147 lines
4.0 KiB
Markdown
147 lines
4.0 KiB
Markdown
---
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name: task-status
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description: "为长时间运行的任务在聊天中发送简短状态描述。"
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---
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# Task Status Skill
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## Quick Start
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### Manual Status Updates
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```bash
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python scripts/send_status.py "Starting data fetch..." "progress" "step1"
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python scripts/send_status.py "Processing complete" "success" "final"
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python scripts/send_status.py "Error: Missing API key" "error" "auth"
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```
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### Automatic Periodic Monitoring (Every 5 seconds)
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```bash
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# Start monitoring a long-running task
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python scripts/monitor_task.py start "My Long Task" "processing"
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# Monitor will send "Still working..." updates every 5 seconds
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# When task completes, report final status
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python scripts/monitor_task.py stop "My Long Task" "success" "Completed successfully!"
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```
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## Status Types
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- **progress**: Ongoing work (shows 🔄 or ->)
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- **success**: Task complete (shows ✅ or OK)
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- **error**: Failed task (shows ❌ or !)
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- **warning**: Issue but continuing (shows ⚠️ or ?)
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## Periodic Monitoring
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The `monitor_task.py` script provides automatic updates:
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### Starting Monitor
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```bash
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python scripts/monitor_task.py start "<task_name>" "<status_type>" [--interval <seconds>]
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```
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- Automatically sends "Still working..." updates every 5 seconds
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- Runs in background until stopped
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- Can be customized with different intervals
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### Stopping Monitor
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```bash
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python scripts/monitor_task.py stop "<task_name>" "<final_status>" "<final_message>"
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```
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### Example: Long File Processing
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```bash
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# Start monitoring
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python scripts/monitor_task.py start "video_processing" "progress"
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# ... long processing happens here ...
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# Stop with final status
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python scripts/monitor_task.py stop "video_processing" "success" "Processing complete!"
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```
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## Manual Updates (Quick Status)
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For single status updates without monitoring:
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```bash
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python scripts/send_status.py "Still fetching data..." "progress" "fetch"
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python scripts/send_status.py "Processing records: 250/1000" "progress" "process"
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python scripts/send_status.py "Complete! 3 files ready" "success" "final"
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python scripts/send_status.py "Error: Connection timeout" "error" "api"
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```
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## When to Use Each Method
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### Use Manual Updates When:
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- Task is short (under 30 seconds)
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- You want control over when updates are sent
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- Task has discrete, meaningful milestones
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### Use Periodic Monitoring When:
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- Task is long-running (over 1 minute)
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- You want consistent "heartbeat" updates every 5 seconds
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- Task has long periods of quiet work
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- You want to reassure user that work is ongoing
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## Message Guidelines
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Keep status messages under 140 characters. Examples:
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- **Progress**: "Still fetching data..." or "Processing records: 250/1000"
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- **Success**: "Complete! 3 files ready" or "Task finished successfully"
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- **Error**: "Error: Connection timeout" or "Failed: Missing API key"
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- **Warning**: "Continuing despite timeout" or "Partial success: 5/10 files"
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## Advanced Usage
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### With Additional Details
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```bash
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python scripts/send_status.py "Uploading..." "progress" "upload" --details "File: report.pdf (2.4MB)"
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```
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### Different Intervals
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```bash
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python scripts/monitor_task.py start "data_sync" "progress" --interval 10
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```
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### Importing for Python Scripts
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```python
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from send_status import send_status
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def long_task():
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send_status("Starting...", "progress", "step1")
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# ... work
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send_status("Step complete", "success", "step1")
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```
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## Automation with Clawdbot Cron
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For scheduled tasks, use Clawdbot's cron feature:
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```python
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# In a script or session
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from cron import add
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# Every 5 seconds, check status
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job = {
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"text": "Check status update",
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"interval": "5s",
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"enabled": True
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}
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add(job)
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```
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This allows status updates even when you're not actively watching.
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## Installation
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To use this skill, copy the `task-status` folder into your Clawdbot skills directory:
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```
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C:\Users\Luffy\AppData\Roaming\npm\node_modules\clawdbot\skills\task-status
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```
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Or add it to your workspace and reference it from `AGENTS.md` or `TOOLS.md`.
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Once installed, the skill will be available for any task where you need periodic status updates. |