oil-frontend
Standardized Chinese frontend conventions reduce integration friction and inconsistency across distributed agent-driven development, accelerating delivery an…
给前端 Agent 使用的中文规范,统一产品界面、数据状态、组件组织和代码归属。
- Ask Claude to review frontend code against Chinese naming and structure standards
- Generate consistent component organization guidelines for your design system
- Automate checks for data state naming and UI pattern compliance across projects
Standardized Chinese frontend conventions reduce integration friction and inconsistency across distributed agent-driven development, accelerating delivery and reducing rework from misaligned architecture decisions.
Engineering teams building multi-agent frontend systems or products requiring consistent UI/data patterns across Chinese-language codebases.
https://github.com/oil-oil/oil-frontend
By oil-oil
How to Get It
claude plugins install oil-oil/oil-frontend
Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.
Auto-generated from the tool's public listing — not hands-on verified. Cross-check against the source repo's README before running.
After installing, paste this into Claude:
Review frontend code against Chinese naming and structure standards
Trust Signals Auto-scanned
Community Pulse New
No community discussions found yet. This doesn't mean the tool isn't good — it may be new or serve a niche use case.
Reviewer notes
Auto-scanned review. These are observations, not a security certification.
Scored from trust signals (evidence-eval-v1): 74 GitHub stars; contributors unknown; last commit 0d ago; license MIT.
Things to check
- Scanned, not hands-on tested — this entry was auto-scanned from public metadata (GitHub metrics, license, security flags). No reviewer has run it, and no tool-specific limitations have been documented yet.
How to evaluate tools before deploying →
Data shown here comes from public APIs and automated scanning. Reviewer notes reflect one person's experience. This is not a security certification or legal recommendation. Always evaluate tools according to your own organization's policies.
Evaluation
Scored from trust signals (evidence-eval-v1): 74 GitHub stars; contributors unknown; last commit 0d ago; license MIT.