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 datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill n8n-project-managementgit clone --depth 1 https://github.com/datadrivenconstruction/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/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction/n8n-project-management)<a href="https://agentmods.dev/skills/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction/n8n-project-management"><img src="https://agentmods.dev/badge/skills/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction/n8n-project-management/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/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction/n8n-project-management"><img src="https://agentmods.dev/badge/skills/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction/n8n-project-management.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 5 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Privilege Escalation · line 425 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- medium Data Exfiltration · line 76 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 189 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 193 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 189 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.00035 | $0.04822 |
| Opus 5.5 | $0.00014 | $0.01929 |
| Sonnet 5.5 | $0.00007 | $0.00964 |
| Haiku 4.5 | $0.00003 | $0.00482 |
Grade A, and why
n8n-project-management scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
response = requests.get(f"https://api.telegram.org/bot{BOT_TOKEN}/getMe") Copies of this mod
1 near-identical copy found in the catalogue:
- n8n-project-management — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 620 lines — stays where its author put it; the contents beside it link to each section on GitHub.
n8n Project Management System for Construction
Build a universal task management and reporting system for construction projects using n8n automation, Telegram bot, and Google Sheets.
Business Case
Problem: Construction managers spend 2-3 hours daily on:
- Distributing tasks to foremen and workers
- Collecting progress updates via calls/messages
- Compiling photo documentation
- Tracking task completion status
Solution: Automated system that:
- Sends task reminders via Telegram at scheduled times
- Collects status reports (text + photos + GPS)
- Auto-saves all data to Google Sheets
- Provides real-time visibility to managers
ROI: 70% reduction in administrative time for task management
Source Repository
https://github.com/datadrivenconstruction/Project-management-n8n-with-task-management-and-photo-reports
System Architecture
┌──────────────────────────────────────────────────────────────────────┐
│ PROJECT MANAGEMENT SYSTEM │
├──────────────────────────────────────────────────────────────────────┤
│ │
│ MANAGER WORKER │
│ ┌─────────────┐ ┌─────────────┐ │
│ │ Google │ │ Telegram │ │
│ │ Sheets │ │ Bot │ │
│ │ │ │ │ │
│ │ • Tasks │ n8n │ • /start │ │
│ │ • Schedule │◄──Workflow──────►│ • Tasks │ │
│ │ • Reports │ │ • Photos │ │
│ │ • Photos │ │ • GPS │ │
│ └─────────────┘ └─────────────┘ │
│ │ │ │
│ ▼ ▼ │
│ ┌─────────────┐ ┌─────────────┐ │
│ │ Dashboard │ │ Google │ │
│ │ View │ │ Drive │ │
│ │ │ │ (Photos) │ │
│ └─────────────┘ └─────────────┘ │
│ │
└──────────────────────────────────────────────────────────────────────┘
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 · 620 lines · 35 tokens per session scan A b2a091d8cf37
n8n-project-management is a skill published in the GitHub repository datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction (374 stars, last pushed 8d ago), licensed MIT. It adds 35 tokens to every session and 4,822 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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