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-qimengit 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-qimen)<a href="https://agentmods.dev/skills/metago-ai/metagolifeform/metago-qimen"><img src="https://agentmods.dev/badge/skills/metago-ai/metagolifeform/metago-qimen/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-qimen"><img src="https://agentmods.dev/badge/skills/metago-ai/metagolifeform/metago-qimen.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 | $0.00047 | $0.00478 |
| Opus 5.5 | $0.00019 | $0.00191 |
| Sonnet 5.5 | $0.00009 | $0.00096 |
| Haiku 4.5 | $0.00005 | $0.00048 |
Grade A, and why
metago-qimen 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 today.
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
metago-qimen
能力
时家奇门：节气定局（阴阳遁 18 局）/ 三元 / 三奇六仪 / 值符值使 / 九星八门八神 / 1080 局全枚举
输入
metago-shushu qimen
应用
天盘=环境层 / 地盘=基础层 / 人盘=主体层 / 神盘=不可控层 —— 直接服务 P-Space OS / SIP 态势建模
输出
阴阳遁局数 + 九宫三奇六仪 + 星门神落宫
合规红线（所有易理技能通用）
- 一切断言 = 启发式标签 + 置信度 + 规则编号，禁止无据断言
- 不用于医疗/投资/法律等受监管决策替代（A36）
- 输出含免责声明段；避封建迷信表述
- 引擎：本环境的
yiliMCP 服务器（14 个工具）——shushu_almanac历法 /bazi_calc四柱 /liuyao_divine六爻 /qimen_calc奇门 /ziwei_calc紫微 /taiyi_calc太乙 /yijing_divine周易 /hetu_luoshu河图洛书 /wuxing_analyze五行 /shushu_diagnose象数诊断 /shushu_calculus文言微积分 /shushu_zeri择日 /ganzhi_convert干支 /shushu_info引擎元数据
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.
- today Changed · +6 lines b1c6e8d85b94
- 2d ago First seen · 26 lines · 47 tokens per session scan A f601d709234b
metago-qimen is a skill published in the GitHub repository metago-ai/metagolifeform (5 stars, last pushed today), licensed MIT. It adds 47 tokens to every session and 478 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-10-25.
Other skills, from other repositories
todo-for-ai-agent-runtime
Runtime integration skill for external agents connecting to Todo for AI over HTTP API Token / Agent Key, including auth, task lease, events, commit, and task logs.
karpathy-guidelines
Tool-agnostic behavioral guidelines for AI coding assistants. Use when writing, reviewing, debugging, or refactoring code to reduce overengineering, surface ambiguity, make surgical changes, and define verifiable success criteria.
pkf-writing
Author, update, convert, validate, persist, and render PKF (.pkf) content through message-inline, Library Asset, or Memory Page carriers. Use for structured reports, knowledge pages, delivery cards, or any .pkf body. NOT for recall, memory-graph placement, or curation decisions — those belong to the memory skill.
monorepo-management
Master monorepo management with Turborepo, Nx, and pnpm workspaces to build efficient, scalable multi-package repositories with optimized builds and dependency management. Use when setting up monorepos, optimizing builds, or managing shared dependencies.
loop-engineering
Shared loop-engineering reference for COG skills - the agent loop, deterministic verifiers, termination conditions, in-loop context management, and named patterns. Invoke when designing or debugging a skill that iterates (search-verify-retry, scan-until-dry, fetch-retry-gate).
qa-knowledge
To run QA engineering — requirements/gap analysis, scenario & spec design, test implementation, failure triage — over the QA knowledge base.