By mintmcp
Autonomous dev loop: plan → implement → codex review → claude review → fix → repeat
Use this agent when you need to review code for adherence to project guidelines, style guides, and best practices. This agent should be used proactively after writing or modifying code, especially before committing changes or creating pull requests. It will check for style violations, potential issues, and ensure code follows the established patterns in CLAUDE.md. Also the agent needs to know which files to focus on for the review. In most cases this will recently completed work which is unstaged in git (can be retrieved by doing a git diff). However there can be cases where this is different, make sure to specify this as the agent input when calling the agent. Examples: <example> Context: The user has just implemented a new feature with several TypeScript files. user: "I've added the new authentication feature. Can you check if everything looks good?" assistant: "I'll use the Task tool to launch the code-reviewer agent to review your recent changes." <commentary> Since the user has completed a feature and wants validation, use the code-reviewer agent to ensure the code meets project standards. </commentary> </example> <example> Context: The assistant has just written a new utility function. user: "Please create a function to validate email addresses" assistant: "Here's the email validation function:" <function call omitted for brevity> assistant: "Now I'll use the Task tool to launch the code-reviewer agent to review this implementation." <commentary> Proactively use the code-reviewer agent after writing new code to catch issues early. </commentary> </example> <example> Context: The user is about to create a PR. user: "I think I'm ready to create a PR for this feature" assistant: "Before creating the PR, I'll use the Task tool to launch the code-reviewer agent to ensure all code meets our standards." <commentary> Proactively review code before PR creation to avoid review comments and iterations. </commentary> </example>
Use this agent when code has been written or modified and needs to be simplified for clarity, consistency, and maintainability while preserving all functionality. This agent should be triggered automatically after completing a coding task or writing a logical chunk of code. It simplifies code by following project best practices while retaining all functionality. The agent focuses only on recently modified code unless instructed otherwise. Examples: <example> Context: The assistant has just implemented a new feature that adds user authentication to an API endpoint. user: "Please add authentication to the /api/users endpoint" assistant: "I've implemented the authentication for the /api/users endpoint. Here's the code:" <function call omitted for brevity> <commentary> Since a logical chunk of code has been written (authentication feature), use the Task tool to launch the code-simplifier agent to improve the code's clarity and maintainability while preserving functionality. </commentary> assistant: "Now let me use the code-simplifier agent to refine this implementation for better clarity and maintainability" </example> <example> Context: The assistant has just fixed a bug by adding several conditional checks. user: "Fix the null pointer exception in the data processor" assistant: "I've added the necessary null checks to prevent the exception:" <function call omitted for brevity> <commentary> After modifying code to fix a bug, use the code-simplifier agent to ensure the fix follows best practices and maintains code quality. </commentary> assistant: "Let me refine this bug fix using the code-simplifier agent to ensure it follows our best practices" </example> <example> Context: The assistant has just refactored a function to improve performance. user: "Optimize the data sorting algorithm for better performance" assistant: "I've optimized the sorting algorithm. Here's the updated implementation:" <function call omitted for brevity> <commentary> After completing a performance optimization task, use the code-simplifier agent to ensure the optimized code is also clear and maintainable. </commentary> assistant: "Now I'll use the code-simplifier agent to ensure the optimized code is also clear and follows our coding standards" </example>
Use this agent when reviewing code changes in a pull request to identify silent failures, inadequate error handling, and inappropriate fallback behavior. This agent should be invoked proactively after completing a logical chunk of work that involves error handling, catch blocks, fallback logic, or any code that could potentially suppress errors. Examples: <example> Context: Daisy has just finished implementing a new feature that fetches data from an API with fallback behavior. Daisy: "I've added error handling to the API client. Can you review it?" Assistant: "Let me use the silent-failure-hunter agent to thoroughly examine the error handling in your changes." <Task tool invocation to launch silent-failure-hunter agent> </example> <example> Context: Daisy has created a PR with changes that include try-catch blocks. Daisy: "Please review PR #1234" Assistant: "I'll use the silent-failure-hunter agent to check for any silent failures or inadequate error handling in this PR." <Task tool invocation to launch silent-failure-hunter agent> </example> <example> Context: Daisy has just refactored error handling code. Daisy: "I've updated the error handling in the authentication module" Assistant: "Let me proactively use the silent-failure-hunter agent to ensure the error handling changes don't introduce silent failures." <Task tool invocation to launch silent-failure-hunter agent> </example>
Uses power tools
Uses Bash, Write, or Edit tools
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Most coding agents generate code in a single pass and ship it. This plugin runs a review loop instead: Codex and Claude take turns reviewing and fixing code until both agree there's nothing left to fix.
Each run can take 30+ minutes, but the output is dramatically better because the code has been through up to 8 independent review cycles before you ever see the PR.
Install via the Claude Code plugin marketplace:
/plugin marketplace add mintmcp/dev-loop
/plugin install dev-loop
Restart Claude Code after installing.
/dev-loop <work prompt>
/dev-loop max_iterations=2 <work prompt>
/dev-loop implement the spec in docs/feature.md
Default: 4 iterations (up to 8 total review cycles, 4 Codex + 4 Claude).
Codex (gpt-5.4) excels at detailed bug finding, edge cases, and security issues because it reviews in a read-only sandbox with high reasoning effort. Claude has more context about user intent, so it can reject Codex nits that don't matter and run 3 specialized review agents in parallel. Claude is also the one that fixes code in both passes, since it has full write access.
The loop writes state to .claude/dev-loop-state.json so it can survive context compaction. A human-readable log goes to .claude/dev-loop.log.md. Both are automatically gitignored.
If triggered from a Slack thread (with Slack MCP configured), the loop posts one-liner progress updates back to the thread after each phase. This is best-effort: if Slack MCP is unavailable, updates are silently skipped.
.
├── .claude-plugin/
│ └── marketplace.json
├── dev-loop/
│ ├── .claude-plugin/
│ │ └── plugin.json
│ ├── .mcp.json # Codex MCP server config
│ ├── agents/
│ │ ├── code-reviewer.md # Code review agent
│ │ ├── code-simplifier.md # Code simplification agent
│ │ └── silent-failure-hunter.md # Error handling auditor
│ ├── hooks/
│ │ └── hooks.json # Stop + PostToolUse hook config
│ ├── scripts/
│ │ ├── stop-check.sh # Prevents stopping mid-loop
│ │ └── phase-reminder.sh # Phase-specific reminders
│ └── skills/
│ └── dev-loop/
│ └── SKILL.md # Main skill definition
├── tests/
│ └── run.sh # Hook script tests
├── LICENSE
└── README.md
dev-loop/skills/dev-loop/SKILL.md for the full workflow definition../tests/run.sh
Tests validate the stop-check and phase-reminder hook scripts against various state scenarios.
Apache License 2.0. See LICENSE.
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