Architecture audit
Skill MarieLynneBlock/arcanum-artifex/skills/analysis/architecture-audit
Provides a repeatable, evidence-based framework for reviewing software architectures.From its SKILL.md
npx -y skills add MarieLynneBlock/arcanum-artifex --skill architecture-auditAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
2 things to look at
- no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
- 2 stars2 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
SKILL.md
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What this skill does
Provides a repeatable, evidence-based framework for reviewing software architectures. It evaluates a design against quality attributes (scalability, maintainability, security, reliability, performance, operability), checks for constraint violations, and produces a prioritised list of findings with actionable recommendations.
When to use it
- User asks to "review", "audit", or "assess" an architecture, design document, or ADR.
- User shares a system diagram, architecture description, or tech-stack decision and wants structured feedback.
- User wants to identify risks or trade-offs in a design before committing to it.
- User needs a report suitable for a design review meeting.
Instructions
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Understand scope. Clarify what is in scope (components, boundaries, interfaces) and what quality attributes matter most to the stakeholder. If not stated, default to: scalability, maintainability, security, reliability, performance, and operability.
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Collect evidence. Read any provided diagrams, ADRs, documentation, or code. Note what is explicit, what is implied, and what is missing.
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Evaluate each quality attribute. For each attribute in scope:
- State the current approach (how the architecture addresses it).
- Rate the approach:
Strong/Adequate/Weak/Not addressed. - Identify specific risks or gaps.
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Check constraints. Identify whether known constraints (team size, budget, compliance requirements, existing systems) are respected or at risk.
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Identify trade-offs. Call out explicit design trade-offs and assess whether they are intentional and well-reasoned.
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Prioritise findings. Rank findings by impact × likelihood:
Critical— must address before proceeding.High— address in the next iteration.Medium— schedule for backlog.Low/Informational— note for awareness.
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Write recommendations. For each Critical/High finding, provide at least one concrete, actionable recommendation.
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Produce the report using the output format below.
Output format
# Architecture Audit: [Subject]
**Date:** YYYY-MM-DD
**Auditor:** [name or AI-assisted]
**Scope:** [what was reviewed]
---
## Quality Attribute Summary
| Attribute | Rating | Key finding |
|-----------------|-----------|--------------------------------------|
| Scalability | Adequate | ... |
| Maintainability | Weak | ... |
| Security | Strong | ... |
| Reliability | Weak | ... |
| Performance | Adequate | ... |
| Operability | Not addressed | ... |
---
## Findings
### [CRITICAL/HIGH/MEDIUM/LOW] Finding title
**Evidence:** [what in the architecture leads to this finding]
**Risk:** [what could go wrong]
**Recommendation:** [concrete action]
---
## Trade-off Register
| Decision | What was gained | What was sacrificed | Intentional? |
|----------|----------------|---------------------|--------------|
| ... | ... | ... | Yes / No / Unknown |
---
## Summary
[2–4 sentence overall assessment. Is the architecture fit for purpose? What is the single most important thing to address?]
Examples
Example 1 — Microservices migration proposal
Input: User shares an ADR proposing to migrate a monolith to 12 microservices.
Expected output: Audit report rating each quality attribute, flagging operational complexity and distributed tracing gap as High findings, noting the trade-off between deployment independence and increased latency.
Example 2 — Database technology choice
Input: User asks to review a decision to use a document store for a heavily relational dataset.
Expected output: Report highlighting the data integrity (Critical) and query complexity (High) risks, recommending either a relational store or a hybrid approach with explicit join patterns.
Notes
- If the user provides insufficient detail, ask one targeted clarifying question before proceeding — do not invent architecture details.
- Do not rate a quality attribute as
Strongwithout citing specific evidence from the provided material. - Keep findings to the most impactful items; a ten-page list of nitpicks is less useful than three actionable priorities.
What ships with it
Read from the repository
Just SKILL.md. No reference files, no scripts.