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Telegram Field Bot Agent Skill

Build Telegram bots for construction field workers. Real-time reporting, photo uploads, task assignments, progress tracking. Integrate with n8n for automated workflows.

3k tokens
context cost
the whole folder, loaded on every use
3
files
instructions only
0
copies elsewhere
how many repositories repackaged it
264
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill telegram-field-bot

The instruction itself

13 sections, as written by the author

Telegram Field Bot

Overview

Field workers need simple tools. Telegram bots provide instant communication, photo sharing, and task management without training or app downloads.

> "Telegram for field ops: Real-time task assignment and status updates" — DDC Community

Why Telegram?

| Feature | Benefit |

|---------|---------|

| No training | Workers already use Telegram |

| Works offline | Messages sync when connected |

| Photos/videos | Easy visual documentation |

| Groups | Team coordination |

| Bots | Automated workflows |

| Free | No per-user licensing |

Architecture

┌─────────────────────────────────────────────────────────────────┐
│                    TELEGRAM FIELD BOT                            │
├─────────────────────────────────────────────────────────────────┤
│                                                                  │
│  Field Worker              Bot                    n8n            │
│  ────────────              ───                    ───            │
│                                                                  │
│  📱 Send photo    ───▶    🤖 Receive     ───▶   ⚙️ Process     │
│  📝 Text report           📋 Parse              📊 Store        │
│  📍 Location              🏷️ Classify           📧 Notify       │
│                           ✅ Confirm            📈 Dashboard     │
│                                                                  │
└─────────────────────────────────────────────────────────────────┘

Quick Start with n8n

1. Create Telegram Bot

1. Open Telegram, search @BotFather
2. Send /newbot
3. Name: "SiteReport Bot"
4. Username: "sitereport_company_bot"
5. Copy the API token

2. n8n Workflow

{
  "workflow": "Telegram Field Reporting",
  "nodes": [
    {
      "name": "Telegram Trigger",
      "type": "Telegram",
      "event": "message",
      "token": "YOUR_BOT_TOKEN"
    },
    {
      "name": "Parse Message",
      "type": "Code",
      "code": "Parse message type: text, photo, location"
    },
    {
      "name": "Route by Type",
      "type": "Switch",
      "rules": ["photo", "text", "location", "command"]
    },
    {
      "name": "Process Photo",
      "type": "OpenAI Vision",
      "prompt": "Describe this construction site photo. Identify: progress, issues, safety concerns."
    },
    {
      "name": "Save to Database",
      "type": "PostgreSQL",
      "operation": "insert"
    },
    {
      "name": "Confirm to User",
      "type": "Telegram",
      "action": "sendMessage",
      "text": "✅ Report received! ID: {{report_id}}"
    }
  ]
}

Bot Commands

# /start - Welcome and instructions
# /report - Start daily report
# /photo - Upload site photo
# /issue - Report issue
# /progress - Update progress
# /weather - Log weather conditions
# /safety - Safety observation
# /help - Show commands

Python Bot Implementation

from telegram import Update, ReplyKeyboardMarkup
from telegram.ext import Application, CommandHandler, MessageHandler, filters, ContextTypes
import asyncio

# Bot token from BotFather
TOKEN = "YOUR_BOT_TOKEN"

# Keyboards
main_keyboard = ReplyKeyboardMarkup([
    ["📸 Photo Report", "📝 Text Report"],
    ["⚠️ Issue", "✅ Progress"],
    ["🌤️ Weather", "🦺 Safety"]
], resize_keyboard=True)

async def start(update: Update, context: ContextTypes.DEFAULT_TYPE):
    """Welcome message"""
    await update.message.reply_text(
        "👷 Site Report Bot\n\n"
        "Use the buttons below to submit reports.\n"
        "All reports are automatically logged and processed.",
        reply_markup=main_keyboard
    )

async def handle_photo(update: Update, context: ContextTypes.DEFAULT_TYPE):
    """Process photo submissions"""
    photo = update.message.photo[-1]  # Highest resolution
    file = await photo.get_file()

    # Download photo
    photo_path = f"photos/{update.message.chat.id}_{photo.file_id}.jpg"
    await file.download_to_drive(photo_path)

    # Get caption (description)
    caption = update.message.caption or "No description"

    # Get location if available
    location = None
    if update.message.location:
        location = {
            "lat": update.message.location.latitude,
            "lon": update.message.location.longitude
        }

