settings-and-env

A reference for configuring the application through environment variables, which are settings supplied outside the source code. It lists values for security, the database, Redis, and language-model providers.

In plain words
What is it for?
Use it to prepare a local or production environment, set database and cache connections, configure authentication and encryption, and choose language-model backends.
Why use it?
It keeps secrets and deployment-specific settings out of the code and makes required production configuration explicit.

Cursor rule for Claude Code

Install

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.

agentmods
npx agentmods add rules/eliornl/rolemule/settings-and-env
Clone the repo
git clone --depth 1 https://github.com/eliornl/rolemule

Made for: Claude Code.

Per session 0 Nothing until a file matches its globs; then the whole rule loads.
When invoked 2,307 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00000 $0.02307
Opus 5 $0.00000 $0.01154
Sonnet 5 $0.00000 $0.00461
Haiku 4.5 $0.00000 $0.00231

Measured 2d ago against content hash 0d70d64a4fc6, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

settings-and-env 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 2d 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.

.claude/rules/settings-and-env.mdc · 206 lines

How it starts

The opening of the file, as written. The whole thing — 206 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Settings & Environment Variables

Complete .env Reference

# App
APP_NAME=RoleMule
DEBUG=false
BASE_URL=https://yourdomain.com  # Used in password-reset and verification emails
ALLOWED_HOSTS=yourdomain.com,www.yourdomain.com

# Security
JWT_SECRET=<32+ char, 3 char types min>
# Generate: python -c "import secrets; print(secrets.token_urlsafe(48))"
JWT_EXPIRATION_HOURS=24
BCRYPT_ROUNDS=12

# Encryption key for stored BYOK API keys (REQUIRED in production)
# Must be set BEFORE the first JWT_SECRET rotation to avoid losing stored keys.
# Generate: python -c "from cryptography.fernet import Fernet; print(Fernet.generate_key().decode())"
ENCRYPTION_KEY=<Fernet base64url key>

# Database
DATABASE_URL=postgresql+asyncpg://user:pass@host:5432/dbname

# Redis
REDIS_URL=redis://localhost:6379/0

# LLM — provider selection (health/admin fallback; users pick via Settings BYOK)
# LLM_PROVIDER=gemini   # gemini | openai | anthropic | ollama
# Optional server-side Gemini key (health/admin only under per-user BYOK)
# GEMINI_API_KEY=<your Gemini API key>
GEMINI_MODEL=gemini-3.5-flash

# LLM — Vertex AI (optional Gemini backend, server-admin only — skips user BYOK)
# USE_VERTEX_AI=true
# VERTEX_AI_PROJECT=your-gcp-project
# IMPORTANT: gemini-3-* models ONLY work with VERTEX_AI_LOCATION=global
# VERTEX_AI_LOCATION=global

# LLM — OpenAI (user BYOK in Settings; server key for health/admin)
# OPENAI_API_KEY=
# OPENAI_MODEL=gpt-5.6-luna

# LLM — Anthropic (user BYOK in Settings; server key for health/admin)
# ANTHROPIC_API_KEY=
# ANTHROPIC_MODEL=claude-sonnet-5

# LLM — Ollama local/self-hosted (preferred_provider=ollama needs no user key)
# OLLAMA_BASE_URL=http://127.0.0.1:11434
# OLLAMA_MODEL=qwen3.6

# Google OAuth (optional)
GOOGLE_CLIENT_ID=xxx.apps.googleusercontent.com
GOOGLE_CLIENT_SECRET=GOCSPX-xxx

# Email (Gmail SMTP)
SMTP_HOST=smtp.gmail.com
SMTP_PORT=587
[email protected]
SMTP_PASSWORD=<App Password>
[email protected]
SMTP_FROM_NAME=RoleMule

# Analytics (optional — banner is hidden when POSTHOG_ENABLED=false)
POSTHOG_API_KEY=phc_xxx
POSTHOG_HOST=https://us.i.posthog.com
POSTHOG_ENABLED=false

# Security contact for /.well-known/security.txt (RFC 9116)
# Defaults to security@<BASE_URL domain> when not set.
# [email protected]

# Self-hosted flags
# Skip email verification — users auto-verified on registration.
# Required when SMTP is not configured. NOT safe for public multi-user deployments.
# DISABLE_EMAIL_VERIFICATION=true

# Logging
LOG_LEVEL=INFO
LOG_FORMAT=json    # always respected — not overridden by DEBUG mode
LOG_DIR=logs
LOG_FILE_ENABLED=true

Read the full file on GitHub · 206 lines

Changes

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.

  1. 2d ago First seen · 206 lines · 0 tokens per session scan A 0d70d64a4fc6

Subscribe to this mod's changes

settings-and-env is a cursor rule published in the GitHub repository eliornl/rolemule (37 stars, last pushed 2d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 2,307 tokens. 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 2026-08-30.

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