Token-efficient Claude Code workflow. Other skills burn tokens polling tmux every 30s — this one uses completion callbacks and only checks when notified. Observable tmux sessions, smart dispatch rules (know when NOT to spawn Claude Code), and structured JSON monitoring. Saves 80%+ supervision tokens vs polling-based approaches. Use when: multi-file coding tasks that need background execution. NOT for: simple single-file fixes (just read+edit directly — that's the point). Requires: tmux, claud...
Scanned 9/7/2026
Install to Claude Code
npx -y skills add modbender/skill-library-mcp --skill claude-code-pro --agent claude-codeInstalls into .claude/skills of the current project.
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---
name: claude-code-pro
description: >
Token-efficient Claude Code workflow. Other skills burn tokens polling tmux every 30s —
this one uses completion callbacks and only checks when notified. Observable tmux sessions,
smart dispatch rules (know when NOT to spawn Claude Code), and structured JSON monitoring.
Saves 80%+ supervision tokens vs polling-based approaches.
Use when: multi-file coding tasks that need background execution.
NOT for: simple single-file fixes (just read+edit directly — that's the point).
Requires: tmux, claude CLI.
metadata:
{
"openclaw":
{
"emoji": "⚡",
"os": ["darwin", "linux"],
"requires": { "bins": ["tmux", "bash"], "anyBins": ["claude"] },
},
}
---
# Claude Code Pro ⚡
Production-grade Claude Code workflow that doesn't waste your tokens.
## The Problem with Other Skills
Most Claude Code tmux skills work like this:
```
Start task → Poll every 30s → Poll → Poll → Poll → Done
🔥 tokens 🔥 🔥 🔥
```
Each poll reads 100-200 lines of terminal output, feeds it to your agent, and burns tokens deciding "is it done yet?" A 20-minute task = 40 polls = thousands of wasted tokens.
## How This Skill Works
```
Start task (with callback) → Wait → 📩 Notification → Read result (50 lines)
😴 zero tokens ⚡ one read
```
**The task itself tells you when it's done.** Your agent sleeps until notified. One lightweight check confirms the result. That's it.
### Token Savings Breakdown
| Approach | 20-min task | Tokens burned |
|----------|-------------|---------------|
| Poll every 30s | 40 reads × ~500 tokens | **~20,000** |
| Poll every 60s | 20 reads × ~500 tokens | **~10,000** |
| **This skill** | 1 notification + 1 read | **~500** |
**80-97% token savings** on supervision alone.
## Smart Dispatch: Know When NOT to Start
Before spawning Claude Code, ask:
| Situation | Action |
|-----------|--------|
| < 3 files involved | **Don't start CC.** Just read + edit directly. |
| Single bug fix | **Don't start CC.** Faster to fix inline. |
| Need extensive context exploration | ✅ Start CC |
| Multi-file refactor | ✅ Start CC |
| New feature (5+ files) | ✅ Start CC |
The fastest token savings come from not spawning a session at all.
## Quick Start
```bash
# Start a task — note the callback at the end
bash {baseDir}/scripts/start.sh --label auth-refactor --workdir ~/project --task "Refactor auth module to use JWT.
When completely finished, run: openclaw system event --text \"Done: JWT auth refactor complete\" --mode now"
```
That's the key line: `openclaw system event --text "Done: ..." --mode now`. The task notifies your agent on completion. No polling needed.
### Task from file (complex requirements)
```bash
bash {baseDir}/scripts/start.sh --label my-feature --workdir ~/project \
--task-file /path/to/requirements.md --mode auto
```
Write detailed requirements once upfront → fewer mid-task corrections → fewer tokens.
## Monitor (Only When Needed)
```bash
# Lightweight check — 50 lines, minimal tokens
bash {baseDir}/scripts/monitor.sh --session my-task --lines 50
# JSON mode — structured, even fewer tokens for agent parsing
bash {baseDir}/scripts/monitor.sh --session my-task --json
# Send follow-up (use sparingly — write requirements upfront instead)
bash {baseDir}/scripts/send.sh --session my-task --text "Also add unit tests"
# Compact context when running long
bash {baseDir}/scripts/send.sh --session my-task --compact
```
## Manage Sessions
```bash
# List all active sessions
bash {baseDir}/scripts/list.sh # human-readable
bash {baseDir}/scripts/list.sh --json # structured
# Stop sessions
bash {baseDir}/scripts/stop.sh --session my-task
bash {baseDir}/scripts/stop.sh --all
```
## Attach (Human SSH Access)
```bash
tmux -L cc attach -t cc-<label>
```
## Agent Workflow
```
1. DECIDE — Is this a 3+ file task? No → just edit. Yes → continue.
2. START — start.sh with detailed task + completion callback
3. WAIT — Do other work. Zero tokens spent watching.
4. NOTIFIED — Receive "Done: ..." event
5. CHECK — monitor.sh --lines 50 to confirm result
6. CLEANUP — stop.sh to end session
```
**Fallback:** If no notification after 15 minutes, one lightweight poll with `--json`.
## Completion Callback Template
Always append to your task prompt:
```
When completely finished, run this command to notify:
openclaw system event --text "Done: [brief description]" --mode now
```
This is what makes the whole approach work. The task signals completion; your agent doesn't need to guess.
## Modes
| Mode | Flag | Behavior |
|------|------|----------|
| auto | `--mode auto` | Full permissions, runs freely (default) |
## Design Choices
- **Isolated tmux socket** (`-L cc`) — doesn't interfere with your tmux sessions
- **`cc-` prefix** on all sessions — easy to list/filter
- **Bracketed paste** for multi-line prompts — no escaping issues
- **JSON output** from list/monitor — agent-friendly, fewer tokens to parse
## Files
| Script | Purpose |
|--------|---------|
| `scripts/start.sh` | Launch CC in tmux with task |
| `scripts/monitor.sh` | Lightweight output capture |
| `scripts/send.sh` | Send prompts / compact / approve |
| `scripts/list.sh` | List active sessions |
| `scripts/stop.sh` | Kill sessions |
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