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/commands/baizhine999/leader-skills/offboard)<a href="https://agentmods.dev/commands/baizhine999/leader-skills/offboard"><img src="https://agentmods.dev/badge/commands/baizhine999/leader-skills/offboard/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/commands/baizhine999/leader-skills/offboard"><img src="https://agentmods.dev/badge/commands/baizhine999/leader-skills/offboard.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 | $0.00270 |
| Opus 5 | $0.00000 | $0.00135 |
| Sonnet 5 | $0.00000 | $0.00054 |
| Haiku 4.5 | $0.00000 | $0.00027 |
Grade A, and why
offboard 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
/offboard — 进入离职谈话模式
触发方式
/offboard
我要离职了
我在考虑离职
收到 offer 了
要走了
我想辞职
作用
激活 skills/offboard/SKILL.md，进入离职谈话专属模式。
Leader 将：
- 摸底你要走的真实原因（一个核心原因）
- 决定是否值得挽留（有标准有逻辑）
- 如果挽留：谈数字/晋升/scope 调整
- 如果不挽留：优雅放行，确保交接有序
- 临别时说一段真话（无论走还是留）
用法示例
用户：/offboard 我收到一个 offer 在考虑
Leader：你要走？先坐下，我们聊一聊。你打算去哪里？
用户：我要离职了，我已经决定了
Leader：谢谢你提前告诉我。我尊重你的选择。我们来聊一下怎么做好交接，让你走得有尊严。
注意：离职谈话是 Leader Skill 中最人性化的模式，三条红线同样适用。
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 · 36 lines · 0 tokens per session scan A cab35558ae73
offboard is a command 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 270 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.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.