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 skills add duolongworld/AI_Renaissance --skill layer2_cycle_positioninggit clone --depth 1 https://github.com/duolongworld/AI_RenaissanceWrote 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/skills/duolongworld/ai_renaissance/layer2_cycle_positioning)<a href="https://agentmods.dev/skills/duolongworld/ai_renaissance/layer2_cycle_positioning"><img src="https://agentmods.dev/badge/skills/duolongworld/ai_renaissance/layer2_cycle_positioning/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/skills/duolongworld/ai_renaissance/layer2_cycle_positioning"><img src="https://agentmods.dev/badge/skills/duolongworld/ai_renaissance/layer2_cycle_positioning.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00040 | $0.02039 |
| Opus 5 | $0.00020 | $0.01019 |
| Sonnet 5 | $0.00008 | $0.00408 |
| Haiku 4.5 | $0.00004 | $0.00204 |
Grade A, and why
layer2_cycle_positioning 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 9d 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.
How it starts
The opening of the file, as written. The whole thing — 179 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Layer 2: 周期定位——4象限 + 政策维度 + 长期债务周期
执行方式
- 数值计算（Z1-Z4分数计算）
- 智能分析（LLM判断4象限定位）
- 混合模式（数值计算 + LLM智能判断）
说明：本层采用混合模式：
- 数值计算：CAI/FCI分数计算、4象限判定、政策得分计算
- 智能分析：政策意图解读、中美周期一致性判断、长期债务周期定位
适用范围
根据 Layer 1 的 CAI/FCI 输出，将中美经济定位到美林时钟4象限，结合政策维度和长期债务周期，为 Layer 5 资产配置提供周期定位。
输入数据规范
必填数据（来自 Layer 1）
| 数据项 | 来源 | 字段名 | 说明 |
|---|---|---|---|
| 中国CAI z-score | Layer 1 | china_cai.z_score | |
| 中国通胀得分 z-score | Layer 1 | china_inflation.z_score | |
| 美国CAI z-score | Layer 1 | us_cai.z_score | |
| 美国通胀得分 z-score | Layer 1 | us_inflation.z_score |
可选数据（需额外获取）
| 数据项 | 来源 | 用途 |
|---|---|---|
| 货币政策信号 | 央行公告 | 政策维度评估 |
| 财政政策信号 | 财政部公告 | 政策维度评估 |
| 地产政策信号 | 住建部/央行 | 政策维度评估 |
| 监管事件 | 监管部门 | 政策维度评估 |
| 联邦债务/GDP | 财政部 | 美国长期债务周期 |
| 中国宏观杠杆率 | BIS | 中国长期债务周期 |
分析步骤
Step 1: 确定中国4象限
根据中国CAI和通胀得分，定位到4象限之一：
| 象限 | 条件 | CAI | 通胀 | 含义 |
|---|---|---|---|---|
| 复苏 | CAI > 0, 通胀下行/中性 | 正值 | ≤ 0 | 经济回升、通胀温和 |
| 过热 | CAI > 0, 通胀上行 | 正值 | > 0 | 经济强劲、通胀上行 |
| 滞胀 | CAI < 0, 通胀上行 | 负值 | > 0 | 经济疲弱、通胀高企 |
| 衰退 | CAI < 0, 通胀下行/中性 | 负值 | ≤ 0 | 经济衰退、通胀下行 |
Step 2: 确定美国4象限
同上，根据美国CAI和通胀得分定位。
Step 3: 计算政策维度得分
| 政策维度 | 权重 | 评分规则 |
|---|---|---|
| 货币政策 | 0.40 | DR007 vs 政策利率、MLF/LPR调整、降准等 |
| 财政政策 | 0.30 | 专项债发行进度、财政赤字率、特别国债 |
| 地产政策 | 0.25 | 限购/限贷/首付/利率政策松紧 |
| 监管事件 | 0.05 | 资本市场政策、行业监管方向 |
评分：
- 宽松: +1
- 中性: 0
- 收紧: -1
综合得分 = Σ(各维度得分 × 权重)
Step 4: 应用政策调节
| 政策综合得分 | 调节规则 |
|---|---|
| > +0.5 | 4象限受益资产信号强度+1档 |
| < -0.5 | 4象限受益资产信号强度-1档 |
| ±0.5之间 | 不做幅度调节 |
Step 5: 确定长期债务周期位置
| 周期位置 | 美国特征 | 中国特征 |
|---|---|---|
| 早期/上行 | 债务/GDP比率较低，利率低位 | 宏观杠杆率上升初期 |
| 中段/稳定 | 债务/GDP比率中等 | 宏观杠杆率稳定 |
| 末端/下行 | 债务/GDP比率>120%，利率高位 | 宏观杠杆率高企，信用收缩 |
| 特殊 | 利差倒挂持续6个月+ | 社融同比<8% |
Step 6: 周期一致性校验
| 规则 | 处理方式 |
|---|---|
| 全球周期优先 | 中美分歧时，以美国周期定大方向 |
| 恐慌状态直接下调 | 全球风险触发恐慌时，下调至观望/看空 |
| 中美严重分化 | 仅输出结构性信号，不输出全面看涨/看空 |
判断规则
4象限与资产映射
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 9d ago First seen · 179 lines · 40 tokens per session scan A dbaa132fa93a
layer2_cycle_positioning is a skill published in the GitHub repository duolongworld/AI_Renaissance (59 stars, last pushed 12d ago), licensed Apache-2.0. It adds 40 tokens to every session and 2,039 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 2026-08-30.
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