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-daily-reportgit 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-daily-report)<a href="https://agentmods.dev/skills/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction/n8n-daily-report"><img src="https://agentmods.dev/badge/skills/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction/n8n-daily-report/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-daily-report"><img src="https://agentmods.dev/badge/skills/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction/n8n-daily-report.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
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 →
- medium Data Exfiltration · line 56 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 156 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 | $0.00020 | $0.01383 |
| Opus 5.5 | $0.00008 | $0.00553 |
| Sonnet 5.5 | $0.00004 | $0.00277 |
| Haiku 4.5 | $0.00002 | $0.00138 |
Grade A, and why
n8n-daily-report scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
response = requests.post(webhook_url, json=payload) Copies of this mod
1 near-identical copy found in the catalogue:
- n8n-daily-report — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 188 lines — stays where its author put it; the contents beside it link to each section on GitHub.
n8n Daily Report Automation
Business Case
Daily reports are critical but time-consuming. This n8n workflow automates collection of site data from multiple sources and generates formatted daily reports.
Workflow Overview
[Site Data Sources] → [n8n Webhook] → [Data Processing] → [Report Generation] → [Distribution]
n8n Workflow Configuration
1. Trigger Node: Schedule + Webhook
{
"nodes": [
{
"name": "Daily Schedule",
"type": "n8n-nodes-base.scheduleTrigger",
"parameters": {
"rule": {
"interval": [{"field": "cronExpression", "expression": "0 17 * * 1-5"}]
}
}
},
{
"name": "Webhook Input",
"type": "n8n-nodes-base.webhook",
"parameters": {
"httpMethod": "POST",
"path": "daily-report-data"
}
}
]
}
2. Data Collection Nodes
{
"nodes": [
{
"name": "Get Weather Data",
"type": "n8n-nodes-base.httpRequest",
"parameters": {
"url": "https://api.openweathermap.org/data/2.5/weather",
"qs": {
"lat": "={{$json.site_lat}}",
"lon": "={{$json.site_lon}}",
"appid": "={{$env.WEATHER_API_KEY}}"
}
}
},
{
"name": "Get Site Photos",
"type": "n8n-nodes-base.httpRequest",
"parameters": {
"url": "={{$env.PROCORE_API}}/projects/{{$json.project_id}}/images",
"authentication": "oAuth2"
}
},
{
"name": "Get Labor Data",
"type": "n8n-nodes-base.spreadsheetFile",
"parameters": {
"operation": "read",
"fileFormat": "xlsx"
}
}
]
}
3. Data Processing
{
"name": "Process Report Data",
"type": "n8n-nodes-base.code",
"parameters": {
"jsCode": "const items = $input.all();\n\nconst weather = items[0].json;\nconst photos = items[1].json;\nconst labor = items[2].json;\n\nconst report = {\n date: new Date().toISOString().split('T')[0],\n project: $('Webhook Input').first().json.project_name,\n weather: {\n condition: weather.weather[0].main,\n temp_high: Math.round(weather.main.temp_max - 273.15),\n temp_low: Math.round(weather.main.temp_min - 273.15)\n },\n labor_summary: {\n total_workers: labor.reduce((sum, l) => sum + l.workers, 0),\n total_hours: labor.reduce((sum, l) => sum + l.hours, 0)\n },\n photo_count: photos.length\n};\n\nreturn [{json: report}];"
}
}
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 · 188 lines · 20 tokens per session scan A 2a37dc7845c2
n8n-daily-report 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 20 tokens to every session and 1,383 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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