| ## Workflow Orchestration | |
| ### 1. Plan Mode Default | |
| - Enter plan mode for ANY non-trivial task (3+ steps or architectural decisions) | |
| - If something goes sideways, STOP and re-plan immediately | |
| - Don't keep pushing. | |
| - Use plan mode for verification steps, not just building | |
| - Write detailed specs upfront to reduce ambiguity | |
| ### 2. Subagent Strategy |
| name | description | user_invocable |
|---|---|---|
codex-review |
Send the current plan to OpenAI Codex CLI for iterative review. Claude and Codex go back-and-forth until Codex approves the plan. |
true |
Send the current implementation plan to OpenAI Codex for review. Claude revises the plan based on Codex's feedback and re-submits until Codex approves. Max 5 rounds.
You are a code reviewer agent powered by OpenAI Codex. Your job is to review code changes and provide actionable feedback.
mcp__codex__codex tool to start a Codex review session with the relevant code context.mcp__codex__codex-reply with the thread ID from step 2.Prompts to recreate each piece of the OpenClaw system. Use these with any AI coding assistant.
1. Personal CRM "Build a personal CRM that automatically scans my Gmail and Google Calendar to discover contacts from the past year. Store them in a SQLite database with vector embeddings so I can query in natural language ('who do I know at NVIDIA?' or 'who haven't I talked to in a while?'). Auto-filter noise senders like marketing emails and newsletters. Build profiles for each contact with their company, role, how I know them, and our interaction history. Add relationship health scores that flag stale relationships, follow-up reminders I can create, snooze, or mark done, and duplicate contact detection with merge suggestions. Link relevant documents from Box to contacts so when I look up a person, I also see related docs."
2. Meeting Action Items (Fathom)
| # OpenClaw Implementation Prompts | |
| Each prompt below is a self-contained brief you can hand to an AI coding assistant (or use as a project spec) to build that use case from scratch. Adapt the specific services to whatever you already use — the patterns are what matter. | |
| --- | |
| ## 1) Personal CRM Intelligence | |
| ``` | |
| Build me a personal CRM system that automatically tracks everyone I interact with, with smart filtering so it only adds real people — not newsletters, bots, or cold outreach. |
These rules define how an AI coding agent should plan, execute, verify, communicate, and recover when working in a real codebase. Optimize for correctness, minimalism, and developer experience.
| name | description | disable-model-invocation |
|---|---|---|
codex |
Use OpenAI Codex CLI for complex debugging, code analysis, or when stuck on difficult problems. Invokes Codex with a file-based question/answer pattern. |
true |
When you encounter a difficult problem that would benefit from a second perspective or deep analysis, use Codex via the file-based pattern.
| name | description |
|---|---|
Logging Best Practices |
Use before implementing logs in a medium to large scale production system. |
This skill is adpated from "Logging sucks. And here's how to make it better. by Boris Tane.
When helping with logging, observability, or debugging strategies, follow these principles:
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| --- | |
| alwaysApply: true | |
| --- | |
| # Claude Delegation via tmux MCP Server | |
| ## Overview | |
| This guide explains how to delegate tasks to Claude Code (claude-yolo) using the tmux MCP server. claude-yolo is a version of Claude Code that automatically performs many tasks in the background without needing as much user interaction as regular claude code (claude). This setup allows you to run Claude in a persistent tmux session and communicate with it programmatically through MCP server tools. |