Sets up a project for AI-assisted development with optimized CLAUDE.md, coding guidelines, and formatter hooks. Provides structured workflows for brainstorming, spec-driven development, TDD, code review, refactoring, test coverage analysis, git branch/commit/PR management, JIRA integration, and project documentation.
Simplifies and refines code for clarity, consistency, and maintainability while preserving all functionality. Focuses on recently modified code unless instructed otherwise.
Monitors test coverage gaps when testable code is added or modified. Does not write tests — only flags what needs testing.
Guides structured design brainstorming — explores the codebase, asks clarifying questions, proposes multiple approaches with trade-offs, and writes an approved spec to docs/specs/ for /optimus:tdd and /optimus:workflow to auto-detect. Use before implementation to think through design decisions and avoid premature coding. Produces a persistent artifact that feeds into plan mode and TDD. For stakeholder-facing or acceptance-criteria-driven work, the spec includes a Given/When/Then Scenarios section consumed by /optimus:tdd.
Creates and switches to a new, conventionally named branch — derives the name from an inline description, conversation context, or local git diffs. Preserves all local changes. Never commits or pushes. Use when you want a properly named branch for new or in-progress work.
Iterative auto-fix code review — runs `/optimus:code-review` in a fresh subagent context per iteration, applies fixes, runs tests, bisects failures, and continues until convergence or the iteration cap (default 8, hard cap 20). Creates a git checkpoint commit after each iteration (skip with --no-commit). Requires a test command in .claude/CLAUDE.md. Use when single-pass review leaves issues or for thorough cleanup before a release.
Reviews local changes, PRs/MRs, or branch diffs against project coding guidelines using 5 to 7 parallel review agents (bug detection, security/logic, guideline compliance x2, code simplification, test coverage, contract quality). Use before committing, on open PRs/MRs, or to review any branch diff. HIGH SIGNAL only: real bugs, logic errors, security concerns, and guideline violations. For iterative auto-fix in a loop, use `/optimus:code-review-deep`.
Suggests conventional commit messages by analyzing staged, unstaged, and untracked git changes — read-only, never commits. Use when a commit message suggestion is needed without actually committing. Best run in the conversation where the changes were implemented, so the message body captures the why.
Uses power tools
Uses Bash, Write, or Edit tools
Based on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
A Claude Code plugin that sets up your project for effective AI-assisted engineering.
The problem: AI amplifies whatever it finds. Messy code leads to messier AI-generated code, which becomes the new context for even worse output — a vicious cycle that compounds faster than any human could create technical debt. Without maintained context, any AI coding tool's quality degrades with every file it reads.
The solution: Optimus Claude generates tailored and optimized CLAUDE.md files, coding guidelines, formatter hooks, TDD and test coverage, all based on your actual codebase. Built-in quality agents (code simplifier, test guardian) run alongside reviews and TDD cycles; refactor runs the code simplifier plus its own consistency and testability agents.
Use it regularly and your project stays clean, consistent, tested, and well-documented. Exactly the conditions where Claude Code performs at its prime.
The philosophy: This is all about perfecting context. The codebase, prompts, unit tests, docs, commit messages, PR descriptions, branch names — it's all context and it all adds up to shape how well Claude Code performs. Optimus Claude provides developers ways to create and maintain optimal context for AI-assisted engineering across the entire development workflow.
Run these commands inside Claude Code:
/plugin marketplace add https://github.com/oprogramadorreal/optimus-claude.git
/plugin install optimus@optimus-claude
Having trouble? See Troubleshooting.
Start a new Claude Code session and type /optimus:init in any project directory. See Skills for the full list.
Every skill operates on the same shared foundation: your project's quality guidelines (coding guidelines for code, skill-writing guidelines for markdown instruction projects) and a verification protocol that demands evidence over confidence.
/optimus:init analyzes your codebase and generates constraint docs — coding guidelines, CLAUDE.md, formatter hooks, and test infrastructure (framework, coverage tooling, testing docs) — into your .claude/ directory. It detects your project's stacks (Python, Node, Rust, UI frameworks, etc.) and installs the matching quality doc for each. This includes skill authoring as a recognized stack: if your project is a Claude Code plugin, a Codex skill repo, a prompt library, or any other project whose "source code" includes markdown instructions authored for an AI agent, init installs skill-writing-guidelines.md alongside coding-guidelines.md, and review/refactor skills route markdown instruction files through the skill-writing lens while routing code files through the coding lens. The plugin bundles quality agents at two levels: plugin-level agents (code-simplifier, test-guardian) that define reusable quality concerns, and skill-level agents that adapt them for specific workflows within skills like code-review, refactor, and tdd. Skill-level agents often extend the plugin-level definitions with skill-specific scope and output format — see references/agent-architecture.md for the full architecture. From that point on, skills that analyze or modify code load the relevant guidelines, and skills that make completion claims apply the verification protocol as a gate before reporting.
/optimus:code-review doesn't run a generic review — its agents check your naming conventions, your architectural patterns, and your DRY principles alongside bugs and security. For projects with a skill-authoring stack, it also reviews markdown instruction files against your skill-writing conventions (progressive disclosure, writing style, reference-depth limits). /optimus:tdd applies coding-guidelines.md during the Refactor step. /optimus:refactor uses them as its quality lens. /optimus:unit-test follows them for test naming and structure.
Every skill is also conservative by default — /optimus:unit-test never refactors source code, and /optimus:commit warns about secret files before proceeding.
The result: consistent patterns, meaningful names, and lean context across every operation — exactly the signals that keep Claude Code accurate and productive.
npx claudepluginhub oprogramadorreal/optimus-claude --plugin optimusInteractive setup wizard for configuring any repository with Claude Code best practices, based on Boris Cherny's workflow
Universal Claude Code workflow with specialized agents, skills, hooks, and output styles for any software project. Includes orchestrator, code-reviewer, debugger, docs-writer, security-auditor, refactorer, and test-architect agents.
Use Claude Code As Is - native plugin leveraging built-in architecture
SDLC enforcement for AI agents — TDD, planning, self-review, CI shepherd
Autonomous session orchestrator for Claude Code - manages multi-phase development workflows
PROJECT.md-first autonomous development with hybrid auto-fix documentation. 8-agent pipeline, auto-orchestration, docs auto-update on commit (true vibe coding). Knowledge base system with 90% faster repeat research. Strict mode enforces SDLC best practices automatically. Works for ANY Python/JavaScript/TypeScript/Go project.