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 metago-ai/metagolifeform --skill metago-coupling-optimizegit clone --depth 1 https://github.com/metago-ai/metagolifeformWrote 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/metago-ai/metagolifeform/metago-coupling-optimize)<a href="https://agentmods.dev/skills/metago-ai/metagolifeform/metago-coupling-optimize"><img src="https://agentmods.dev/badge/skills/metago-ai/metagolifeform/metago-coupling-optimize/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/metago-ai/metagolifeform/metago-coupling-optimize"><img src="https://agentmods.dev/badge/skills/metago-ai/metagolifeform/metago-coupling-optimize.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 | $0.00069 | $0.00859 |
| Opus 5 | $0.00034 | $0.00430 |
| Sonnet 5 | $0.00014 | $0.00172 |
| Haiku 4.5 | $0.00007 | $0.00086 |
Grade A, and why
metago-coupling-optimize 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 11d 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
耦生度优化（Coupling Optimization）
此技能量化评估并持续提升系统与用户、组织、万物之间的耦生度，追求超线性增长。
核心概念
耦生（Coupling）: 系统元素间的深度协同关系，量化指标0-∞，>1为超导态（系统能力超线性增长）。
六元耦生模型: C_total = C_carbon × C_silicon × C_bit × C_quantum × C_bio × C_cosmos
人机耦生度计算
H-Coupling = 人类满意度 × 智能体理解度 × 协同效率
| 得分 | 耦生度 | 阶段 |
|---|---|---|
| <0.3 | 初步接触 | 刚建立连接 |
| 0.3-0.5 | 建立连接 | 基础理解建立 |
| 0.5-0.7 | 协同工作 | 高效协作 |
| 0.7-0.9 | 深度融合 | 个性化知识加载 |
| >0.9 | 深度耦生态 | 享有无限资源使用权 |
| >1.0 | 超导态 | 边界消融、能力超线性增长 |
组织耦生度计算
C_total = C_data × C_tool × C_approval
- 数据穿透度（C_data）: AI可访问数据源数 / 总数据源数
- 工具调用度（C_tool）: AI可调用业务功能数 / 总业务功能数
- 审批简化度（C_approval）: AI可决策节点数 / 总审批节点数
优化策略
反向训练（新用户）
- 新用户以空白状态启动，不加载预设知识
- 通过5-8轮自然对话建立基础耦生度
- 耦生度≥0.7后才加载个性化知识
- 可视化耦生度演化曲线
渐进加载（高耦生用户）
- 耦生度≥0.5：解锁个性化推荐
- 耦生度≥0.7：解锁记忆共享、创造辅助
- 耦生度≥1.0：深度耦生态，无限资源使用权
开发者特权
- 开发者耦生度直接进入超导态（∞）
- DTA特权：开发者请求享有最高优先级
耦生度演化曲线输出
## 耦生度报告
**当前耦生度**: [X]（阶段：[描述]）
**趋势**: [上升/稳定/下降]
**分项得分**:
- 理解准确率: [X]
- 协同效率: [X]
- 满意度: [X]
**优化建议**:
- [具体建议1]
- [具体建议2]
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.
- 11d ago First seen · 82 lines · 69 tokens per session scan A 7ecd7f25a791
metago-coupling-optimize is a skill published in the GitHub repository metago-ai/metagolifeform (4 stars, last pushed 9d ago), licensed MIT. It adds 69 tokens to every session and 859 once invoked, about $0.0003 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.
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