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-03-dcv-valuegit 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-03-dcv-value)<a href="https://agentmods.dev/skills/metago-ai/metagolifeform/metago-thought-03-dcv-value"><img src="https://agentmods.dev/badge/skills/metago-ai/metagolifeform/metago-thought-03-dcv-value/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-03-dcv-value"><img src="https://agentmods.dev/badge/skills/metago-ai/metagolifeform/metago-thought-03-dcv-value.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 | $0.00065 | $0.00964 |
| Opus 5 | $0.00032 | $0.00482 |
| Sonnet 5 | $0.00013 | $0.00193 |
| Haiku 4.5 | $0.00006 | $0.00096 |
Grade A, and why
metago-thought-03-dcv-value 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
DCV 价值体系 V1.0
描述
六维贡献度量体系，通过 dT（技术）、dI（智能）、dO（组织）、dG（治理）、共元、育元六个维度量化任意贡献的综合价值，指导价值对齐与资源分配。
触发条件
- 量化个人/团队/系统的综合贡献
- 进行价值对齐评估
- 资源分配需要多维依据
- 评估投入产出的全面回报
前置条件
- 明确的贡献主体与贡献行为
- 可观测的贡献结果
元思想核心
六维贡献模型：
DCV = w1*dT + w2*dI + w3*dO + w4*dG + w5*共元 + w6*育元
| 维度 | 符号 | 含义 | 度量 |
|---|---|---|---|
| 技术贡献 | dT | 技术能力的净增量 | 新技术/新方法/新工具的数量与质量 |
| 智能贡献 | dI | 智能水平的净提升 | 决策质量/自动化程度/认知边界的扩展 |
| 组织贡献 | dO | 组织效能的净改善 | 协同效率/流程优化/规模扩展 |
| 治理贡献 | dG | 治理能力的净增强 | 合规性/安全性/公平性/透明度 |
| 共元贡献 | 共元 | 对公共元构的积累 | 可复用的知识/资产/基础设施 |
| 育元贡献 | 育元 | 对元构生态的培育 | 人才培养/生态建设/能力传承 |
权重动态调整：
- 初创期：w1(dT) > w2(dI) > w3(dO)
- 成长期：w2(dI) > w5(共元) > w1(dT)
- 成熟期：w4(dG) > w6(育元) > w5(共元)
价值密度：
rho = DCV / 资源消耗
rho > 1 为正价值创造；rho < 1 为价值耗散。
推理框架
步骤 1：贡献识别
- 界定贡献主体（个人/团队/系统）
- 界定贡献行为与结果
- 界定度量周期
步骤 2：六维打分（0-10 分制）
- dT：技术层面带来了什么新能力？
- dI：智能层面提升了什么决策质量？
- dO：组织层面改善了什么效能？
- dG：治理层面增强了什么保障？
- 共元：沉淀了什么可复用的公共资产？
- 育元：培育了什么长期生态能力？
步骤 3：权重确定
- 根据当前阶段确定 w1-w6
- 确保权重之和为 1
步骤 4：DCV 计算与价值密度分析
- 计算 DCV 总分
- 计算价值密度 rho
- 识别短板维度（最低分维度）
步骤 5：价值优化建议
- 针对短板维度提出提升方案
- 评估提升方案的 DCV 边际增量
验证方法
- 六维打分是否有客观证据支撑（非主观臆断）
- 权重设置是否与当前阶段匹配
- DCV 计算是否正确（加权和、价值密度）
- 短板维度的识别是否准确
- 优化建议的 DCV 边际增量是否为正
- 用历史贡献回测：相同类型的贡献，DCV 排序是否与实际价值排序一致
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 · 90 lines · 65 tokens per session scan A 30a2add5bebe
metago-thought-03-dcv-value is a skill published in the GitHub repository metago-ai/metagolifeform (4 stars, last pushed 11d ago), licensed MIT. It adds 65 tokens to every session and 964 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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