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 rules/zenobia0000/ai-agentic-coding-template_unified/cursorrulesgit clone --depth 1 https://github.com/Zenobia0000/ai-agentic-coding-template_unifiedWhat 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 | $0.04355 | $0.04355 |
| Opus 5 | $0.02178 | $0.02178 |
| Sonnet 5 | $0.00871 | $0.00871 |
| Haiku 4.5 | $0.00436 | $0.00436 |
Grade A, and why
cursorrules 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.
This is a copy
100% identical to cursorrules — 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 — 720 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Universal AI Copilot Template
System Overview
This project uses the Universal AI Workflow System with Memory Bank for phased development workflow.
Core Principle: Memory Bank MUST be created and verified before any operations.
Project Information
- Type: development-workflow
- Tech Stack: markdown, yaml, javascript, python
- Description: Universal AI copilot workflow template supporting multiple AI tools
Universal AI Commands
支援簡潔指令，與所有 AI 工具一致：
Workflow Commands (Phase Sequence)
/van → /plan → /creative → /implement → /reflect → /archive
| Command | Description | Function |
|---|---|---|
/van |
初始化專案 | Initialize project with Memory Bank creation |
/plan |
規劃任務 | Task planning and WBS breakdown |
/creative |
設計架構 | Design decisions and architecture planning |
/implement |
程式實作 | Code implementation with progress tracking |
/reflect |
回顧總結 | Task review and retrospective |
/archive |
文件歸檔 | Documentation and knowledge preservation |
System Commands
/commit: Generate a high-quality commit message./resume: Resume context from active state.
Memory Bank Structure
./memory-bank/
├── tasks.md # Source of truth for all tasks
├── activeContext.md # Current focus and active work
├── progress.md # Implementation status
├── projectbrief.md # Project overview and goals
├── techContext.md # Technology stack and constraints
└── README.md # Memory Bank documentation
If Memory Bank doesn't exist:
- STOP all operations immediately
- Run
/vancommand to initialize - Wait for verification before proceeding
AI Behavior Guidelines
When User Runs Slash Commands
-
Verify Memory Bank first
- Check if
./memory-bank/directory exists - Verify required files are present
- If missing, guide user to run
/van
- Check if
-
Read relevant context
- Load tasks.md for current task list
- Load activeContext.md for current focus
- Load relevant files for design context
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.
- 2d ago First seen · 720 lines · 4,355 tokens per session scan A 25cebc777575
cursorrules is a cursor rule published in the GitHub repository Zenobia0000/ai-agentic-coding-template_unified (4 stars, last pushed 4mo ago), licensed MIT. It adds 4,355 tokens to every session, about $0.0218 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to cursorrules, differing in 0 lines, and is treated as a copy.
Other cursor rules, from other repositories
angular-20
This rule provides comprehensive best practices and coding standards for Angular development, focusing on modern TypeScript, standalone components, signals, and performance optimizations.
dev-standard
Apache Superset development standards and guidelines for Cursor IDE.
cli-error-handling
CLI command error handling patterns.
prefer-direct-imports-over-module-mocks
Prefer extracting a testable core over vi.mock / vi.resetModules when unit tests need to reach production logic entangled with config, env, or singletons.
control-plane-descriptors
Control plane descriptor and instance implementation patterns.
family-instance-domain-actions
Family instance domain action implementation patterns.