Self-hosted Convex development in Coder workspaces with authentication, queries, mutations, React integration, and environment configuration

Coder workspace environment for hahomelabs.com deployments. Includes networking, ports, convex config, nhost config

**NEVER call memory MCP tools directly!** Use Task tool with `subagent_type: "general-purpose"` to keep main context clean.

**NEVER call memory MCP tools directly!** Use Task tool with `subagent_type: "general-purpose"` to keep main context clean.

Coder CLI commands for workspace management, templates, and platform operations

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This skill should be used when CodeRabbit code review feedback needs to be processed and fixed systematically. Use after running `coderabbit --plain` to automatically save feedback, analyze issues using MCP tools, and implement minimal code fixes with proper planning.

Implement fixes for specific CodeRabbit review issues. Runs in isolated subagent context with focused task. Verifies fixes with tests before returning. Use one per issue from triage task list.

Systematic workflow for CodeRabbit reviews - local CLI, PR threads, and commit attribution

Use after completing file changes - strongest for source code (AST-aware linting, security, tests), lighter support for markdown/config. Dispatches CodeRabbit reviewer subagent. ALWAYS request review before considering work complete.

Use CodeRabbit CLI to receive external code review feedback and address identified issues. Invoke this skill when the user requests CodeRabbit review, or proactively after implementing significant code changes to get feedback and improve code quality.

Integrates CodeRabbit for automated PR code review. Use after PR creation to get AI-powered review feedback before human review.

Analyze code review findings and create execution plan. Decides parallel vs sequential fixing based on issue severity and independence. Returns structured task list with clear fixer instructions.

Systematic workflow for CodeRabbit reviews - local CLI, PR threads, and commit attribution

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Analyze code for style violations, pattern compliance, and quality issues

Hand off a task to Codex CLI for autonomous execution. Use when a task would benefit from a capable subagent to implement, fix, investigate, or review code. Codex has full codebase access and can make changes.

Get a second opinion from OpenAI Codex CLI for plan reviews, code reviews, architecture decisions, and hard problems. Use when you need external validation, want to compare approaches, or are stuck on a difficult problem.

Execute tasks using OpenAI Codex CLI and analyze results.

Setup and manage OpenAI Codex CLI authentication including ChatGPT Plus/Pro OAuth, API keys, and multi-account management. Use when configuring Codex access, switching accounts, or troubleshooting authentication.

Orchestrates a triple-AI engineering loop where Claude plans, Codex validates logic and reviews code, and Cursor implements, with continuous feedback for optimal code quality

Dual-AI engineering loop orchestrating Claude Code (planning/implementation) and Codex (validation/review). Use when (1) complex feature development requiring validation, (2) high-quality code with security/performance concerns, (3) large-scale refactoring, (4) user requests codex-claude loop or dual-AI review. Do NOT use for simple one-off fixes or prototypes.

OpenAI Codex CLI orchestration for AI-assisted development using gpt-5.2-codex model. Capabilities: code generation, refactoring, automated editing, parallel task execution, session management, code review, architecture analysis, and MCP integration. Actions: analyze, implement, review, fix, refactor with Codex. Keywords: Codex CLI, gpt-5.2-codex, codex exec, code generation, refactoring, parallel execution, session resume, code review, second opinion, independent review, architecture validation, Context7 MCP. Use when: delegating complex code tasks to Codex, running multi-agent workflows, executing automated reviews, implementing features with AI assistance, resuming previous sessions, querying OpenAI documentation. Triggers: 'use codex', 'codex exec', 'run with codex', 'codex resume', 'implement with codex', 'review with codex', 'codex docs'.

Single source of truth and librarian for ALL OpenAI Codex CLI documentation. Manages local documentation storage, scraping, discovery, and resolution. Use when finding, locating, searching, or resolving Codex CLI documentation; discovering docs by keywords, category, tags, or natural language queries; scraping from llms.txt; managing index metadata (keywords, tags, aliases); or rebuilding index from filesystem. Run scripts to scrape, find, and resolve documentation. Handles doc_id resolution, keyword search, natural language queries, category/tag filtering, alias resolution, llms.txt parsing, markdown subsection extraction for internal use, hash-based drift detection, and comprehensive index maintenance.

