openclaw-kirocli-coding-agentRun Codex CLI, Claude Code, Kiro CLI, OpenCode, or Pi Coding Agent via background process for programmatic control.
Install via ClawdBot CLI:
clawdbot install dandysuper/openclaw-kirocli-coding-agentUse bash (with optional background mode) for all coding agent work. Simple and effective.
Coding agents (Codex, Claude Code, Kiro, 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'"
AWS AI coding assistant with session persistence, custom agents, steering, and MCP integration.
Install: https://kiro.dev/docs/cli/installation
kiro-cli # Start interactive chat (default)
kiro-cli chat "Your question" # Direct question
kiro-cli --agent my-agent # Use specific agent
kiro-cli chat --resume # Resume last session (per-directory)
kiro-cli chat --resume-picker # Pick from saved sessions
kiro-cli chat --list-sessions # List all sessions
# Single response to STDOUT, then exit
kiro-cli chat --no-interactive "Show current directory"
# Trust all tools (no confirmation prompts)
kiro-cli chat --no-interactive --trust-all-tools "Create hello.py"
# Trust specific tools only (comma-separated)
kiro-cli chat --no-interactive --trust-tools "fs_read,fs_write" "Read package.json"
🔐 Tool Trust: Use --trust-all-tools for automation (default). For untrusted input or sensitive systems, consider --trust-tools "fs_read,fs_write,shell" to limit scope.
# Interactive session (background)
bash pty:true workdir:~/project background:true command:"kiro-cli"
# One-shot query (non-interactive)
bash pty:true workdir:~/project command:"kiro-cli chat --no-interactive --trust-all-tools 'List all TODO comments in src/'"
# With specific agent
bash pty:true workdir:~/project background:true command:"kiro-cli --agent aws-expert 'Set up Lambda'"
# Resume previous session
bash pty:true workdir:~/project command:"kiro-cli chat --resume"
Pre-define tool permissions, context resources, and behaviors:
kiro-cli agent list # List available agents
kiro-cli agent create my-agent # Create new agent
kiro-cli agent edit my-agent # Edit agent config
kiro-cli agent validate ./a.json # Validate config file
kiro-cli agent set-default my-agent # Set default
Benefits: Pre-approve trusted tools, limit tool access, auto-load project docs, share configs across team.
Provide persistent project knowledge via markdown files in .kiro/steering/:
.kiro/steering/
├── product.md # Product overview
├── tech.md # Tech stack
├── structure.md # Project structure
└── api-standards.md # API conventions
.kiro/steering/ — applies to current project only~/.kiro/steering/ — applies to all projects~/.kiro/steering/In custom agents: Add "resources": ["file://.kiro/steering/*/.md"] to config.
Connect external tools and data sources via Model Context Protocol:
kiro-cli mcp add --name my-server --command "node server.js" --scope workspace
kiro-cli mcp list [workspace|global]
kiro-cli mcp status --name my-server
kiro-cli mcp remove --name my-server --scope workspace
Plan Agent is a built-in agent for structured planning before execution. It helps transform ideas into detailed implementation plans.
When to suggest Plan Agent to user:
When NOT to use Plan Agent:
How to use:
# Start Plan mode
> /plan
# Or with immediate prompt
> /plan Build a REST API for user authentication
# Or toggle with keyboard shortcut
Shift + Tab
Plan workflow (4 phases):
y), plan transfers to execution agentPlan Agent limitations (read-only):
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 agent 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: <description>. Commit and push.'"
# 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
--trust-tools for untrusted inputWhen 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 gateway wake --text "Done: [brief summary of what was built]" --mode now
Example (Codex):
bash pty:true workdir:~/project background:true command:"codex --yolo exec 'Build a REST API for todos.
When completely finished, run: openclaw gateway wake --text \"Done: Built todos REST API with CRUD endpoints\" --mode now'"
This triggers an immediate wake event — 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 Feb 23, 2026
Maintainers can use the coding agent to automatically review pull requests in parallel, ensuring code quality without manual effort. By cloning PRs to temporary directories and running Codex with PTY, it provides detailed feedback that can be posted directly to GitHub, speeding up the review process for large projects.
Startup teams can leverage the agent to quickly generate and iterate on code for minimum viable products. Using background mode with PTY in a focused workdir, developers can prompt Codex or Claude to build features like dark mode toggles or API error handling, accelerating development cycles and reducing initial coding overhead.
Enterprises can employ the agent to refactor outdated modules, such as authentication systems, by running Codex in yolo mode for speed or full-auto for safety. With PTY and background sessions, it allows continuous monitoring and input, enabling efficient modernization of codebases while minimizing disruption to ongoing operations.
Instructors can use the agent to demonstrate coding concepts interactively in classrooms or online courses. By setting up temporary git repos and running agents like Kiro CLI with PTY, students see real-time code generation and execution, enhancing learning through hands-on examples and immediate feedback on prompts.
Developers working on AWS projects can integrate Kiro CLI for AI-driven coding support, leveraging its session persistence and MCP integration. Using PTY and background mode, they can automate tasks like infrastructure-as-code generation or debugging, improving productivity in cloud-native environments with guided AI interactions.
Offer a subscription-based service that integrates the coding agent to provide automated PR reviews for development teams. By using the batch review pattern with PTY, it scales across multiple repositories, charging per review or on a monthly basis, reducing manual effort and improving code quality for clients.
Provide consulting services to help companies implement and optimize the coding agent in their workflows. This includes setting up PTY configurations, background sessions, and integration with existing tools, generating revenue through project-based fees or ongoing support contracts tailored to client needs.
Develop and sell training programs and certifications focused on using coding agents like Codex and Claude effectively. Courses cover PTY usage, background processes, and scenario-based applications, with revenue from course sales, workshops, and certification exams for professionals seeking to enhance their skills.
💬 Integration Tip
Always enable PTY when running coding agents to avoid broken output, and use background mode with workdir for focused, long-running tasks to maintain control and monitor progress efficiently.
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