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 cxcscmu/SkillLearnBench --skill chinese-rhyme-moderngit clone --depth 1 https://github.com/cxcscmu/SkillLearnBenchWrote 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/cxcscmu/skilllearnbench/chinese-rhyme-modern)<a href="https://agentmods.dev/skills/cxcscmu/skilllearnbench/chinese-rhyme-modern"><img src="https://agentmods.dev/badge/skills/cxcscmu/skilllearnbench/chinese-rhyme-modern/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/cxcscmu/skilllearnbench/chinese-rhyme-modern"><img src="https://agentmods.dev/badge/skills/cxcscmu/skilllearnbench/chinese-rhyme-modern.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 | $0.00023 | $0.00633 |
| Opus 5 | $0.00012 | $0.00316 |
| Sonnet 5 | $0.00005 | $0.00127 |
| Haiku 4.5 | $0.00002 | $0.00063 |
Grade A, and why
chinese-rhyme-modern 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 8d 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
Modern Mandarin Rhyme Groups for Poetry (中华新韵)
Overview
When composing classical-style Chinese poetry using modern Mandarin pronunciation (普通话), the rhyming is based on the vowel finals (韵母) of Pinyin.
Common Rhyme Groups (韵部)
1. 麻花韵 (a, ia, ua)
Examples: 家(jiā), 花(huā), 沙(shā), 下(xià), 华(huá)
2. 波歌韵 (o, e, uo)
Examples: 歌(gē), 河(hé), 多(duō), 国(guó)
3. 皆来韵 (ai, uai)
Examples: 来(lái), 开(kāi), 台(tái), 怀(huái)
4. 开微韵 (ei, ui/uei)
Examples: 飞(fēi), 归(guī), 回(huí), 催(cuī)
5. 姑苏韵 (u)
Examples: 书(shū), 湖(hú), 路(lù), 图(tú)
6. 鱼居韵 (ü)
Examples: 鱼(yú), 居(jū), 去(qù)
7. 豪遥韵 (ao, iao)
Examples: 高(gāo), 朝(cháo), 遥(yáo), 桥(qiáo)
8. 侯求韵 (ou, iu/iou)
Examples: 楼(lóu), 秋(qiū), 流(liú), 州(zhōu)
9. 寒山韵 (an, ian, uan, üan)
Examples: 山(shān), 年(nián), 关(guān), 圆(yuán), 天(tiān), 间(jiān)
10. 痕辰韵 (en, in, un, ün)
Examples: 人(rén), 春(chūn), 门(mén), 新(xīn)
11. 唐阳韵 (ang, iang, uang)
Examples: 光(guāng), 乡(xiāng), 长(cháng), 黄(huáng)
12. 庚青韵 (eng, ing, ong, iong)
Examples: 声(shēng), 明(míng), 风(fēng), 中(zhōng)
Key Rules
- All rhyming characters in a poem must belong to the same rhyme group.
- For regulated verse, rhyming characters should be in 平声 (1st or 2nd tone).
- Modern Mandarin has no 入声 (entering tone), so all characters are classified as 平 or 仄 based on their modern tones.
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.
- 8d ago First seen · 53 lines · 23 tokens per session scan A 9bf8a73d2446
chinese-rhyme-modern is a skill published in the GitHub repository cxcscmu/SkillLearnBench (83 stars, last pushed 2mo ago), licensed MIT. It adds 23 tokens to every session and 633 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 2026-09-03.
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