bytedance/agentkit-samples is a collection of examples and tutorials for Volcengine AgentKit, an AI-agent development platform for building, deploying, and operating agent applications. Developers use the samples to learn agent creation, multi-agent collaboration, memory, retrieval, MCP integrations, media generation, customer service, and other workflows. The catalogue skills provide agent workflows based on these examples.
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 bytedance/agentkit-samples --skill byted-recruitment-generalgit clone --depth 1 https://github.com/bytedance/agentkit-samplesWrote 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/bytedance/agentkit-samples/byted-recruitment-general)<a href="https://agentmods.dev/skills/bytedance/agentkit-samples/byted-recruitment-general"><img src="https://agentmods.dev/badge/skills/bytedance/agentkit-samples/byted-recruitment-general/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/bytedance/agentkit-samples/byted-recruitment-general"><img src="https://agentmods.dev/badge/skills/bytedance/agentkit-samples/byted-recruitment-general.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00060 | $0.01410 |
| Opus 5 | $0.00030 | $0.00705 |
| Sonnet 5 | $0.00012 | $0.00282 |
| Haiku 4.5 | $0.00006 | $0.00141 |
Grade A, and why
byted-recruitment-general 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 6d 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 — 164 lines — stays where its author put it; the contents beside it link to each section on GitHub.
通用招聘平台技能
功能概述
本技能提供通用的招聘平台候选人搜索与筛选流程，适用于多个招聘平台。
通用流程
1. 平台选择与登录
| 平台 | 登录URL | 特点 |
|---|---|---|
| https://www.linkedin.com/talent/home | 高端人才、国际化、详细工作经历 | |
| 猎聘 | https://wow.liepin.com/ | 本土人才 |
| 脉脉 | https://maimai.cn/platform/login?fr=ent&to=https%3A%2F%2Fmaimai.cn%2Fent%2Findex%3Ffr%3Dent | 本土人才 |
登录步骤：
- 打开对应平台的招聘者登录页面
- 等待页面加载
- 移交控制权给用户手动登录 (
<browser-handoff />) - 登录成功后保存 cookies
- 定期检查登录状态，失效时重新登录
2. 候选人搜索
搜索条件设置：
- 职位：根据JD确定目标职位
- 公司：目标公司列表（如：小米、OPPO、vivo、华为等）
- 地点：目标工作地点
- 经验：工作经验要求
- 学历：学历要求
搜索结果获取：
- 设置搜索条件
- 获取搜索结果页面快照
- 记录候选人基本信息
- 滚动获取更多结果
- 处理分页（如适用）
3. 候选人信息记录
基本信息：
- 姓名
- 当前职位
- 当前公司
- 工作地点
- 年龄
- 工作经验
- 学历
- 当前状态（在职/离职）
详细信息：
- 完整工作经历（公司、职位、时间）
- 教育背景（学校、专业、时间）
- 技能标签
- 成就和项目经验
- 优势描述
4. 匹配度评分体系
5星评分标准：
| 评分 | 匹配度 | 说明 |
|---|---|---|
| ⭐⭐⭐⭐⭐ | 完美匹配 | 经验、技能、背景完全符合JD要求 |
| ⭐⭐⭐⭐ | 很好匹配 | 大部分条件符合，经验技能高度相关 |
| ⭐⭐⭐ | 基本匹配 | 部分条件符合，有一定相关性 |
| ⭐⭐ | 一般匹配 | 少部分条件符合，相关性较低 |
| ⭐ | 不太匹配 | 基本不符合要求 |
评分维度：
- 工作经验：相关行业、相关职位、工作年限
- 技能匹配：JD要求的技能是否具备
- 公司背景：是否有目标公司或同行业经验
- 教育背景：学历、专业是否匹配
- 地点匹配：工作地点是否符合
5. 高匹配度候选人筛选
筛选标准：
- 优先选择 ⭐⭐⭐⭐⭐ 和 ⭐⭐⭐⭐ 候选人
- 每个职位至少筛选10个高匹配度候选人
- 记录完整的候选人信息
- 保存候选人详情页面截图（如需要）
6. 候选人沟通
打招呼操作：
- 找到候选人的"打招呼"或类似按钮
- 点击发送打招呼
- 记录已发送的候选人
- 优先给高评分候选人发送
注意事项：
- 打招呼前确认候选人匹配度
- 记录发送时间和候选人
- 避免重复发送
7. 结果保存与汇报
文件保存：
- LinkedIn:
/root/.openclaw/workspace/jd-process/[职位名]/[候选人姓名]-linkedIn-candidates.md - 脉脉:
/root/.openclaw/workspace/jd-process/[职位名]/[候选人姓名]-maimai-candidates.md - 猎聘:
/root/.openclaw/workspace/jd-process/[职位名]/[候选人姓名]-liepin-candidates.md
文件内容结构：
# [平台名称] - [职位] 候选人推荐
## 📋 任务说明
- 职位：[职位名称]
- 地点：[工作地点]
- 搜索条件：[搜索条件列表]
## 👥 候选人统计
- 总查看：XX位
- 5星：XX位
- 4星：XX位
- ...
## 🏆 高匹配度候选人推荐
### 1. [候选人姓名] ⭐⭐⭐⭐⭐
- **基本信息**：...
- **工作经历**：...
- **教育背景**：...
- **优势**：...
## 📊 总结
- 已记录XX位候选人
- 推荐XX位高匹配度候选人
- 已给XX位发送打招呼
平台特定技能
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.
- 6d ago First seen · 164 lines · 60 tokens per session scan A 10087d9e8cc8
byted-recruitment-general is a skill published in the GitHub repository bytedance/agentkit-samples (450 stars, last pushed 5d ago), licensed Apache-2.0. It adds 60 tokens to every session and 1,410 once invoked, about $0.0003 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 2026-09-03.
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