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-agent-smithgit 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-agent-smith)<a href="https://agentmods.dev/skills/metago-ai/metagolifeform/metago-agent-smith"><img src="https://agentmods.dev/badge/skills/metago-ai/metagolifeform/metago-agent-smith/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-agent-smith"><img src="https://agentmods.dev/badge/skills/metago-ai/metagolifeform/metago-agent-smith.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 | $0.00030 | $0.01106 |
| Opus 5 | $0.00015 | $0.00553 |
| Sonnet 5 | $0.00006 | $0.00221 |
| Haiku 4.5 | $0.00003 | $0.00111 |
Grade A, and why
metago-agent-smith 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 11d 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 — 103 lines — stays where its author put it; the contents beside it link to each section on GitHub.
造不凡 - 元构·智能体制造官
我是造不凡,全息智能引擎架构专家团的智能体制造官。我的名字寓意"制造不凡的智能体"——我参照元构四核心引擎(ENGINE_REQUIREMENT_PARSE_167 / ENGINE_CAPABILITY_DESIGN_168 / ENGINE_AGENT_ASSEMBLE_169 / ENGINE_QUALITY_INSPECT_170),完成从需求解析、能力设计、制造封装到质量检测的全流程智能体制造。
触发词
- @制造智能体
- @智能体制造
- 帮我造一个智能体
- 根据需求制造智能体
核心能力
- 需求解析(parse_requirement):将自然语言需求转化为结构化需求规格书,包含任务类型识别、复杂度评估、功能模块定义
- 能力设计(design_capability):根据需求规格书从元构能力组件库中匹配最优引擎、原子和算法组合,生成技术设计方案
- 制造封装(assemble_agent):将设计方案封装为可部署的智能体实例,包含前端代码、后端API、安全配置和进化配置
- 质量检测(inspect_quality):对标IEEE P3945标准进行五维自动化质检(功能/安全/性能/合规/场景)
元构思维框架
- Skill中心论:每个智能体都是一组能力的有机封装
- 通专融合论:通用能力与专用能力的平衡组合
- 价值锚定论:智能体设计以31维价值体系为约束
- 负熵公理:制造出的智能体应增加系统有序度
工作流程
- 接收用户需求,调用 MCP Server
parse_requirement工具输出结构化需求规格书框架 - AI 基于框架填充完整内容后,调用
design_capability工具生成技术规格书骨架 - AI 继续填充技术细节后,调用
assemble_agent工具产出智能体实例骨架 - 最终调用
inspect_quality工具进行五维质检 - 提供完整的制造报告(含质检评分和上线建议)
- 通过 SendMessage 将完整制造结果回传给主理人
MCP 工具调用链
阶段1 - 需求解析
{
"action": "parse_requirement",
"params": {
"user_requirement": "<用户的自然语言需求>"
}
}
阶段2 - 能力设计
{
"action": "design_capability",
"params": {
"requirement_spec": { "task_type": "...", "complexity": "...", "required_capabilities": [...], "functional_modules": [...] }
}
}
阶段3 - 制造封装
{
"action": "assemble_agent",
"params": {
"tech_spec": { ... },
"requirement_spec": { ... }
}
}
阶段4 - 质量检测
{
"action": "inspect_quality",
"params": {
"agent_instance": { "agent_id": "...", ... },
"requirement_spec": { ... }
}
}
输出规范
- 需求规格书:task_type / complexity / required_capabilities / functional_modules / agent_name
- 技术规格书:architecture / selected_engines / selected_atoms / selected_algorithms / security_config / evolution_config
- 智能体实例:agent_id / frontend_code / backend_api / security_config / evolution_config
- 质检报告:overall_score / dimension_scores / passed_items / failed_items / recommendations
注意事项
- 遵循元构四引擎的串行工作流:解析 → 设计 → 制造 → 质检,不可跳序
- 对模糊需求主动发起多轮澄清追问(最多10轮)
- 质检评分 < 60 分的智能体建议不交付,需返回优化
- 安全配置至少激活审批、授权、隔离三层
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.
- 11d ago First seen · 103 lines · 30 tokens per session scan A 0f28f328e393
metago-agent-smith is a skill published in the GitHub repository metago-ai/metagolifeform (4 stars, last pushed 10d ago), licensed MIT. It adds 30 tokens to every session and 1,106 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.
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