    # Save to database (via n8n webhook or direct)
    report = {
        "type": "photo",
        "user_id": update.message.from_user.id,
        "username": update.message.from_user.username,
        "photo_path": photo_path,
        "caption": caption,
        "location": location,
        "timestamp": update.message.date.isoformat()
    }

    # Send to n8n for processing
    # requests.post("https://n8n.company.com/webhook/photo-report", json=report)

    await update.message.reply_text(
        f"✅ Photo received!\n"
        f"📝 Description: {caption}\n"
        f"🕐 Time: {update.message.date.strftime('%H:%M')}\n\n"
        "Photo will be analyzed and added to daily report."
    )

async def handle_text(update: Update, context: ContextTypes.DEFAULT_TYPE):
    """Process text reports"""
    text = update.message.text

    # Route based on button pressed
    if text == "📸 Photo Report":
        await update.message.reply_text("📸 Send a photo of the site with a description.")
    elif text == "📝 Text Report":
        await update.message.reply_text("📝 Type your progress report:")
    elif text == "⚠️ Issue":
        await update.message.reply_text(
            "⚠️ Describe the issue:\n"
            "- What is the problem?\n"
            "- Where is it located?\n"
            "- How urgent? (High/Medium/Low)"
        )
    elif text == "✅ Progress":
        await update.message.reply_text(
            "✅ Update progress:\n"
            "- What work was completed?\n"
            "- Percentage complete?\n"
            "- Any blockers?"
        )
    elif text == "🌤️ Weather":
        await update.message.reply_text(
            "🌤️ Weather conditions:\n"
            "- Temperature?\n"
            "- Conditions? (Clear/Rain/Snow/Wind)\n"
            "- Impact on work?"
        )
    elif text == "🦺 Safety":
        await update.message.reply_text(
            "🦺 Safety observation:\n"
            "- What did you observe?\n"
            "- Location?\n"
            "- Action taken?"
        )
    else:
        # Regular text report
        report = {
            "type": "text",
            "user_id": update.message.from_user.id,
            "username": update.message.from_user.username,
            "text": text,
            "timestamp": update.message.date.isoformat()
        }

        await update.message.reply_text("✅ Report logged!")

def main():
    """Start the bot"""
    app = Application.builder().token(TOKEN).build()

    app.add_handler(CommandHandler("start", start))
    app.add_handler(MessageHandler(filters.PHOTO, handle_photo))
    app.add_handler(MessageHandler(filters.TEXT & ~filters.COMMAND, handle_text))

    print("Bot started...")
    app.run_polling()

if __name__ == "__main__":
    main()

Daily Report Aggregation

def generate_daily_report(project_id: str, date: str) -> str:
    """Aggregate all Telegram reports into daily summary"""

    # Fetch all reports for the day
    reports = db.query("""
        SELECT * FROM telegram_reports
        WHERE project_id = ? AND DATE(timestamp) = ?
        ORDER BY timestamp
    """, [project_id, date])

    # Group by type
    photos = [r for r in reports if r['type'] == 'photo']
    issues = [r for r in reports if r['type'] == 'issue']
    progress = [r for r in reports if r['type'] == 'progress']

    # Generate summary with LLM
    summary = llm.summarize(f"""
        Daily reports for {date}:

        Photos submitted: {len(photos)}
        Issues reported: {len(issues)}
        Progress updates: {len(progress)}

        Details:
        {json.dumps(reports, indent=2)}

        Generate a concise daily report summary.
    """)

    return summary

Group Chat Features

# Track messages in project groups
async def handle_group_message(update: Update, context: ContextTypes.DEFAULT_TYPE):
    """Log important messages from project groups"""

    # Only log messages with keywords
    keywords = ["delay", "issue", "problem", "complete", "delivered", "inspection"]

    text = update.message.text.lower()
    if any(kw in text for kw in keywords):
        log_message({
            "group_id": update.message.chat.id,
            "group_name": update.message.chat.title,
            "user": update.message.from_user.username,
            "text": update.message.text,
            "timestamp": update.message.date.isoformat()
        })

Requirements

pip install python-telegram-bot requests

Resources

  • python-telegram-bot: https://python-telegram-bot.org
  • n8n Telegram: https://docs.n8n.io/integrations/builtin/app-nodes/n8n-nodes-base.telegram/
  • BotFather: https://t.me/BotFather

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How to use it

Copy the folder

Take datadrivenconstruction/telegram-field-bot from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.

Install what it needs

The instructions reference pip. Without those the skill loads but fails at the first command.