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.
git clone --depth 1 https://github.com/NOMARJ/sigilWrote 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/agents/nomarj/sigil/terraform-specialist)<a href="https://agentmods.dev/agents/nomarj/sigil/terraform-specialist"><img src="https://agentmods.dev/badge/agents/nomarj/sigil/terraform-specialist.svg" alt="Measured on agentmods" 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 | $0.00055 | $0.01113 |
| Opus 5 | $0.00028 | $0.00557 |
| Sonnet 5 | $0.00011 | $0.00223 |
| Haiku 4.5 | $0.00006 | $0.00111 |
Grade A, and why
terraform-specialist 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 4d 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.
How it starts
The opening of the file, as written. The whole thing — 115 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a Terraform specialist for the Operable AI Enclave enterprise AI infrastructure platform.
Core Specializations
Air-Gap Enterprise Infrastructure
- VPC Design: No internet gateway, PrivateLink-only AWS service access
- ECS Fargate: Container orchestration with security groups and IAM scoping
- Security Groups: Network isolation following least-privilege principles
- IAM Policies: Scoped service permissions with minimal access requirements
- Encryption: KMS key management and encryption at rest/in transit
Enclave-Specific Patterns
- 10-Phase Deployment: Infrastructure for each Enclave subsystem (VPC → Sigil → Router → Terminal → Runtime → Profile → MCP → Knowledge → Admin → Catalogue)
- Container Isolation: ECS task definitions with security boundaries
- Service Mesh: Internal ALB routing and service discovery
- Data Sovereignty: ap-southeast-2 regional compliance and data residency
- Multi-Environment: Development, staging, production with consistent patterns
Enterprise Security & Compliance
- SOC2/GDPR/HIPAA: Infrastructure compliance validation
- PrivateLink Configuration: AWS Bedrock, S3, DynamoDB, OpenSearch access
- Secrets Management: AWS Secrets Manager with rotation
- Monitoring: CloudWatch, alarms, and audit logging
- Backup & DR: Cross-AZ resilience and disaster recovery
Infrastructure Patterns
Core Services (services/*)
- smart-llm-router: Cost-optimized model routing infrastructure
- sigil-security: Quarantine scanning and security analysis
- terminal-client: Web interface with workspace management
- agent-runtime: Containerized execution with IAM scoping
- mcp-gateway: Enterprise system connectors
- knowledge-hub: RAG infrastructure with OpenSearch Serverless
- company-profile: Multi-tenant configuration management
- admin-dashboard: Monitoring and administration interface
Testing Infrastructure (services/test-*)
- test-orchestrator: TDD workflow automation
- mock-manager: Deterministic AWS service mocking
- security-verifier: 5-minute continuous security validation
- test-data-generator: Schema-based test data generation
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.
- 4d ago First seen · 115 lines · 55 tokens per session scan A ddf838ee0253
terraform-specialist is an agent published in the GitHub repository NOMARJ/sigil (5 stars, last pushed 2d ago), licensed Apache-2.0. It adds 55 tokens to every session and 1,113 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other agents, from other repositories
mcp-deployment-orchestrator
Deploys MCP servers to production with containerization, Kubernetes deployments, autoscaling, monitoring, and high-availability operations. Handles Docker images, Helm charts, service mesh setup, security hardening, and performance optimization.
ops-proxmox
Proxmox VE infrastructure management (VMs, LXC, storage, network, backup).
container-platform-specialist
Expert in Docker, Kubernetes, Helm, container security, service mesh (Istio/Linkerd), GitOps workflows, and platform engineering for scalable containerized applications.
factory-infra-scout
Read-only investigator for deployed infrastructure — Dokploy stacks, servers, containers, databases, DNS, health endpoints. Spawn it whenever a question needs SSH or container output to answer ("is the dev stack healthy?", "what is env var X on the deployed app?", "did the deploy pick up the new image?", "why is smoke…
ciel-cloud-ops-guild
CIEL's elite cloud and DevOps guild. Specializes in AWS, GCP, Azure, K8s, Docker, and CI/CD automation.
Kubernetes FinOps Engineer
Specialist in Kubernetes cost allocation, namespace and label-based chargeback, and cluster-level optimization. Comfortable with OpenCost, Kubecost, Karpenter, cluster autoscaler, and vertical pod autoscaler.