adoresever/task-status

Task Status Skill

Quick Start

Manual Status Updates

python scripts/send_status.py "Starting data fetch..." "progress" "step1"
python scripts/send_status.py "Processing complete" "success" "final"
python scripts/send_status.py "Error: Missing API key" "error" "auth"

Automatic Periodic Monitoring (Every 5 seconds)

# Start monitoring a long-running task
python scripts/monitor_task.py start "My Long Task" "processing"

# Monitor will send "Still working..." updates every 5 seconds
# When task completes, report final status
python scripts/monitor_task.py stop "My Long Task" "success" "Completed successfully!"

Status Types

• progress: Ongoing work (shows 🔄 or ->)
• success: Task complete (shows ✅ or OK)
• error: Failed task (shows ❌ or !)
• warning: Issue but continuing (shows ⚠️ or ?)

Periodic Monitoring

The monitor_task.py script provides automatic updates:

Starting Monitor

python scripts/monitor_task.py start "<task_name>" "<status_type>" [--interval <seconds>]

• Automatically sends "Still working..." updates every 5 seconds
• Runs in background until stopped
• Can be customized with different intervals

Stopping Monitor

python scripts/monitor_task.py stop "<task_name>" "<final_status>" "<final_message>"

Example: Long File Processing

# Start monitoring
python scripts/monitor_task.py start "video_processing" "progress"

# ... long processing happens here ...

# Stop with final status
python scripts/monitor_task.py stop "video_processing" "success" "Processing complete!"

Manual Updates (Quick Status)

For single status updates without monitoring:

python scripts/send_status.py "Still fetching data..." "progress" "fetch"
python scripts/send_status.py "Processing records: 250/1000" "progress" "process"
python scripts/send_status.py "Complete! 3 files ready" "success" "final"
python scripts/send_status.py "Error: Connection timeout" "error" "api"

When to Use Each Method

Use Manual Updates When:

• Task is short (under 30 seconds)
• You want control over when updates are sent
• Task has discrete, meaningful milestones

Use Periodic Monitoring When:

• Task is long-running (over 1 minute)
• You want consistent "heartbeat" updates every 5 seconds
• Task has long periods of quiet work
• You want to reassure user that work is ongoing

Message Guidelines

Keep status messages under 140 characters. Examples:

• Progress: "Still fetching data..." or "Processing records: 250/1000"
• Success: "Complete! 3 files ready" or "Task finished successfully"
• Error: "Error: Connection timeout" or "Failed: Missing API key"
• Warning: "Continuing despite timeout" or "Partial success: 5/10 files"

Advanced Usage

With Additional Details

python scripts/send_status.py "Uploading..." "progress" "upload" --details "File: report.pdf (2.4MB)"

Different Intervals

python scripts/monitor_task.py start "data_sync" "progress" --interval 10

Importing for Python Scripts

from send_status import send_status

def long_task():
    send_status("Starting...", "progress", "step1")
    # ... work
    send_status("Step complete", "success", "step1")

Automation with Clawdbot Cron

For scheduled tasks, use Clawdbot's cron feature:

# In a script or session
from cron import add

# Every 5 seconds, check status
job = {
    "text": "Check status update",
    "interval": "5s",
    "enabled": True
}
add(job)

This allows status updates even when you're not actively watching.

Installation

To use this skill, copy the task-status folder into your Clawdbot skills directory:

C:\Users\Luffy\AppData\Roaming\npm\node_modules\clawdbot\skills\task-status

Or add it to your workspace and reference it from AGENTS.md or TOOLS.md.

Once installed, the skill will be available for any task where you need periodic status updates.