OpenAI Codex CLI fundamentals for code analysis, review, and validation. Use when (1) executing codex commands for code review/analysis, (2) configuring models (gpt-5.2-codex/gpt-5.2/gpt-5.1-codex-max/codex-mini), sandbox modes (read-only/workspace-write), or reasoning effort (low/medium/high/xhigh), (3) managing Codex sessions with resume, (4) integrating Codex into automation scripts. Do NOT use for orchestration patterns (use codex-claude-loop instead).

Code review skill with rubric and templates

Comprehensive code review with Codex (gpt-5.2).

Codex CLI integration for code review and consultation. Use when: (1) code needs review before commit, (2) need expert consultation on implementation approach, (3) debugging assistance needed. This skill provides Codex interaction patterns only - workflow orchestration is defined in project CLAUDE.md.

Manages OpenAI Codex CLI configuration including config.toml settings, MCP servers, model profiles, sandbox modes, approval policies, and skill paths. Use when configuring Codex CLI, setting up model profiles, managing MCP server integrations, troubleshooting Codex configuration issues, or optimizing Codex for different workflows.

Invoke Codex CLI as a coworker for implementation, brainstorming, specs, and reviews. Use when you want parallel thinking, cheap execution, or a second opinion. Codex tokens are cheaper than yours — delegate aggressively. Keywords: codex, delegate, implement, draft, review, brainstorm, write tests, code review.

Automatically delegate complex, logic-intensive tasks to OpenAI Codex CLI via `codex exec --full-auto`. Claude Code uses this skill to invoke Codex for complex backend logic, intricate algorithms, or persistent bugs. Enables seamless AI-to-AI collaboration where Claude Code analyzes and Codex executes.

Execute development tasks using OpenAI Codex CLI for code generation, refactoring, feature implementation, and bug fixes. Use when the user asks to create code, add features, refactor, fix bugs, or generate tests. Requires Codex CLI installed.

Create or edit Codex execpolicy .rules files (allow/prompt/forbid commands, define prefix_rule patterns, add match/not_match tests) and validate them with codex execpolicy check. Use when a user mentions Codex rules, execpolicy, command policies, allowlists/denylists, or controlling which commands Codex can run, and when scope (global vs project) must be clarified.

Git-aware development workflows with Codex CLI including intelligent commits, PR automation, branch management, and diff application. Use for git operations, PR reviews, or automated git workflows.

Use Codex CLI in full-auto mode to fix issues iteratively until tests pass. Autonomous debugging and test-fixing loop with sandbox safety.

Use this when updating the codex submodule or when patch files in codex-patches/ need to be added, regenerated, or repaired.

[CLAUDE CODE ONLY] Leverage Codex CLI for AI peer review, second opinions on architecture and design decisions, cross-validation of implementations, security analysis, and alternative approach generation. Requires terminal access to execute Codex CLI commands. Use when making high-stakes decisions, reviewing complex architecture, or when explicitly requested for a second AI perspective. Must be explicitly invoked using skill syntax.

Read and integrate response from Codex. Use when user says codex read, get codex response, or check codex results.

Run the Codex Readiness integration test. Use when you need an end-to-end agentic loop with build/test scoring.

Run the Codex Readiness unit test report. Use when you need deterministic checks plus in-session LLM evals for AGENTS.md/PLANS.md.

Review implementation quality and regression risks via claude-delegator (Code Reviewer expert). Use after implementation for complex tasks, refactors, or API changes.

Automated code review workflow using OpenAI Codex CLI. Implements iterative fix-and-review cycles until code passes validation or reaches iteration limit. Use when building features requiring automated code validation, security checks, or quality assurance through Codex CLI.

Use Codex CLI sandbox mode to try risky changes safely. Isolated experimentation with network disabled and directory restrictions.

Use at the start of a Codex session (especially sandboxed) to run `scripts/codex-sandbox-preflight.sh` and interpret network + writable_roots constraints.

Run code in Codex fully isolated sandbox - network disabled, CWD only, Seatbelt/Docker isolation

Investigate the @openai/codex-sdk API by first inspecting installed .d.ts typings in node_modules, then cloning and searching the github.com/openai/codex repo for source/docs. Use for questions about Codex SDK API surface, types, response formats, threads/runs, or debugging codex-sdk behavior.

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Helps you to run a subagent using codex exec