task-status
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.
Best use case
task-status is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
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.
Teams using task-status should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/task-status/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How task-status Compares
| Feature / Agent | task-status | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this 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.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Task Status Skill
## Quick Start
### Manual Status Updates
```bash
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)
```bash
# 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
```bash
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
```bash
python scripts/monitor_task.py stop "<task_name>" "<final_status>" "<final_message>"
```
### Example: Long File Processing
```bash
# 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:
```bash
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
```bash
python scripts/send_status.py "Uploading..." "progress" "upload" --details "File: report.pdf (2.4MB)"
```
### Different Intervals
```bash
python scripts/monitor_task.py start "data_sync" "progress" --interval 10
```
### Importing for Python Scripts
```python
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:
```python
# 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`.
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