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 zhinjs/zhin --skill musicgit clone --depth 1 https://github.com/zhinjs/zhinWrote 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/zhinjs/zhin/music)<a href="https://agentmods.dev/skills/zhinjs/zhin/music"><img src="https://agentmods.dev/badge/skills/zhinjs/zhin/music/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/zhinjs/zhin/music"><img src="https://agentmods.dev/badge/skills/zhinjs/zhin/music.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 | $0.00073 | $0.00418 |
| Opus 5.5 | $0.00029 | $0.00167 |
| Sonnet 5.5 | $0.00015 | $0.00084 |
| Haiku 4.5 | $0.00007 | $0.00042 |
Grade A, and why
music 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 26d 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
音乐搜索分享技能
搜索歌曲并以富文本卡片分享到聊天中。
工作流
典型的点歌流程是两步走：先搜后分享。
Example:
用户: 点一首周杰伦的晴天
步骤1: music_search(keyword="周杰伦 晴天", source="qq") → 获取歌曲列表
步骤2: music_share(id=搜索结果中的歌曲ID, source="qq") → 发送卡片
| 工具 | 用途 | 关键参数 |
|---|---|---|
music_search |
搜索歌曲 | keyword（关键词）, source（qq/163）, count（数量） |
music_share |
分享歌曲 | id（歌曲 ID，来自搜索结果）, source（qq/163） |
易错点
- search 和 share 的 source 必须一致。QQ 音乐搜到的 ID 不能用网易云分享。
- 分享需要 ID，不能直接用歌名。必须先搜索获取 ID。
- 用户没说平台时，默认用 QQ 音乐（
source="qq"）。
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 26d ago First seen · 51 lines · 73 tokens per session scan A a33ce38de3af
music is a skill published in the GitHub repository zhinjs/zhin (136 stars, last pushed today), licensed MIT. It adds 73 tokens to every session and 418 once invoked, about $0.0003 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 2026-09-21.
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