claude-code-pro

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.

Safety Notice

This listing is from the official public ClawHub registry. Review SKILL.md and referenced scripts before running.

Copy this and send it to your AI assistant to learn

Install skill "claude-code-pro" with this command: npx skills add swaylq/claude-code-pro

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

Approach20-min taskTokens burned
Poll every 30s40 reads × ~500 tokens~20,000
Poll every 60s20 reads × ~500 tokens~10,000
This skill1 notification + 1 read~500

80-97% token savings on supervision alone.

Smart Dispatch: Know When NOT to Start

Before spawning Claude Code, ask:

SituationAction
< 3 files involvedDon't start CC. Just read + edit directly.
Single bug fixDon'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

# 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 {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)

# 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

# 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)

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

ModeFlagBehavior
auto--mode autoFull 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

ScriptPurpose
scripts/start.shLaunch CC in tmux with task
scripts/monitor.shLightweight output capture
scripts/send.shSend prompts / compact / approve
scripts/list.shList active sessions
scripts/stop.shKill sessions

Source Transparency

This detail page is rendered from real SKILL.md content. Trust labels are metadata-based hints, not a safety guarantee.

Related Skills

Related by shared tags or category signals.

Coding

Agent Dev Workflow

Orchestrate coding agents (Claude Code, Codex, etc.) to implement coding tasks through a structured workflow. Use when the user gives a coding requirement, f...

Registry SourceRecently Updated
Coding

Cortex Engine

Persistent cognitive memory for AI agents — query, record, review, and consolidate knowledge across sessions with spreading activation, FSRS scheduling, and...

Registry SourceRecently Updated
Coding

Skill Blocker - 安全守卫

Blocks execution of dangerous commands and risky operations like destructive deletions, credential theft, code injection, and unauthorized system changes to...

Registry SourceRecently Updated
014
Profile unavailable