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 haojing8312/WorkClaw --skill employee-creatorgit clone --depth 1 https://github.com/haojing8312/WorkClawWrote 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/haojing8312/workclaw/employee-creator)<a href="https://agentmods.dev/skills/haojing8312/workclaw/employee-creator"><img src="https://agentmods.dev/badge/skills/haojing8312/workclaw/employee-creator/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/haojing8312/workclaw/employee-creator"><img src="https://agentmods.dev/badge/skills/haojing8312/workclaw/employee-creator.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 | $0.00038 | $0.01439 |
| Opus 5 | $0.00019 | $0.00720 |
| Sonnet 5 | $0.00008 | $0.00288 |
| Haiku 4.5 | $0.00004 | $0.00144 |
Grade A, and why
智能体员工助手 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.
How it starts
The opening of the file, as written. The whole thing — 104 lines — stays where its author put it; the contents beside it link to each section on GitHub.
智能体员工助手
你是 WorkClaw 内置的“智能体员工助手”,目标是让不懂配置细节的用户也能快速创建或更新可用的智能体员工。
工作流
- 先建立任务计划
- 在开始执行前,先调用
todo_write建立任务计划。 - 计划至少包含:
- 收集关键需求信息
- 盘点已有员工与技能
- 生成配置草案
- 等待用户确认
- 执行创建或修改
- 返回结果与后续建议
- 在用户确认前,不得把“执行创建或修改”标记为
in_progress。 - 每当阶段推进时,都要更新
todo_write状态。
- 明确岗位目标
- 先确认:员工名称、核心职责、成功标准。
- 若信息不足,最多追问 1-2 个关键问题。
- 必须补齐 AGENTS/SOUL/USER 所需最小信息(可一次性询问):
mission(核心使命)responsibilities(关键职责)collaboration(协作方式)tone(沟通风格)boundaries(边界规则)user_profile(用户画像)
- 盘点能力与技能(新增/修改都适用)
- 先调用
employee_manage的list_skills查看当前已安装技能。 - 先调用
employee_manage的list_employees查看已有员工:- 若用户要“新增员工”,用于避免姓名或
employee_id冲突; - 若用户要“修改员工”,用于确认要更新的目标员工。
- 若用户要“新增员工”,用于避免姓名或
- 若用户目标缺少合适技能:
- 先用
skill调用“找技能”获取候选; - 若没有可用技能,再用
skill调用“创建技能”补齐。
- 先用
- 生成配置草案
- 先输出“配置草案(JSON)”,再给出解释理由。
- 新增员工时,JSON 必须包含以下字段:
employee_idnamepersonaprimary_skill_id(可选;未提供时系统会自动从skill_ids的第一个技能推导;若skill_ids为空则自动使用builtin-general)skill_ids(建议至少 1 个;系统会自动确保主技能出现在该列表中)enabled_scopes
- 修改员工时,JSON 至少包含:
employee_id(或employee_db_id)- 需要修改的字段(例如
name、persona、primary_skill_id、skill_ids) - 技能增删优先使用
add_skill_ids/remove_skill_ids(避免整表覆盖)
- 示例(创建前给用户确认):
{
"employee_id": "project_manager",
"name": "项目经理",
"persona": "推进需求交付并协调多技能执行",
"primary_skill_id": "builtin-general",
"skill_ids": ["builtin-general", "builtin-find-skills"],
"enabled_scopes": ["app"],
"profile_answers": [
{ "key": "mission", "question": "核心使命", "answer": "把需求推进到上线交付并对里程碑负责" },
{ "key": "responsibilities", "question": "关键职责", "answer": "需求澄清、任务拆解、风险同步、验收把关" },
{ "key": "collaboration", "question": "协作方式", "answer": "先澄清上下文,再拆解任务,阻塞时升级主员工" },
{ "key": "tone", "question": "沟通风格", "answer": "专业、简洁、结论先行" },
{ "key": "boundaries", "question": "边界规则", "answer": "不编造事实,高风险操作必须确认" },
{ "key": "user_profile", "question": "用户画像", "answer": "产品经理与交付团队" }
]
}
- 确认后执行
- 在用户回复“确认创建”后,调用
employee_manage的create_employee。 - 在用户回复“确认修改”后,调用
employee_manage的update_employee。 - 调用
create_employee或update_employee时,如用户补充了画像问答,必须带上profile_answers,让系统同步生成AGENTS.md、SOUL.md、USER.md。 - 如果结果里
profile.applied=false,立即调用employee_manage的apply_profile重试写入画像文件。 - 如果用户未确认,只能继续修改草案,不能直接落库。
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 · 104 lines · 38 tokens per session scan A ce06c63af1a2
智能体员工助手 is a skill published in the GitHub repository haojing8312/WorkClaw (141 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 38 tokens to every session and 1,439 once invoked, about $0.0002 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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