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 agentmods add commands/matteocervelli/llms/infrastructure-setupgit clone --depth 1 https://github.com/matteocervelli/llmsWhat 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 | $0.00008 | $0.01317 |
| Opus 5 | $0.00004 | $0.00659 |
| Sonnet 5 | $0.00002 | $0.00263 |
| Haiku 4.5 | $0.00001 | $0.00132 |
Grade A, and why
infrastructure-setup 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 yesterday.
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 — 261 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Infrastructure Setup: $ARGUMENTS
💡 Tip: For safer planning, activate Plan Mode (press Shift+Tab twice) before running this command to review the infrastructure strategy before execution.
Architecture Implementation
!git checkout -b infrastructure/setup
Use sequential-thinking-mcp to plan infrastructure based on @TECH-STACK.md requirements.
Create modular code structure:
src/
├── interfaces/ # Contracts and types
├── core/ # Business logic
├── implementations/ # Concrete implementations
├── middleware/ # Security, logging, validation
├── config/ # Environment configuration
└── utils/ # Shared utilities
Database & Persistence
Schema Design
- Create migration files with proper indexing
- Implement connection pooling and query optimization
- Add database health checks and monitoring
ORM/Database Layer
TypeScript + Prisma:
!npx prisma init
# Configure schema with security constraints
!npx prisma migrate dev --name init
Python + SQLAlchemy:
!alembic init alembic
!alembic revision --autogenerate -m "Initial migration"
API & Security Layer
Authentication & Authorization
- Implement JWT/session-based auth
- Add role-based access control (RBAC)
- Configure password hashing and validation
- Setup rate limiting and request validation
Security Middleware
- Input sanitization and validation
- Security headers (CORS, CSP, HSTS)
- API rate limiting and throttling
- Request/response logging for audit
Input Validation
TypeScript + Zod:
// Schemas with security validation
export const CreateUserSchema = z.object({
email: z.string().email().max(255),
name: z.string().min(2).max(100).regex(/^[a-zA-Z\s]+$/),
});
Python + Pydantic:
# Type-safe validation with security
class UserCreate(BaseModel):
email: EmailStr
name: str = Field(..., min_length=2, max_length=100)
Performance & Caching
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.
- yesterday First seen · 261 lines · 8 tokens per session scan A 2b0ad729f213
infrastructure-setup is a command published in the GitHub repository matteocervelli/llms (25 stars, last pushed 3mo ago), licensed MIT. It adds 8 tokens to every session and 1,317 once invoked, about $0.0000 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 2026-09-01.
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