Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add jdmorag97-rgb/DDC_Skills_for_AI_Agents_in_Construction --skill telegram-field-botgit clone --depth 1 https://github.com/jdmorag97-rgb/DDC_Skills_for_AI_Agents_in_ConstructionWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/jdmorag97-rgb/ddc_skills_for_ai_agents_in_construction/telegram-field-bot)<a href="https://agentmods.dev/skills/jdmorag97-rgb/ddc_skills_for_ai_agents_in_construction/telegram-field-bot"><img src="https://agentmods.dev/badge/skills/jdmorag97-rgb/ddc_skills_for_ai_agents_in_construction/telegram-field-bot/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/jdmorag97-rgb/ddc_skills_for_ai_agents_in_construction/telegram-field-bot"><img src="https://agentmods.dev/badge/skills/jdmorag97-rgb/ddc_skills_for_ai_agents_in_construction/telegram-field-bot.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00036 | $0.02156 |
| Opus 5.5 | $0.00014 | $0.00862 |
| Sonnet 5.5 | $0.00007 | $0.00431 |
| Haiku 4.5 | $0.00004 | $0.00216 |
Grade B, and why
telegram-field-bot scanned grade B with 2 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Sends data to an external URLmediumData exfiltration
A POST to an outside endpoint may be telemetry or may be exfiltration; either way the mod talks to somewhere, and you should know where.
# requests.post("https://n8n.company.com/webhook/photo-report", json=report) Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
# requests.post("https://n8n.company.com/webhook/photo-report", json=report) This is a copy
100% identical to telegram-field-bot — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 309 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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}}"
}
]
}
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 309 lines · 36 tokens per session scan B 42d6877a5e4a
telegram-field-bot is a skill published in the GitHub repository jdmorag97-rgb/DDC_Skills_for_AI_Agents_in_Construction (2 stars, last pushed 8mo ago), licensed MIT. It adds 36 tokens to every session and 2,156 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it B with 2 findings (sends data to an external url, makes network calls). It is 100% identical to telegram-field-bot, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
story-readiness
Checks whether a story is ready to implement: clear acceptance criteria, no open questions, valid ADR and dependencies. Use when the user asks if a story, or the sprint's stories, are ready to start or build.
recipe-create-meet-space
Create a Google Meet meeting space and share the join link.
workthreads
SpecStory Workthreads - a weekly work-thread rollup across a team's repos from SpecStory coding histories (any agent - Claude Code, Codex, Cursor, Gemini, and more). It groups the window's sessions into threads of work per project and labels each new / open / recently closed, so a lead sees what shipped, what is still…
atmos-config
Atmos root configuration: atmos.yaml discovery, precedence, deep merging, basepath, imports, minimal bootstrap, and routing to narrower Atmos skills.
qa-project-bootstrap
Onboard a new QA engineer to an existing codebase, or audit an existing test architecture. Produces a 30-day ramp plan: codebase orientation, framework walkthrough, test architecture audit, mentorship pairing, and first-test guidance. Use when: "QA onboarding," "new tester," "ramp up," "test architecture audit,"…
remove
Remove a deployed framework or addon from the current workspace.