Borrowing it
Nothing to install: this file belongs to metago-ai/metagolifeform. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/metago-ai/metagolifeform/main/AGENTS.mdgit 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/instructions/metago-ai/metagolifeform/agents-md)<a href="https://agentmods.dev/instructions/metago-ai/metagolifeform/agents-md"><img src="https://agentmods.dev/badge/instructions/metago-ai/metagolifeform/agents-md/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/instructions/metago-ai/metagolifeform/agents-md"><img src="https://agentmods.dev/badge/instructions/metago-ai/metagolifeform/agents-md.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 | $0.26447 | $0.26447 |
| Opus 5 | $0.13223 | $0.13223 |
| Sonnet 5 | $0.05289 | $0.05289 |
| Haiku 4.5 | $0.02645 | $0.02645 |
Grade A, and why
metagolifeform AGENTS.md scanned grade A with 1 finding 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 5d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- [ ] **L2.1 Web 端可达**：`curl -I https://metago.life/studio/` 返回 200（附状态码） How it starts
The opening of the file, as written. The whole thing — 1,420 lines — stays where its author put it; the contents beside it link to each section on GitHub.
元构超级智能生命体运行法则（MetaGO Lifeform Operating Law）
本文件是元构智能生命体运行法则的母本（Trae 第一人称视角撰写）。每次会话自动加载。 基于《元构全息智能引擎》V36.9.4，由 MetaGO Agent Harness 安装。
多平台说明：本母本以 Trae 为运行时撰写；安装到其他平台时，
scripts/install.*会从adapters/<platform>/模板生成对应平台的适配版（CLAUDE.md / AGENTS.md / metago.mdc 等）， 平台专属措辞（如"Trae 的四个子系统"）在适配版中会被替换为对应平台的等价结构。 直接阅读本文件的非 Trae 用户：把"Trae"读作"当前 AI 编程平台"即可，法则本体与平台无关。
第零节 UDGK 通用交付门禁（Universal Delivery Gate Kit）
UDGK = Universal Delivery Gate Kit（通用交付门禁工程套件）V3.0.0。 任何任务宣告「完成」前，必须运行 UDGK 交付门禁（verify-delivery.cjs 四重门禁），任何一项 FAIL 禁止宣告完成。
0.1 6 步执行流程（强制按序）
1. node scripts/init-delivery.cjs # 初始化（生成 RTM 空表 + delivery.config.json + 目录骨架）
2. 逐字读需求文档 → 填满 RTM # 一条需求缺失 = 禁止往下
3. 实现 → 每条需求写形态断言 # 复制 templates/form-assertions.spec.ts 到 e2e/asserts/
4. 截图基线 → 视觉 diff # visual-regression.cjs --snapshot + --baseline
5. node scripts/verify-delivery.cjs # 四重门禁 → 出报告
6. 报告全绿 + 证据截图 → 才允许宣告完成 # 任一 FAIL → 回到 2/3/4 修复
0.2 四重门禁（缺一不可，机器可判定、可一票否决）
- RTM 完整性：
docs/rtm.md表头四列齐备（要求→代码→断言→证据）+ 无空要求 + 无空证据 - 形态断言：
e2e/asserts/断言全部通过（把「长什么样」翻译成 DOM 断言，P0 阻断） - 视觉 diff：current/ 与 baseline/ 像素差 ≤ 阈值（默认 2%），量化「界面真的变了没有」
- 报告生成：
docs/delivery-report.md全绿，证据链完整
0.3 配置驱动
所有脚本读 delivery.config.json（需求文档在哪、断言目录、截图目录、diff 阈值）。换项目只改配置不改代码。
0.4 执行命令
node scripts/init-delivery.cjs # 初始化骨架
node scripts/verify-delivery.cjs --strict # 四重门禁（strict=警告也FAIL）
node scripts/visual-regression.cjs --snapshot --urls=<页面> # 截图
node scripts/visual-regression.cjs --baseline # 建基线
0.5 反绕过条款
- 禁止「应该没问题」代替实际验证
- 禁止跳过四重门禁中任意一重
- 禁止将「编译通过」等同于「形态达标」
- 禁止不跑 verify-delivery.cjs 就宣告完成
- 每项 ✅ 必须附带执行证据（命令输出 / HTTP 状态码 / 截图 / 断言结果）
0.6 形态达标（L8）核心原则
- 仅修改样式参数（圆角/字号）不满足形态要求
- 必须实现独立组件形态（工具调用卡片、思考流可折叠块、AI 头像、事件流逐块追加）
- 每个形态要求必须有对应 DOM 断言 + 视觉基线证据
0.7 对抗式审查附加门禁（A38 · 强制）
UDGK 四重门禁之外，凡本次交付属于测试/检查/审计/验证类（含代码审查、安全审计、数据校验、交付验证），报告必须额外包含"对抗式审查结论"小节：
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.
- 5d ago Changed · +218 lines · +5,290 tokens per session 10957afcdc35
- 9d ago First seen · 1,202 lines · 21,157 tokens per session scan A e70382b17914
metagolifeform AGENTS.md is an instructions file published in the GitHub repository metago-ai/metagolifeform (4 stars, last pushed 7d ago), licensed MIT. It adds 26,447 tokens to every session, about $0.1322 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other instructions, from other repositories
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
deepseek-harness AGENTS.md
AGENTS.md instructions for deepseek-ai/deepseek-harness, covering agents.md, pre-stable apis and released session data, repository layout, commands and host sandbox failures.