MCPInstall

task-status

by aaaaqwqProductivity & Automation

Send short status descriptions in chat for long-running tasks. Use when you need to provide periodic updates during multi-step operations, confirm task completion, or notify of failures. Includes automated periodic monitoring that sends updates every 5 seconds, status message templates, and a helper function for consistent status reporting.

Installs
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Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/aaaaqwq/agi-super-team --skill task-status
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads task-status automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

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.

FAQ

What does the task-status skill do?

Send short status descriptions in chat for long-running tasks. Use when you need to provide periodic updates during multi-step operations, confirm task completion, or notify of failures. Includes automated periodic monitoring that sends updates every 5 seconds, status message templates, and a helper function for consistent status reporting.

How do I install task-status?

Run npx skills add https://github.com/aaaaqwq/agi-super-team --skill task-status in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/task-status/ (personal) or .claude/skills/task-status/ (project).

Which AI agents can use task-status?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is task-status safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains task-status?

It is published by aaaaqwq in aaaaqwq/agi-super-team. It has 172 recorded installs.

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