coding-agent-backupDelegate coding tasks to Codex, Claude Code, or Pi agents via background process. Use when: (1) building/creating new features or apps, (2) reviewing PRs (sp...
Install via ClawdBot CLI:
clawdbot install nickchan0412/coding-agent-backupUse bash (with optional background mode) for all coding agent work. Simple and effective.
Coding agents (Codex, Claude Code, Pi) are interactive terminal applications that need a pseudo-terminal (PTY) to work correctly. Without PTY, you'll get broken output, missing colors, or the agent may hang.
Always use pty:true when running coding agents:
# ✅ Correct - with PTY
bash pty:true command:"codex exec 'Your prompt'"
# ❌ Wrong - no PTY, agent may break
bash command:"codex exec 'Your prompt'"
| Parameter | Type | Description |
| ------------ | ------- | --------------------------------------------------------------------------- |
| command | string | The shell command to run |
| pty | boolean | Use for coding agents! Allocates a pseudo-terminal for interactive CLIs |
| workdir | string | Working directory (agent sees only this folder's context) |
| background | boolean | Run in background, returns sessionId for monitoring |
| timeout | number | Timeout in seconds (kills process on expiry) |
| elevated | boolean | Run on host instead of sandbox (if allowed) |
| Action | Description |
| ----------- | ---------------------------------------------------- |
| list | List all running/recent sessions |
| poll | Check if session is still running |
| log | Get session output (with optional offset/limit) |
| write | Send raw data to stdin |
| submit | Send data + newline (like typing and pressing Enter) |
| send-keys | Send key tokens or hex bytes |
| paste | Paste text (with optional bracketed mode) |
| kill | Terminate the session |
For quick prompts/chats, create a temp git repo and run:
# Quick chat (Codex needs a git repo!)
SCRATCH=$(mktemp -d) && cd $SCRATCH && git init && codex exec "Your prompt here"
# Or in a real project - with PTY!
bash pty:true workdir:~/Projects/myproject command:"codex exec 'Add error handling to the API calls'"
Why git init? Codex refuses to run outside a trusted git directory. Creating a temp repo solves this for scratch work.
For longer tasks, use background mode with PTY:
# Start agent in target directory (with PTY!)
bash pty:true workdir:~/project background:true command:"codex exec --full-auto 'Build a snake game'"
# Returns sessionId for tracking
# Monitor progress
process action:log sessionId:XXX
# Check if done
process action:poll sessionId:XXX
# Send input (if agent asks a question)
process action:write sessionId:XXX data:"y"
# Submit with Enter (like typing "yes" and pressing Enter)
process action:submit sessionId:XXX data:"yes"
# Kill if needed
process action:kill sessionId:XXX
Why workdir matters: Agent wakes up in a focused directory, doesn't wander off reading unrelated files (like your soul.md 😅).
Model: gpt-5.2-codex is the default (set in ~/.codex/config.toml)
| Flag | Effect |
| --------------- | -------------------------------------------------- |
| exec "prompt" | One-shot execution, exits when done |
| --full-auto | Sandboxed but auto-approves in workspace |
| --yolo | NO sandbox, NO approvals (fastest, most dangerous) |
# Quick one-shot (auto-approves) - remember PTY!
bash pty:true workdir:~/project command:"codex exec --full-auto 'Build a dark mode toggle'"
# Background for longer work
bash pty:true workdir:~/project background:true command:"codex --yolo 'Refactor the auth module'"
⚠️ CRITICAL: Never review PRs in OpenClaw's own project folder!
Clone to temp folder or use git worktree.
# Clone to temp for safe review
REVIEW_DIR=$(mktemp -d)
git clone https://github.com/user/repo.git $REVIEW_DIR
cd $REVIEW_DIR && gh pr checkout 130
bash pty:true workdir:$REVIEW_DIR command:"codex review --base origin/main"
# Clean up after: trash $REVIEW_DIR
# Or use git worktree (keeps main intact)
git worktree add /tmp/pr-130-review pr-130-branch
bash pty:true workdir:/tmp/pr-130-review command:"codex review --base main"
# Fetch all PR refs first
git fetch origin '+refs/pull/*/head:refs/remotes/origin/pr/*'
