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-12-agentive-osgit 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-12-agentive-os)<a href="https://agentmods.dev/skills/metago-ai/metagolifeform/metago-thought-12-agentive-os"><img src="https://agentmods.dev/badge/skills/metago-ai/metagolifeform/metago-thought-12-agentive-os/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-12-agentive-os"><img src="https://agentmods.dev/badge/skills/metago-ai/metagolifeform/metago-thought-12-agentive-os.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 | $0.00057 | $0.00909 |
| Opus 5.5 | $0.00023 | $0.00364 |
| Sonnet 5.5 | $0.00011 | $0.00182 |
| Haiku 4.5 | $0.00006 | $0.00091 |
Grade A, and why
metago-thought-12-agentive-os 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
Agentive OS 元思想 V32.0
描述
将操作系统重新定义为智能体——OS 不再是被动资源管理者，而是主动的智能体，通过评估 OS 的智能化程度，指导下一代操作系统的架构设计。
触发条件
- 评估操作系统的智能化程度
- 设计智能操作系统架构
- 对比传统 OS 与智能 OS
- 操作系统级别的 AI 集成
前置条件
- 明确的操作系统或 OS 级平台
- 可识别的资源管理与调度机制
元思想核心
核心命题：
OS = Agent
操作系统不再是资源管理者，而是智能体
Agentive OS 五特征：
| 特征 | 传统 OS | Agentive OS | 评估维度 |
|---|---|---|---|
| 主动性 | 被动响应请求 | 主动预测与优化 | Proactivity |
| 感知力 | 无环境感知 | 感知用户/硬件/网络状态 | Perception |
| 决策力 | 规则调度 | 基于世界模型的智能决策 | Decision |
| 学习力 | 无学习 | 从使用模式中学习优化 | Learning |
| 交互力 | 命令行/API | 自然语言/多模态交互 | Interaction |
Agentive 度公式：
A = (Proactivity + Perception + Decision + Learning + Interaction) / 5
Agentive 度判定：
- A >= 0.8：强 Agentive OS
- 0.5 <= A < 0.8：过渡型 OS
- A < 0.5：传统 OS
OS-Agent 融合三阶：
- 一阶（OS with Agent）：OS 内嵌 AI 助手（如 Copilot）-> A 0.2-0.4
- 二阶（OS as Agent）：OS 核心功能由 Agent 驱动 -> A 0.5-0.7
- 三阶（OS = Agent）：OS 本质就是 Agent -> A 0.8-1.0
推理框架
步骤 1：五特征评估（0-1 分）
- Proactivity：OS 是否主动预测用户需求？
- Perception：OS 是否感知环境状态？
- Decision：OS 调度是否基于智能决策？
- Learning：OS 是否从使用中学习？
- Interaction：OS 交互是否支持自然语言/多模态？
步骤 2：Agentive 度计算
- A = 五维均值
- 判定 OS 类型
步骤 3：融合阶次判定
- 一阶：AI 作为 OS 的附属工具
- 二阶：AI 驱动 OS 的核心功能
- 三阶：OS 与 AI 本质合一
步骤 4：架构差距分析
- 识别从当前阶次到下一阶次的差距
- 分析每个差距的技术可行性
步骤 5：演进路线设计
- 短期：提升最低维度
- 中期：跨越融合阶次
- 长期：达到 OS = Agent
验证方法
- 五特征评估是否有 OS 架构层面的证据
- A 值计算是否正确
- 融合阶次判定是否与实际 OS 行为一致
- 演进路线是否可行（非空中楼阁）
- 用用户场景测试：用户需求是否由 OS 主动满足（而非用户主动操作）
- 用性能指标验证：Agentive 特性是否带来实际效率提升
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 · 95 lines · 57 tokens per session scan A 98ac4ad50776
metago-thought-12-agentive-os is a skill published in the GitHub repository metago-ai/metagolifeform (5 stars, last pushed today), licensed MIT. It adds 57 tokens to every session and 909 once invoked, about $0.0002 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 2026-09-03.
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