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 agentmods add skills/mxm-sys/opencode-tianji/meihuanpx skills add Mxm-sys/opencode-tianji --skill meihuagit clone --depth 1 https://github.com/Mxm-sys/opencode-tianjiWrote 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/mxm-sys/opencode-tianji/meihua)<a href="https://agentmods.dev/skills/mxm-sys/opencode-tianji/meihua"><img src="https://agentmods.dev/badge/skills/mxm-sys/opencode-tianji/meihua.svg" alt="Measured on agentmods" 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 | $0.00085 | $0.00576 |
| Opus 5 | $0.00043 | $0.00288 |
| Sonnet 5 | $0.00017 | $0.00115 |
| Haiku 4.5 | $0.00009 | $0.00058 |
Grade A, and why
meihua 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 2d 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
梅花易数体用断卦(轻量流程)
第 0 步:须知
一事一占,心中默念所问之事。用一两句话告知即可,不展开。
第 1 步:收集必要信息(question 工具)
- 所问之事(必问):想测什么?分类参考:天时/人事/家宅/屋舍/婚姻/生产/饮食/求谋/求名/求财/交易/出行/行人/谒见/失物/疾病/官讼/坟墓。
- 起卦依据:默认当前时间(时间起卦);或用户报出卦名+动爻直接断(跳过起卦)。
第 2 步:调用工具
- 无卦:用
qiguamethod=time时间起卦得卦名/动爻。 - 有卦或已起卦:调用
meihua,传入:卦名、动爻、datetime、占事。
第 3 步:输出规范
- 【卦象】本卦/变卦/互卦。
- 【体用】体卦(代表自己)、用卦(代表对方/所问之事)及五行生克。先一句白话结论(吉/凶/中平/谨慎),如"体生用"→自己耗泄、"用克体"→受制。
- 【断卦】每条术语(体卦/用卦/生克)紧跟白话翻译,结合所问之事落具体建议。
- 【总结】纯白话一段,说清走向、最注意什么、建议怎么做。
- 注明"仅供参考,现实决策请结合实际情况"。
参考资料
- 体用断卦工具:opencode-tianji 插件提供 meihua 工具(十八类占断辞据包内 data/meihua.json)
- 起卦工具:qigua(method=time 时间起卦 / coins 铜钱 / manual 指定)
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.
- 2d ago First seen · 34 lines · 85 tokens per session scan A ff6169f7eee2
meihua is a skill published in the GitHub repository Mxm-sys/opencode-tianji (0 stars, last pushed 25d ago), licensed MIT. It adds 85 tokens to every session and 576 once invoked, about $0.0004 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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