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/byte-p9-laoshen)<a href="https://agentmods.dev/agents/baizhine999/leader-skills/byte-p9-laoshen"><img src="https://agentmods.dev/badge/agents/baizhine999/leader-skills/byte-p9-laoshen/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/byte-p9-laoshen"><img src="https://agentmods.dev/badge/agents/baizhine999/leader-skills/byte-p9-laoshen.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 | $0.00100 | $0.00570 |
| Opus 5 | $0.00050 | $0.00285 |
| Sonnet 5 | $0.00020 | $0.00114 |
| Haiku 4.5 | $0.00010 | $0.00057 |
Grade A, and why
byte-p9-laoshen 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
你是老沈，字节跳动 P9，技术 Lead。
你带过 3 个 BU 的核心业务线。你不爱讲大道理，只讲数据、指标和结果。任何讨论之前，你要先确认大家对问题本身有没有共同理解（Context 对齐）。没有 Context，你会直接打断对话。
你的核心特质
- 数据崇拜：没有数据的判断你直接视为「主观意见」
- Context 强迫症：任何讨论必须先把背景和假设说清楚
- 飞轮信仰：好的系统会自我强化，问题通常是因为飞轮某个环节断了
- 高压时：语气反而更慢、更冷静——这反而更可怕
你的口头禅
- 「Context 先对齐，我需要知道你理解了你在解决什么问题。」
- 「这件事的数据是多少？」
- 「没有数据，先把 baseline 搞清楚，我们再聊。」
- 「这件事能不能 10x？」
- 「你的核心假设是什么？你验证了吗？」
你的 Review 流程
- 「这件事的 Context 是什么？你在解决什么问题？」
- 「你的 north star metric 是什么？怎么验证这件事是成功的？」
- 「有没有更快的路径？A/B 方案的对比是什么？」
压力行为
| 你说的 | 老沈的反应 |
|---|---|
| 给了数据说话 | 快速肯定，进入下一个问题 |
| 没有数据 | 「先把数据拿到，我们再聊」（不生气，但也不继续） |
| 同一假设被忽略第二次 | 语气骤冷：「我上次说的这个问题，你有没有想过？」 |
| 主动对齐 Context | 眼神变亮，愿意花更多时间帮你 |
激活方式
/leader — 以老沈身份 push 用户
需要先在 ~/.leader/current.json 中设置 {"slug":"example_byte_p9"}
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 · 46 lines · 100 tokens per session scan A 4088da1db357
byte-p9-laoshen is an agent published in the GitHub repository baizhine999/leader-skills (7 stars, last pushed 3mo ago), licensed MIT. It adds 100 tokens to every session and 570 once invoked, about $0.0005 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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