architecture-review
architecture-review is an code AI skill with a core value of Review repository architecture using Ontoly Software Graph and MCP capabilities. It
helps developers solve real-world problems in the code domain, boosting
efficiency, automating repetitive tasks, and optimizing workflows.
Review repository architecture using Ontoly Software Graph and MCP capabilities. Use when asked to explain architecture, module boundaries, package topology, service ownership, or architectural risk.
Quick Facts
mkdir -p ./skills/architecture-review && curl -sfL https://raw.githubusercontent.com/sickn33/antigravity-awesome-skills/main/skills/architecture-review/SKILL.md -o ./skills/architecture-review/SKILL.mdRun in terminal / PowerShell. Requires curl (Unix) or PowerShell 5+ (Windows).
Skill Content
When to Use
- Use when this upstream workflow matches the user's stated goal.
- Use when the task requires the procedures documented in this skill.
# Architecture Review
Use this skill when the user asks for architecture review using Ontoly evidence.
Required Workflow
Follow [the shared Ontoly workflow. Also read [graph evidence rules, [MCP usage, [best practices, and [fallback rules when the task requires detail.
Ontoly Capabilities
Use these capabilities first: `ExplainArchitecture`, `GraphStatistics`, `FindCycles`, `FindDependencies`, `EvidencePack`.
Output Contract
Return:
- answer or plan
- capabilities invoked
- graph evidence with node ids, edge types, source spans, and graph hash when available
- confidence: high, medium, or low
- fallback reason if repository files were inspected
Boundaries
Do not implement compiler, query, MCP, SDK, or business logic in the skill. Do not search repository files until Ontoly cannot answer or evidence must be confirmed.
Resources
- [Examples
- [Prompt template
- [Capability notes
Learn more
- Documentation: https://ontoly.xyz/docs
- This skill on the web: https://ontoly.xyz/skills#architecture-review
- All Ontoly Agent Skills: https://ontoly.xyz/skills
- Install via skills.sh: https://www.skills.sh/?q=0xsarwagya/ontoly
Examples
User: Apply this skill to my current task.
Assistant: Follow the workflow in this skill, cite limitations, and ask before risky steps.Limitations
- Imported upstream skill; verify credentials, permissions, and safety boundaries before execution.
- Does not replace environment-specific validation, testing, or maintainer review.
🎯 Best For
- Engineering teams doing code reviews
- Open source maintainers
- Claude users
- Software engineers
- Development teams
💡 Use Cases
- Reviewing pull requests for security vulnerabilities
- Checking code style consistency
- Code quality improvement
- Best practice enforcement
📖 How to Use This Skill
- 1
Install the Skill
Copy the install command from the Terminal tab and run it. The SKILL.md file downloads to your local skills directory.
- 2
Load into Your AI Assistant
Open Claude and reference the skill. Paste the SKILL.md content or use the system prompt tab.
- 3
Apply architecture-review to Your Work
Open your project in the AI assistant and ask it to apply the skill. Start with a small module to verify the output quality.
- 4
Review and Refine
Review AI suggestions before committing. Run tests, check for regressions, and iterate on the skill output.
❓ Frequently Asked Questions
Does this skill check for OWASP Top 10?
Security-focused review skills often include OWASP checks. Check the skill content for specific vulnerability categories covered.
Is architecture-review compatible with Cursor and VS Code?
Yes — this skill works with any AI coding assistant including Cursor, VS Code with Copilot, and JetBrains IDEs.
Do I need specific dependencies for architecture-review?
Check the install command and Works With section. Most code skills only require the AI assistant and your codebase.
How do I install architecture-review?
Copy the install command from the Terminal tab and run it. The skill downloads to ./skills/architecture-review/SKILL.md, ready to use.
Can I customize this skill for my team?
Absolutely. Edit the SKILL.md file to add team-specific instructions, examples, or workflows.
⚠️ Common Mistakes to Avoid
Blindly accepting AI suggestions
Always verify AI-generated review comments. Some suggestions may not apply to your specific codebase conventions.
Skipping validation
Always test AI-generated code changes, even for simple refactors.
Missing dependency updates
Check if the skill requires updated dependencies or new packages.