# Deploy the army - one Codex per PR (all with PTY!)
bash pty:true workdir:~/project background:true command:"codex exec 'Review PR #86. git diff origin/main...origin/pr/86'"
bash pty:true workdir:~/project background:true command:"codex exec 'Review PR #87. git diff origin/main...origin/pr/87'"
# Monitor all
process action:list
# Post results to GitHub
gh pr comment <PR#> --body "<review content>"
# With PTY for proper terminal output
bash pty:true workdir:~/project command:"claude 'Your task'"
# Background
bash pty:true workdir:~/project background:true command:"claude 'Your task'"
bash pty:true workdir:~/project command:"opencode run 'Your task'"
# Install: npm install -g @mariozechner/pi-coding-agent
bash pty:true workdir:~/project command:"pi 'Your task'"
# Non-interactive mode (PTY still recommended)
bash pty:true command:"pi -p 'Summarize src/'"
# Different provider/model
bash pty:true command:"pi --provider openai --model gpt-4o-mini -p 'Your task'"
Note: Pi now has Anthropic prompt caching enabled (PR #584, merged Jan 2026)!
For fixing multiple issues in parallel, use git worktrees:
# 1. Create worktrees for each issue
git worktree add -b fix/issue-78 /tmp/issue-78 main
git worktree add -b fix/issue-99 /tmp/issue-99 main
# 2. Launch Codex in each (background + PTY!)
bash pty:true workdir:/tmp/issue-78 background:true command:"pnpm install && codex --yolo 'Fix issue #78: <description>. Commit and push.'"
bash pty:true workdir:/tmp/issue-99 background:true command:"pnpm install && codex --yolo 'Fix issue #99 from the approved ticket summary. Implement only the in-scope edits and commit after review.'"
# 3. Monitor progress
process action:list
process action:log sessionId:XXX
# 4. Create PRs after fixes
cd /tmp/issue-78 && git push -u origin fix/issue-78
gh pr create --repo user/repo --head fix/issue-78 --title "fix: ..." --body "..."
# 5. Cleanup
git worktree remove /tmp/issue-78
git worktree remove /tmp/issue-99
When you spawn coding agents in the background, keep the user in the loop.
This prevents the user from seeing only "Agent failed before reply" and having no idea what happened.
For long-running background tasks, append a wake trigger to your prompt so OpenClaw gets notified immediately when the agent finishes (instead of waiting for the next heartbeat):
... your task here.
When completely finished, run this command to notify me:
openclaw system event --text "Done: [brief summary of what was built]" --mode now
Example:
bash pty:true workdir:~/project background:true command:"codex --yolo exec 'Build a REST API for todos.
When completely finished, run: openclaw system event --text \"Done: Built todos REST API with CRUD endpoints\" --mode now'"
This triggers an immediate wake event — Skippy gets pinged in seconds, not 10 minutes.
pty:true, output breaks or agent hangs.mktemp -d && git init for scratch work.codex exec "prompt" runs and exits cleanly - perfect for one-shots.submit to send input + Enter, write for raw data without newline.Generated Mar 1, 2026
Agencies can use this skill to delegate coding tasks like building new features or refactoring legacy codebases for client projects. By running agents in background with PTY mode, developers can manage multiple tasks concurrently, improving throughput and reducing manual oversight.
Maintainers can automate PR reviews by spawning coding agents in temporary directories to analyze code changes safely. This helps scale review processes, ensure code quality, and integrate feedback without risking the main workspace.
Platforms can integrate this skill to provide students with AI-assisted coding exercises, where agents generate or refactor code in sandboxed environments. It supports iterative learning by allowing file exploration and automated feedback loops.
Startups can accelerate product development by using coding agents to build prototypes and new features iteratively. With background sessions and PTY, teams can focus on strategy while agents handle coding tasks in designated project directories.
Offer this skill as part of a cloud-based AI coding assistant platform, charging monthly fees based on usage tiers (e.g., number of agent sessions or compute time). Targets developers and teams needing scalable coding automation.
License the skill to large corporations for internal use, such as automating code reviews and refactoring in proprietary systems. Includes custom integration support, security audits, and dedicated SLAs for reliability.
Provide a free tier with basic agent capabilities (e.g., limited sessions) to attract individual developers, then upsell to premium features like parallel PR reviews or advanced AI models. Monetizes through upgrades and add-ons.
💬 Integration Tip
Ensure the hosting environment supports PTY mode in bash tools to avoid agent hangs, and always isolate agent work from critical directories like ~/clawd to prevent data corruption.
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