# Architecture Validation

> Dynamically validate that the implemented codebase matches architectural decisions documented in plan files. Use when validating implementation matches planning documents, checking for architecture drift, or preparing for architecture reviews.

- **Type:** Skill
- **Install:** `agentstack add skill-d-o-hub-rust-self-learning-memory-architecture-validation`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [d-o-hub](https://agentstack.voostack.com/s/d-o-hub)
- **Installs:** 0
- **Category:** [Agent Skills](https://agentstack.voostack.com/c/agent-skills)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [d-o-hub](https://github.com/d-o-hub)
- **Source:** https://github.com/d-o-hub/rust-self-learning-memory/tree/main/.agents/skills/architecture-validation
- **Website:** https://d-o-hub.github.io/rust-self-learning-memory/

## Install

```sh
agentstack add skill-d-o-hub-rust-self-learning-memory-architecture-validation
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# Architecture Validation Skill

Dynamically validate that the implemented codebase matches architectural decisions documented in plan files.

## Quick Reference

- **[Dimensions](dimensions.md)** - What gets validated (components, dependencies, APIs, etc.)
- **[Workflow](workflow.md)** - Step-by-step validation process
- **[Extraction Patterns](extraction.md)** - How to extract architectural elements from plans
- **[Compliance](compliance.md)** - Compliance levels and report format
- **[Self-Learning](self-learning.md)** - Continuous improvement framework

## Purpose

**Generic, adaptive framework** that:
- Discovers all plan files in `plans/` directory
- Extracts architectural requirements dynamically
- Validates implementation compliance
- Reports gaps, drift, and violations

**Key Principle**: Be architecture-agnostic. Work with ANY project structure.

## When to Use

- Validating implementation matches planning documents
- Checking for architecture drift after development
- Ensuring design decisions are followed
- Identifying missing implementations
- Preparing for architecture reviews
- Verifying refactoring didn't break boundaries

## Validation Workflow

1. **Discover** - Find all plan files
2. **Extract** - Pull architectural elements
3. **Analyze** - Compare vs codebase
4. **Validate** - Check compliance
5. **Gap Analysis** - Identify missing/drift/extra
6. **Report** - Generate comprehensive report

See **[workflow.md](workflow.md)** for detailed phases and **[dimensions.md](dimensions.md)** for validation categories.

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [d-o-hub](https://github.com/d-o-hub)
- **Source:** [d-o-hub/rust-self-learning-memory](https://github.com/d-o-hub/rust-self-learning-memory)
- **License:** MIT
- **Homepage:** https://d-o-hub.github.io/rust-self-learning-memory/

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-d-o-hub-rust-self-learning-memory-architecture-validation
- Seller: https://agentstack.voostack.com/s/d-o-hub
- Browse the marketplace: https://agentstack.voostack.com/browse

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Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.