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-balance-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-balance-optimize)<a href="https://agentmods.dev/skills/metago-ai/metagolifeform/metago-balance-optimize"><img src="https://agentmods.dev/badge/skills/metago-ai/metagolifeform/metago-balance-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-balance-optimize"><img src="https://agentmods.dev/badge/skills/metago-ai/metagolifeform/metago-balance-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 | $0.00027 | $0.01253 |
| Opus 5 | $0.00014 | $0.00626 |
| Sonnet 5 | $0.00005 | $0.00251 |
| Haiku 4.5 | $0.00003 | $0.00125 |
Grade A, and why
metago-balance-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 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.
What it actually says
APO动态平衡
触发条件
当用户明确提到"动态平衡"、"APO"、"系统平衡"、"优化平衡"、"平衡度"、"三维平衡"等关键词，或面对需要在效率、稳定、创新三维之间寻求动态平衡的系统优化需求时，自动触发本技能。适用于静态最优解失效、需在多目标之间寻求动态均衡的场景。
适用场景
- 系统优化：在性能、稳定性、可扩展性之间寻求动态平衡
- 资源配置：在成本、质量、速度之间寻求动态平衡
- 性能调优：在吞吐量、延迟、资源占用之间寻求动态平衡
- 组织治理：在效率、公平、创新之间寻求动态平衡
- 产品迭代：在功能、质量、速度之间寻求动态平衡
执行步骤
1. A阶段（Assessment）——评估当前系统三维状态
对系统进行三维评估：
- 效率维度（E）：单位资源产出、响应速度、吞吐量
- 稳定维度（S）：故障率、一致性、可预测性
- 创新维度（I）：演化能力、适应性、探索性
- 每个维度评分（0-100），并标注当前瓶颈
- 输出三维状态向量 V = (E, S, I)
2. P阶段（Positioning）——定位平衡点
- 计算当前状态与理想平衡点的三维偏移量
- 识别偏移方向：偏效率、偏稳定、偏创新
- 计算各维度偏移量：ΔE, ΔS, ΔI
- 定位当前平衡点在三维空间中的坐标
3. O阶段（Optimization）——优化平衡
- 生成调优方案集（至少3个方案）
- 每个方案标注对三维的影响方向与幅度
- 评估方案的副作用与连锁反应
- 选择最小干预原则下的最优方案（参考卷3第七章）
4. 平衡度计算
B = 1 - σ(三维偏移) / 三维均值
- σ(三维偏移) = 三维偏移量的标准差
- B ∈ [0, 1]，越接近1表示越平衡
- B ≥ 0.85：优级平衡
- 0.6 ≤ B < 0.85：良级平衡
- B < 0.6：失衡，需立即优化
5. 动态平衡曲线生成
- 绘制三维平衡的时间演化曲线
- 标注历史平衡点与目标平衡点
- 识别平衡漂移趋势（向哪个维度偏移）
- 预测未来N步的平衡演化路径
6. 输出优化方案
输出包含：三维状态评估、平衡点坐标、平衡度B值、调优方案集（含副作用分析）、动态平衡曲线、预测路径。
输出格式
【APO动态平衡报告】
■ 三维状态：V = (E=78, S=92, I=45)
■ 当前瓶颈：创新维度偏低
■ 偏移量：ΔE=+8, ΔS=+22, ΔI=-25
■ 平衡度：B = 0.71（良级平衡，需优化创新维度）
■ 调优方案：
方案1：[描述] → 三维影响 (E-2, S-1, I+15)
方案2：[描述] → 三维影响 (E-5, S-3, I+20)
方案3：[描述] → 三维影响 (E0, S-2, I+10)
■ 推荐方案：方案3（最小干预原则）
■ 演化预测：[未来趋势]
核心理论
本技能基于元构生命体理论体系中的 APO三维动态平衡算法，来源于《卷2第六章》。APO强调平衡不是静态最优点，而是动态演化过程中的相对均衡态——避免任何一维过强导致系统脆性，也避免任何一维过弱导致系统僵化。其与卷3第七章"最小干预心法"深度耦合：调优时遵循最小干预原则，避免过度优化引发系统性震荡。
关联文档
- 卷2第六章：APO三维动态平衡算法的完整定义与数学推导
- 卷3第七章：最小干预心法——APO调优的操作哲学与干预边界
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 · 88 lines · 27 tokens per session scan A 8a8b263f37a3
metago-balance-optimize is a skill published in the GitHub repository metago-ai/metagolifeform (4 stars, last pushed 10d ago), licensed MIT. It adds 27 tokens to every session and 1,253 once invoked, about $0.0001 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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