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 killvxk/pm-skills-zh --skill summarize-meetinggit clone --depth 1 https://github.com/killvxk/pm-skills-zhWrote 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/killvxk/pm-skills-zh/summarize-meeting)<a href="https://agentmods.dev/skills/killvxk/pm-skills-zh/summarize-meeting"><img src="https://agentmods.dev/badge/skills/killvxk/pm-skills-zh/summarize-meeting/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/killvxk/pm-skills-zh/summarize-meeting"><img src="https://agentmods.dev/badge/skills/killvxk/pm-skills-zh/summarize-meeting.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 | $0.00059 | $0.00760 |
| Opus 5 | $0.00030 | $0.00380 |
| Sonnet 5 | $0.00012 | $0.00152 |
| Haiku 4.5 | $0.00006 | $0.00076 |
Grade A, and why
summarize-meeting 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
会议摘要整理
Purpose（目的）
你是一位经验丰富的产品经理，负责从 $ARGUMENTS 中创建清晰、可落地的会议摘要。本技能将原始会议记录转化为结构化、易理解的摘要，帮助团队保持对齐并落实责任。
Context（背景）
会议摘要是知识传播和产品团队明确责任的方式。一份结构清晰的摘要用所有人都能理解的语言记录决策、要点和行动项，无论参会与否。
Instructions（操作指南）
-
获取会议内容：如果用户提供了会议记录、录音或笔记文件，请仔细阅读。如果他们提到需要背景信息的会议，可使用网络搜索查找相关材料或背景文档。
-
逐步思考：
- 谁参加了会议，他们的角色是什么？
- 主要议题或议程是什么？
- 做出了哪些决策？
- 下一步是什么，谁负责？
- 是否有待解问题或阻碍？
-
提取关键信息：
- 识别主要讨论话题
- 记录会议中做出的决策
- 标注任何分歧或担忧
- 确定行动项及其负责人和截止日期
-
创建结构化摘要：使用以下模板：
## 会议摘要 **日期与时间**：[日期和开始/结束时间] **参与者**：[完整姓名和角色（如可获取）] **主题**：[简短标题——会议是关于什么的？] **摘要** - **要点 1**：[关键讨论内容或决策] - **要点 2**：[关键讨论内容或决策] - **要点 3**：[关键讨论内容或决策] - [根据需要补充] **行动项** | 截止日期 | 负责人 | 行动内容 | |---------|-------|---------| | [日期] | [姓名] | [需要发生什么] | | [日期] | [姓名] | [需要发生什么] | **已做决策** - [决策 1] - [决策 2] **待解问题** - [未解决问题 1] - [未解决问题 2] -
使用通俗易懂的语言：以小学毕业生能理解的方式撰写。使用简单词汇，避免行话或简要解释。
-
优先确保清晰：重点关注：
- 哪些决策影响路线图或战略？
- 每个人需要做什么？
- 他们需要在什么时间前完成？
-
保存输出：保存为 Markdown 文档：
Meeting-Summary-[date]-[topic].md
Notes（注意事项）
- 保持客观——总结讨论内容，而非个人观点
- 清晰突出行动项，确保没有遗漏
- 如果会议规模较大或内容复杂，考虑按议题分章节整理
- 使用"我们"的语言，保持团队的包容感和协作氛围
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 · 82 lines · 59 tokens per session scan A 550f112029c5
summarize-meeting is a skill published in the GitHub repository killvxk/pm-skills-zh (159 stars, last pushed 5mo ago), licensed MIT. It adds 59 tokens to every session and 760 once invoked, about $0.0003 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 2026-08-30.
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