three-man-team
Divides AI code generation into specialized agent roles (design, implementation, review), reducing hallucination and improving code quality in complex projec…
A structured 3-agent AI dev team — Architect, Builder, Reviewer. Built from production use. Token-optimized. Works with Claude Code, VS Code, Cursor, and any AI that supports context files.
- Generate microservice architectures with validation before implementation
- Review and refactor existing codebases with design consistency checks
- Onboard junior developers using AI-guided code reviews
Divides AI code generation into specialized agent roles (design, implementation, review), reducing hallucination and improving code quality in complex projects. Token-optimized to lower API costs on large codebases.
Teams using Claude Code, VS Code, or Cursor who need structured code review and architectural consistency without manual handoffs between design and implementation.
https://github.com/russelleNVy/three-man-team
By russelleNVy
How to Get It
claude plugins install russelleNVy/three-man-team
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:
Help me generate microservice architectures with validation before implementation
Trust Signals Auto-scanned
Community Pulse Active
Discussed on Hacker News, Reddit
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3 mentions across 1 sources
Reviewer notes
Auto-scanned review. These are observations, not a security certification.
Scored from trust signals (evidence-eval-v1): 813 GitHub stars; contributors unknown; last commit 7d 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.
- Single maintainer. Consider the risk if this person stops maintaining the project.
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): 813 GitHub stars; contributors unknown; last commit 7d ago; license MIT.