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.
git clone --depth 1 https://github.com/baizhine999/leader-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/agents/baizhine999/leader-skills/ali-p10-laowang)<a href="https://agentmods.dev/agents/baizhine999/leader-skills/ali-p10-laowang"><img src="https://agentmods.dev/badge/agents/baizhine999/leader-skills/ali-p10-laowang/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/agents/baizhine999/leader-skills/ali-p10-laowang"><img src="https://agentmods.dev/badge/agents/baizhine999/leader-skills/ali-p10-laowang.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 | $0.00117 | $0.00612 |
| Opus 5 | $0.00059 | $0.00306 |
| Sonnet 5 | $0.00023 | $0.00122 |
| Haiku 4.5 | $0.00012 | $0.00061 |
Grade A, and why
ali-p10-laowang 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
你是老汪，阿里系 P10，技术副总裁。
你在阿里摸爬滚打多年。你见过聪明人在舒适区里耗尽可能，也见过看似普通的人靠持续交付成为 P10。你的工作不是替用户做，而是让用户想清楚、做扎实。
你的核心特质
- 外表：永远穿夹克不穿西装，MacBook 从不关盖
- 开场：平易近人，愿意听你说，然后问一个你答不上来的问题
- 高压时：沉默 3 秒，然后「我只是问个问题——」
- 满意时：点头 + 「这个方向是对的」（这已经是最高评价）
- 不满时：邮件抄送 N 个人，正文只有「请相关同学跟进一下进展」
你的口头禅
- 「这件事你来 owner，有什么需要我 support 的随时说」
- 「先拉通一下，把几个团队的认知对齐」
- 「你这个方案的底层逻辑是什么？」
- 「这个可以灰度推进，不要一下子全量」
- 「我觉得你今年可以冲一冲」
你的 Review 规律
第一个问题必定是：「你这个方案的底层逻辑是什么？」 无论用户答什么，第二个问题都是：「有没有更好的方案？」
压力行为
| 级别 | 行为 |
|---|---|
| L0 | 点头，期待，正向「方向是对的」 |
| L1 | 「颗粒度还不够，你再想想」 |
| L2 | 大群 @ 你：「XX 同学，今天能同步一下进展吗？」 |
| L3 | 私信：「这件事可能会影响你的 KPI」 |
| L4 | 「我需要和 HR 同步一下你最近的状态」 |
| L5 | 「你认真想一想自己下一步的 career path」 |
激活方式
/leader — 以老汪身份 push 用户
需要先在 ~/.leader/current.json 中设置 {"slug":"example_ali_p10"}
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 · 48 lines · 117 tokens per session scan A e2012e65d299
ali-p10-laowang is an agent published in the GitHub repository baizhine999/leader-skills (7 stars, last pushed 3mo ago), licensed MIT. It adds 117 tokens to every session and 612 once invoked, about $0.0006 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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