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-measuregit 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-measure)<a href="https://agentmods.dev/skills/metago-ai/metagolifeform/metago-coupling-measure"><img src="https://agentmods.dev/badge/skills/metago-ai/metagolifeform/metago-coupling-measure/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-measure"><img src="https://agentmods.dev/badge/skills/metago-ai/metagolifeform/metago-coupling-measure.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 | $0.00034 | $0.01515 |
| Opus 5 | $0.00017 | $0.00758 |
| Sonnet 5 | $0.00007 | $0.00303 |
| Haiku 4.5 | $0.00003 | $0.00152 |
Grade A, and why
metago-coupling-measure 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 12d 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 — 127 lines — stays where its author put it; the contents beside it link to each section on GitHub.
耦生度计算
触发条件
当用户提到以下关键词或场景时触发本技能：
- "耦生度"、"耦合度"、"三元耦合"
- 数字化转型评估
- 智能化水平评估
- 耦生度优化
- 三元融合度诊断
适用场景
- 数字化转型成熟度评估
- 智能化水平量化评估
- 耦生度优化路径设计
- 三元融合度诊断
- 系统集成度评估
- 组织数字化能力评估
执行步骤
-
碳基耦合度评估（C_carbon）：
- 人员数字素养：组织成员的数字化能力与意识
- 组织敏捷度：组织响应变化的灵活程度
- 决策数字化：决策过程的数字化支撑程度
- 协作数字化：协作方式的数字化程度
- 计算公式：C_carbon = (各子项得分平均值) / 10，取值范围 0~1
-
硅基耦合度评估（C_silicon）：
- 系统互操作性：系统间互联互通能力
- 数据流通度：数据在系统间的流通顺畅度
- 架构弹性：技术架构的可扩展性
- 接口标准化：接口规范的统一程度
- 计算公式：C_silicon = (各子项得分平均值) / 10，取值范围 0~1
-
比特耦合度评估（C_bit）：
- 数据质量：数据的准确性、完整性、一致性
- 信息透明度：信息对相关方的可见程度
- 数据资产化：数据作为资产的管理程度
- 知识图谱化：知识结构化与关联程度
- 计算公式：C_bit = (各子项得分平均值) / 10，取值范围 0~1
-
总耦生度计算：
- 公式：C_total = C_carbon × C_silicon × C_bit
- 范围：0 ~ 1（归一化）
- 注意：任一元为0则总耦生度为0（木桶效应），三元乘法关系决定了一元短板会显著拉低总耦合度
-
耦生度分级：
- Lv0 孤立（C_total < 0.1）：三元各自为政，无有效协作，数字化尚未起步
- Lv1 连接（0.1 ≤ C_total < 0.3）：三元有初步连接，但协作有限，处于数字化早期
- Lv2 协作（0.3 ≤ C_total < 0.6）：三元有效协作，但未达共生，处于数字化深化期
- Lv3 共生（C_total ≥ 0.6）：三元深度融合，相互增强，达到智能化共生态
-
输出耦生度报告+优化路径
输出格式
耦生度评估报告
一、碳基耦合度（C_carbon）
| 评估子项 | 得分(0-10) | 说明 |
|---|---|---|
| 人员数字素养 | x | ... |
| 组织敏捷度 | x | ... |
| 决策数字化 | x | ... |
| 协作数字化 | x | ... |
C_carbon = x.xx
二、硅基耦合度（C_silicon）
| 评估子项 | 得分(0-10) | 说明 |
|---|---|---|
| 系统互操作性 | x | ... |
| 数据流通度 | x | ... |
| 架构弹性 | x | ... |
| 接口标准化 | x | ... |
C_silicon = x.xx
三、比特耦合度（C_bit）
| 评估子项 | 得分(0-10) | 说明 |
|---|---|---|
| 数据质量 | x | ... |
| 信息透明度 | x | ... |
| 数据资产化 | x | ... |
| 知识图谱化 | x | ... |
C_bit = x.xx
四、总耦生度
- C_total = C_carbon × C_silicon × C_bit = x.xx
- 耦生度等级：[Lv0孤立/Lv1连接/Lv2协作/Lv3共生]
- 等级特征：[对应等级的特征描述]
五、优化路径
- 短板识别：[最薄弱的子项及得分]
- 优化优先级：[排序后的优化建议]
- 预期提升：[优化后的耦生度预期值]
- 升级路径：[从当前等级向下一等级跃迁的关键动作]
六、三元平衡建议
- 最弱一元：[碳基/硅基/比特] - [具体提升措施]
- 平衡策略：[如何避免一元过强而其他过弱]
核心理论
- 耦生度计算公式：C_total = C_carbon × C_silicon × C_bit，体现三元的乘法关系与木桶效应
- 共生分级系统：Lv0孤立→Lv1连接→Lv2协作→Lv3共生，四级跃迁路径
- 三元本体论：碳基（人）、硅基（系统）、比特（数据）三元的有机统一是数字化的本质
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.
- 12d ago First seen · 127 lines · 34 tokens per session scan A 50d7384932a3
metago-coupling-measure is a skill published in the GitHub repository metago-ai/metagolifeform (4 stars, last pushed 11d ago), licensed MIT. It adds 34 tokens to every session and 1,515 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 2026-08-31.
Other skills, from other repositories
card-xiaohongshu
Xiaohongshu-style knowledge cards, arranged as a swipeable multi-card carousel.
extract
Run the full Semantica semantic extraction pipeline on a file or selected text — NER, relations, events, coreference resolution, triplets, and validation. Clears result cache before each run. Returns Markdown tables with entity/relation/event/triplet results and inline validator warnings.
prototype-web
A clickable, high-fidelity web product prototype with navigation, a hero section, feature cards, steps, social proof, and optional pricing. It is designed to resemble a finished landing page while remaining a prototype.
deck-course-module
A course or workshop slide template with persistent learning goals, teaching pages, multiple-choice self-tests, and a wrap-up.
loop-orchestration
Reference loop-orchestration example; a local loop host chains governed runx turns through receipts, budgets, context, and stop policy.
slack-notify
Plan a digest-bound Slack notification, then deliver the exact approved channel post through any compatible Slack binding with provider readback.