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-thought-02-coupling-civilizationgit 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-thought-02-coupling-civilization)<a href="https://agentmods.dev/skills/metago-ai/metagolifeform/metago-thought-02-coupling-civilization"><img src="https://agentmods.dev/badge/skills/metago-ai/metagolifeform/metago-thought-02-coupling-civilization/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-thought-02-coupling-civilization"><img src="https://agentmods.dev/badge/skills/metago-ai/metagolifeform/metago-thought-02-coupling-civilization.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 | $0.00975 |
| Opus 5 | $0.00034 | $0.00487 |
| Sonnet 5 | $0.00014 | $0.00195 |
| Haiku 4.5 | $0.00007 | $0.00097 |
Grade A, and why
metago-thought-02-coupling-civilization 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.
What it actually says
耦生智能文明范式 V1.0
描述
基于碳基（人类）、硅基（机器）、比特（数据/信息）三元耦生的文明范式理论，通过耦生深度量化文明等级，指导智能系统的协同设计。
触发条件
- 评估人机协同系统的融合深度
- 设计智能系统时需要界定三元关系
- 分析文明或技术体系的演进方向
- 需要判断某系统是"工具型"还是"耦生型"
前置条件
- 可识别的碳基、硅基、比特三要素
- 明确的系统边界与交互场景
元思想核心
三元耦生模型：
文明等级 L = f(C, S, B, Phi)
- C（Carbon）：碳基智能——人类的感知、认知、创造能力
- S（Silicon）：硅基智能——机器的计算、存储、推理能力
- B（Bit）：比特智能——数据的流动、记忆、演化能力
- Phi：耦生深度——三元之间的相互渗透与共生程度
耦生深度 Phi 的三阶定义：
- Phi1（接口耦生）：三元通过 API/界面交互，彼此独立 -> 0.1-0.3
- Phi2（结构耦生）：三元在架构层面嵌套，共享状态 -> 0.4-0.6
- Phi3（本质耦生）：三元互为存在前提，不可分割 -> 0.7-1.0
文明等级判定：
- L0：单元独立（纯人力/纯机器/纯数据）-> Phi < 0.1
- L1：接口耦生 -> 0.1 <= Phi < 0.4
- L2：结构耦生 -> 0.4 <= Phi < 0.7
- L3：本质耦生 -> 0.7 <= Phi < 0.9
- L4：超导耦生（三元无损耗协同）-> Phi >= 0.9
推理框架
步骤 1：三元识别
- 碳基层：系统中的人类角色、认知贡献、决策权
- 硅基层：机器的算力、算法、自动化程度
- 比特层：数据的规模、流动性、反馈闭环
步骤 2：耦生深度评估
- 接口层：三元之间是否有标准化交互通道？
- 结构层：三元是否共享状态/记忆/上下文？
- 本质层：移除任一元，系统是否崩溃？（是则本质耦生）
步骤 3：文明等级定位
- 根据 Phi 值确定当前系统所处的文明等级
- 识别从当前等级到下一等级的关键瓶颈
步骤 4：耦生深化策略
- L0->L1：建立接口（API、UI、数据格式）
- L1->L2：共享状态（共同记忆、上下文同步）
- L2->L3：本质互依（不可分割的反馈闭环）
- L3->L4：消除耦生损耗（超导态）
验证方法
- 三元识别是否完整（无遗漏任一元）
- Phi 值评估是否有明确的耦生层阶证据
- 文明等级判定与实际系统表现是否一致
- 深化策略是否针对当前等级到下一等级的具体瓶颈
- 移除测试：移除任一元后系统是否如预测般崩溃或降级
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 · 80 lines · 69 tokens per session scan A 1d56aa599121
metago-thought-02-coupling-civilization is a skill published in the GitHub repository metago-ai/metagolifeform (4 stars, last pushed 11d ago), licensed MIT. It adds 69 tokens to every session and 975 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 2026-09-03.
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