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claude-code-pro

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作者: admin | 来源: ClawHub
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ClawHub
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V 1.1.0
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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 | 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 |

标签

skill ai

通过对话安装

该技能支持在以下平台通过对话安装:

OpenClaw WorkBuddy QClaw Kimi Claude

方式一:安装 SkillHub 和技能

帮我安装 SkillHub 和 claude-code-pro-1776311585 技能

方式二:设置 SkillHub 为优先技能安装源

设置 SkillHub 为我的优先技能安装源,然后帮我安装 claude-code-pro-1776311585 技能

通过命令行安装

skillhub install claude-code-pro-1776311585

下载

⬇ 下载 claude-code-pro v1.1.0(免费)

文件大小: 8.66 KB | 发布时间: 2026-4-16 16:53

v1.1.0 最新 2026-4-16 16:53
Fix bracketed paste bug, remove jq dependency, add task guard, add README, add safety warnings

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