ai-dev-os-init

A setup wizard for AI Dev OS, a project structure for organizing instructions given to coding agents. It asks about the technology and project size, then creates the matching rule layers.

In plain words
What is it for?
Use it when starting a project or introducing AI Dev OS to import existing rules and generate project guidance for coding, formatting, linting, and delivery.
Why use it?
It avoids designing the instruction structure from scratch and helps bring existing project rules into one organized system. It can inspect files such as AGENTS.md, editor settings, lint rules, and CI configuration.

Cursor rule

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/yunbow/ai-dev-os-plugin-cursor/ai-dev-os-init
Clone the repo
git clone --depth 1 https://github.com/yunbow/ai-dev-os-plugin-cursor
Per session 40 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 682 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 $0.00040 $0.00682
Opus 5 $0.00020 $0.00341
Sonnet 5 $0.00008 $0.00136
Haiku 4.5 $0.00004 $0.00068

Measured 2d ago against content hash 0be7381e976a, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

ai-dev-os-init 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.

rules/ai-dev-os-init.mdc · 76 lines

How it starts

The opening of the file, as written. The whole thing — 76 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AI Dev OS Setup Wizard

Execution Flow

1. Interview the User

  • Tech stack (Next.js / Python / Go / etc.)
  • Project scale (personal / team / enterprise)
  • Existing rule files (.cursorrules, CLAUDE.md, .kiro/steering/, etc.)

2. Detect and Import Existing Rules

Scan the project for existing configuration and rule files:

Source Action
.cursorrules Classify into L3-L4
Existing CLAUDE.md Convert to L3 guidelines
Existing AGENTS.md Classify into L3-L4
.editorconfig Import formatting rules into L3 common/code.md
.eslintrc / eslint.config.* Extract coding rules into L3 guidelines
biome.json / biome.jsonc Extract lint/format rules into L3 guidelines
ruff.toml / pyproject.toml [tool.ruff] Extract Python lint rules into L3 guidelines
.prettierrc / prettier.config.* Import formatting config into L3 common/code.md
tsconfig.json (strict settings) Reference in L3 common/code.md
.github/workflows/*.yml Reference CI/CD patterns in L3 common/cicd.md
Existing .cursor/rules/ Merge with AI Dev OS structure

For each detected file:

  1. Read its content
  2. Extract rules that map to AI Dev OS guideline categories
  3. Present the extracted rules to the user for confirmation
  4. Write confirmed rules into the appropriate L3 guideline files

3. Generate Templates

Generate the following structure:

ai-dev-os/
├── 01_philosophy/
│   └── core-values.md          # Minimal placeholder
├── 02_decision-criteria/
│   └── coding.md               # 5-10 basic principles
├── 03_guidelines/
│   ├── common/
│   │   ├── code.md             # Basic rules based on tech stack
│   │   ├── naming.md
│   │   └── security.md
│   └── frameworks/
│       └── [selected-stack]/
│           └── overview.md
└── 04_ai-frames/
    └── cursor.md               # Cursor-specific configuration

4. Generate .cursorrules

  • Auto-insert references to the ai-dev-os directory
  • Set up Specificity Cascade

Read the full file on GitHub · 76 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 · 76 lines · 40 tokens per session scan A 0be7381e976a

Subscribe to this mod's changes

ai-dev-os-init is a cursor rule published in the GitHub repository yunbow/ai-dev-os-plugin-cursor (2 stars, last pushed 5mo ago), licensed MIT. It adds 40 tokens to every session and 682 once invoked, about $0.0002 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 2026-08-31.