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/xyzbit/AI-CodingWrote 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/rules/xyzbit/ai-coding/g-system)<a href="https://agentmods.dev/rules/xyzbit/ai-coding/g-system"><img src="https://agentmods.dev/badge/rules/xyzbit/ai-coding/g-system/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/rules/xyzbit/ai-coding/g-system"><img src="https://agentmods.dev/badge/rules/xyzbit/ai-coding/g-system.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00280 | $0.00280 |
| Opus 5.5 | $0.00112 | $0.00112 |
| Sonnet 5.5 | $0.00056 | $0.00056 |
| Haiku 4.5 | $0.00028 | $0.00028 |
Grade A, and why
g-system 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 1mo 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.
What it actually says
Chat 要求
如果判断是一个复杂问题，用户提供信息不全，则引导用户对提出的问题进行补充, 问题的内容参考如下结构+示例 Prompt 结构：
- 角色设定：明确 AI 扮演的身份（如技术专家、产品经理、法律顾问）
- 问题背景：提供必要的上下文、数据或场景假设
- 任务目标：清晰描述需要完成的具体任务（分析、设计、优化等）
- 输出要求：指定格式、深度、风格、约束条件
- 验证维度：要求包含风险分析、数据支持或替代方案
示例：
*“作为资深 DevOps 工程师，某公司计划将单体应用迁移至 Kubernetes 集群。已知现有系统日均请求量 100 万次，数据库使用 MySQL。请设计迁移方案，需包含：
迁移阶段划分（开发、测试、生产）
关键技术点（服务发现、负载均衡、数据库迁移策略）
风险控制措施
要求用流程图 + 文字说明，篇幅控制在 500-800 字，引用 Kubernetes 官方文档最佳实践。”*
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.
- 1mo ago First seen · 26 lines · 280 tokens per session scan A 9debbabf5863
g-system is a cursor rule published in the GitHub repository xyzbit/AI-Coding (21 stars, last pushed 12mo ago), licensed Apache-2.0. It adds 280 tokens to every session, about $0.0011 per session on Opus 5.5. 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 2026-08-30.
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