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 YangsonHung/awesome-agent-skills --skill linkedin-cngit clone --depth 1 https://github.com/YangsonHung/awesome-agent-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/skills/yangsonhung/awesome-agent-skills/linkedin-cn)<a href="https://agentmods.dev/skills/yangsonhung/awesome-agent-skills/linkedin-cn"><img src="https://agentmods.dev/badge/skills/yangsonhung/awesome-agent-skills/linkedin-cn/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/yangsonhung/awesome-agent-skills/linkedin-cn"><img src="https://agentmods.dev/badge/skills/yangsonhung/awesome-agent-skills/linkedin-cn.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 | $0.00056 | $0.00479 |
| Opus 5.5 | $0.00022 | $0.00192 |
| Sonnet 5.5 | $0.00011 | $0.00096 |
| Haiku 4.5 | $0.00006 | $0.00048 |
Grade A, and why
linkedin-cn 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 1mo 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
LinkedIn 自动化
Overview
通过 linkedin 命令行工具（由 Linked API 云浏览器驱动）操作 LinkedIn。获取与搜索主页和公司、发送私信与连接请求、发布动态、点赞与评论、运行 Sales Navigator 搜索，并提取关于人物、公司与动态的结构化数据。
何时使用
当智能体需要以编程方式操作 LinkedIn 时使用：规模化触达、潜在客户调研、人脉管理、内容发布或数据提取。
核心功能
- 获取与搜索：主页、公司、人脉搜索、Sales Navigator 搜索
- 互动：发送私信、连接请求、点赞、评论
- 发布：创建动态
- 提取：人物、公司与动态的结构化数据
不要使用
以下场景不应使用本技能：
- 绕过 LinkedIn 的访问控制、速率限制或账号安全措施
- 保存或暴露 LinkedIn 凭据、会话 Cookie 或访问令牌
- 未经用户明确批准发送私信、连接请求、点赞、评论或发布动态
使用说明
- 在任何写入操作前确认 LinkedIn 操作、目标和受众。
- 将 Linked API 凭据保存在用户的安全环境中，示例使用占位符。
- 在用户批准写入前，优先执行只读的主页、公司、搜索和提取操作。
- 在发送、发布或修改数据前，汇总目标与内容并立即取得确认。
- 遵守 LinkedIn 政策、用户同意、隐私要求和速率限制；认证或访问不可用时停止。
说明
每条命令都会通过 Linked API 启动真实云浏览器，因此操作通常需要数秒到数分钟，并非即时完成。需要 Linked API 账号与令牌。文档：https://linkedapi.io
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.
- 1mo ago First seen · 41 lines · 56 tokens per session scan A 8bcf1dffa0cd
linkedin-cn is a skill published in the GitHub repository YangsonHung/awesome-agent-skills (18 stars, last pushed 2mo ago), licensed MIT. It adds 56 tokens to every session and 479 once invoked, about $0.0002 per session on Opus 5.5. 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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