoffs, follow-up questions, and a checklist — then appends an evidence record to an audit log.

Built on the methodology of NathanMaine/architectural-design-review-agent.


What It Does

  1. Loads an architecture brief from a YAML file or inline text.
  2. Validates the brief — asks for missing fields rather than guessing.
  3. Generates a structured review with:
    • Narrative summary
    • Risk table (likelihood, impact, mitigation per risk)
    • Tradeoffs (gains vs. costs per key decision)
    • Follow-up questions the brief does not answer
    • Checklist of standard items for the architecture type
  4. Presents the review as readable Markdown.
  5. Writes the structured JSON review to an optional output file.
  6. Appends a JSONL evidence record (who reviewed, when, how many risks/questions).

Installation

Claude Code

claude mcp add memoriant-architecture-review-skill

Or clone locally:

git clone https://github.com/NathanMaine/memoriant-architecture-review-skill ~/.claude/plugins/memoriant-architecture-review-skill

Codex CLI

codex install NathanMaine/memoriant-architecture-review-skill

Gemini CLI

gemini extension install NathanMaine/memoriant-architecture-review-skill

Usage

In Claude Code (natural language)

Review the architecture in fixtures/my_brief.yaml
Conduct an architecture review for our new caching layer. Context: [description]

Via skill invocation

/architecture-review --brief fixtures/my_brief.yaml --out review.json

Via Codex CLI

codex run architecture-review-agent --var brief=fixtures/my_brief.yaml

Architecture Brief Format

title: "Notifications Service v2"
context: |
  Moving notification dispatch off the critical request path to reduce P99 latency.
constraints:
  - Must not require a new database
  - Must deploy to existing Kubernetes cluster
components:
  - name: Message Queue
    description: RabbitMQ for async dispatch
  - name: Worker Pool
    description: 4 Python consumers
key_risks:
  - Queue saturation under traffic spikes
  - Worker failure leaving notifications undelivered

Plain Markdown or free-form prose is also accepted.


Plugin Structure

memoriant-architecture-review-skill/
├── .claude-plugin/
│   └── plugin.json                      # Plugin manifest
├── skills/
│   └── architecture-review/
│       └── SKILL.md                     # Full methodology for Claude Code
├── agents/
│   └── architecture-review-agent.md    # Autonomous agent definition
├── AGENTS.md                            # Codex CLI agent definitions
├── gemini-extension.json                # Gemini CLI extension manifest
├── SECURITY.md                          # Security policy
├── README.md                            # This file
└── LICENSE                              # MIT

Environment Variables

Variable Default Description
LLM_API_KEY (empty — stub mode) API key for the LLM provider
LLM_BASE_URL https://api.openai.com/v1 Base URL for the OpenAI-compatible API
LLM_MODEL gpt-4o-mini Model identifier
REVIEWER_ID anonymous Identity recorded in the evidence log
EVIDENCE_LOG_PATH logs/evidence.jsonl Evidence log location

Sample Output

## Architecture Review: Notifications Service v2

**Reviewed:** 2026-03-25 | **Reviewer:** anonymous

### Summary
The proposed async notification architecture reduces P99 latency by moving dispatch
off the critical path. Core risks are queue saturation and worker reliability.

### Risks
| ID | Description | Likelihood | Impact | Mitigation |
|----|-------------|-----------|--------|-----------|
| R1 | Queue saturation under spikes | Medium | High | Backpressure + overflow alert |
| R2 | Worker failure = lost messages | Low | High | Dead-letter queue + retry budget |

### Questions to Resolve
1. What happens when the queue reaches capacity?
2. Is there a dead-letter queue configured?

### Checklist
- [ ] Circuit breaker on gateway calls
- [ ] Retry policy with exponential backoff
- [ ] Queue depth monitoring dashboard

Source Reference

Derived from NathanMaine/architectural-design-review-agent, a Python CLI prototype for structured architecture reviews with evidence logging.


License

MIT — see LICENSE.

About

Claude Code plugin: AI-powered architecture review with risk assessments, questions, and checklists from design briefs.

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