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 security-review-constructiongit 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/security-review-construction)<a href="https://agentmods.dev/skills/jdmorag97-rgb/ddc_skills_for_ai_agents_in_construction/security-review-construction"><img src="https://agentmods.dev/badge/skills/jdmorag97-rgb/ddc_skills_for_ai_agents_in_construction/security-review-construction/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/security-review-construction"><img src="https://agentmods.dev/badge/skills/jdmorag97-rgb/ddc_skills_for_ai_agents_in_construction/security-review-construction.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 | $0.00029 | $0.02883 |
| Opus 5 | $0.00015 | $0.01442 |
| Sonnet 5 | $0.00006 | $0.00577 |
| Haiku 4.5 | $0.00003 | $0.00288 |
Grade A, and why
security-review-construction scanned grade A with 0 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 9d 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to security-review-construction — 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 — 406 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Security Review Skill for Construction Systems
This skill ensures all construction software systems follow security best practices, protecting sensitive project data, financial information, and business intelligence.
When to Activate
- Building ERP/BIM system integrations
- Creating construction dashboards
- Handling cost/financial data
- Building document management systems
- Creating APIs for field data collection
- Integrating with external platforms (Procore, PlanGrid, etc.)
- Working with subcontractor/vendor data
- Processing payment applications
Construction-Specific Security Concerns
1. Financial Data Protection
# CRITICAL: Construction financial data security
# ❌ NEVER Do This
project_budget = 15000000 # Hardcoded in source
margin_percentage = 0.18 # Business-sensitive info in code
# ✅ ALWAYS Do This
import os
from cryptography.fernet import Fernet
# Load from secure configuration
project_config = load_secure_config(os.environ['PROJECT_CONFIG_PATH'])
# Encrypt sensitive data at rest
def encrypt_financial_data(data: dict) -> bytes:
key = os.environ.get('ENCRYPTION_KEY')
f = Fernet(key)
return f.encrypt(json.dumps(data).encode())
Financial Data Checklist
- Cost estimates encrypted at rest
- Margin/markup data not exposed in logs
- Payment information tokenized
- Historical pricing protected from competitors
- Bid amounts secured until opening
2. BIM/CAD Data Security
# BIM data often contains proprietary design information
# ❌ NEVER store BIM directly in public cloud without encryption
s3.upload_file('model.ifc', bucket='public-bucket')
# ✅ ALWAYS encrypt and control access
def upload_bim_secure(file_path: str, project_id: str):
# Encrypt file
encrypted_path = encrypt_file(file_path)
# Generate pre-signed URL with expiration
presigned_url = s3.generate_presigned_url(
'get_object',
Params={
'Bucket': 'secure-bim-bucket',
'Key': f'{project_id}/{os.path.basename(file_path)}'
},
ExpiresIn=3600 # 1 hour expiration
)
# Log access
audit_log.info(f"BIM access granted: {project_id}")
return presigned_url
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.
- 9d ago First seen · 406 lines · 29 tokens per session scan A 4c21b3291620
security-review-construction is a skill published in the GitHub repository jdmorag97-rgb/DDC_Skills_for_AI_Agents_in_Construction (2 stars, last pushed 6mo ago), licensed MIT. It adds 29 tokens to every session and 2,883 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to security-review-construction, differing in 0 lines, and is treated as a copy.
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