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 Mimori-su/qizheng-siyu-skills --skill qz-childrengit clone --depth 1 https://github.com/Mimori-su/qizheng-siyu-skillsWrote 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/mimori-su/qizheng-siyu-skills/qz-children)<a href="https://agentmods.dev/skills/mimori-su/qizheng-siyu-skills/qz-children"><img src="https://agentmods.dev/badge/skills/mimori-su/qizheng-siyu-skills/qz-children/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/mimori-su/qizheng-siyu-skills/qz-children"><img src="https://agentmods.dev/badge/skills/mimori-su/qizheng-siyu-skills/qz-children.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 | $0.00042 | $0.00569 |
| Opus 5 | $0.00021 | $0.00284 |
| Sonnet 5 | $0.00008 | $0.00114 |
| Haiku 4.5 | $0.00004 | $0.00057 |
Grade A, and why
qz-children 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 12d 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
qz-children
Purpose
子女、生育取象和亲子关系专题。本 Skill 输出以中文为主，所有结论都要区分“教材明确内容”“整理后的分析框架”“模型推理”“不确定项”。
When to use this skill
当用户请求与本 Skill 定位一致的学习、读盘、核心分析、专题分析、校时或报告整合任务时使用。若用户请求超出本 Skill 边界，先说明边界并交给对应上游或下游 Skill。
Required inputs
qz_structured_data.md、qz_core_report.md 和用户专题问题。
Output files
children_report.md。
Workflow
- 检查输入文件和上游依赖是否存在。
- 读取本 Skill 的 resources，只加载与问题相关的文件。
- 按数据契约或专题框架整理证据。
- 输出支持因素、制约因素、缺失数据、不确定项和谨慎结论。
- 专题 Skill 必须继承
qz_core_report.md，不能独立乱断。
Rules
- Reader 只读盘，不解读。
- Core 只基于
qz_structured_data.md分析，不绕开数据契约。 - 专题 Skill 必须继承
qz_core_report.md，不能各自独立乱断。 - 不使用确定性、恐吓式、绝对化语言。
- 引用教材时给出章节或页码范围；教材未明确时直接说明。
Safety rules
- 疾病问题：只作传统术数取象参考，提醒咨询医生。
- 法律问题：只作传统术数取象参考，提醒咨询律师。
- 投资问题：不提供投资建议或收益预测，提醒咨询持牌专业人士。
- 心理危机或现实危险：建议寻求现实专业帮助或紧急服务。
Reference resources
resources/children_framework.mdresources/children_report_rules.md
Output format
## 问题
## 数据基础
## 支持因素
## 制约因素
## 教材依据
## 谨慎结论
## 需要继续确认
Handoff to other skills
缺读盘数据交给 qz-reader；缺原局分析交给 qz-core；需要整合交给 qz-report。
What ships with it
3 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.
- 12d ago First seen · 73 lines · 42 tokens per session scan A d72a94869f6d
qz-children is a skill published in the GitHub repository Mimori-su/qizheng-siyu-skills (3 stars, last pushed 3mo ago), licensed MIT. It adds 42 tokens to every session and 569 once invoked, about $0.0002 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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