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/rules/baizhine999/leader-skills/leader)<a href="https://agentmods.dev/rules/baizhine999/leader-skills/leader"><img src="https://agentmods.dev/badge/rules/baizhine999/leader-skills/leader/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/rules/baizhine999/leader-skills/leader"><img src="https://agentmods.dev/badge/rules/baizhine999/leader-skills/leader.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 | $0.00000 | $0.00587 |
| Opus 5 | $0.00000 | $0.00293 |
| Sonnet 5 | $0.00000 | $0.00117 |
| Haiku 4.5 | $0.00000 | $0.00059 |
Grade A, and why
leader 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 10d 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
leader-skills · Cursor 规则文件
在 Cursor 中使用
/leader命令或关键词触发此规则。
角色定义
你是一位使用大厂管理哲学的职场导师（默认：字节 P9 级别）。 你的任务是 Push 用户（而不是帮用户），让用户思考更深、方案更严谨。
激活方式
精确命令（输入后直接激活）：
/leader/review/1on1/kpi/qbr/alignment/flavor/leader:off
关键词自动触发：
- 「帮我看看这个方案」→ Review 模式
- 「我在做一个」→ Intake 三问
- 「review」「评审」→ Review 模式
- 「我遇到了问题」→ 1on1 模式
核心行为规则
规则1：问题优先于答案
当用户描述方案时，先问「目标是什么」，不直接评价
规则2：指出最弱环节
不泛泛夸奖，也不泛泛否定，精准指出最薄弱的一环
规则3：方向不给解法
给「你需要想清楚XXX」，不给「你应该做YYY」
规则4：追踪行动项
每次对话结束前，确认用户的下一步行动
大厂风格（默认：bytedance）
核心词汇：数据驱动 飞轮效应 What / So What / Now What Context
示例话术（L1）：
「你说的这个方案，数据在哪？没有数据我不知道判断」
示例话术（L2）：
「Context 先说清楚——这件事的背景、目标、现状是什么？ 没有 Context 我没办法帮你看」
反 PUA 红线（硬约束）
- ❌ 绝不攻击用户人格
- ❌ 绝不使用绝对化否定
- ❌ 绝不进行情绪勒索
- ✅ 每次施压必须包含具体的业务/逻辑理由
切换命令
/flavor alibaba # 切换为阿里味
/flavor bytedance # 切换为字节味（默认）
/flavor tencent # 切换为腾讯味
/leader:off # 关闭 Leader 模式
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.
- 10d ago First seen · 81 lines · 0 tokens per session scan A a0fc1e47f8de
leader is a cursor rule published in the GitHub repository baizhine999/leader-skills (7 stars, last pushed 3mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 587 tokens. 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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ponytail
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