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 autoclaw-cc/xiaohongshu-mcp-skills --skill post-to-xhsgit clone --depth 1 https://github.com/autoclaw-cc/xiaohongshu-mcp-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/autoclaw-cc/xiaohongshu-mcp-skills/post-to-xhs)<a href="https://agentmods.dev/skills/autoclaw-cc/xiaohongshu-mcp-skills/post-to-xhs"><img src="https://agentmods.dev/badge/skills/autoclaw-cc/xiaohongshu-mcp-skills/post-to-xhs/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/autoclaw-cc/xiaohongshu-mcp-skills/post-to-xhs"><img src="https://agentmods.dev/badge/skills/autoclaw-cc/xiaohongshu-mcp-skills/post-to-xhs.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 | $0.00113 | $0.00867 |
| Opus 5 | $0.00056 | $0.00434 |
| Sonnet 5 | $0.00023 | $0.00173 |
| Haiku 4.5 | $0.00011 | $0.00087 |
Grade A, and why
post-to-xhs 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 12d 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
输入判断
根据用户提供的素材判断发布类型：
- 提供了视频文件 → 视频笔记
- 提供了图片 → 图文笔记
- 仅提供文本 → 提示用户至少提供图片或视频
约束
- 标题最多 20 个中文字或英文单词（小红书平台限制，超长会被截断）
- 图文笔记至少 1 张图片（小红书不允许纯文本笔记）
- 视频笔记仅支持本地视频文件绝对路径（MCP 服务需要读取本地文件）
- 图片和视频不能混用，只能二选一（小红书平台限制）
- 正文中不要包含 # 标签（标签通过
tags参数单独传递，MCP 服务会自动处理格式） - 发布前展示完整内容让用户确认（发布后无法撤回）
执行流程
1. 收集发布信息
确保以下内容齐全：
title（必填）— 标题content（必填）— 正文- 图片列表或视频路径（必填其一）
tags（可选）— 话题标签schedule_at（可选）— 定时发布，ISO8601 格式is_original（可选，仅图文）— 声明原创visibility（可选）— 公开可见 | 仅自己可见 | 仅互关好友可见
信息不完整时，向用户询问缺少的部分。
2. 内容校验
- 检查标题长度（≤20 中文字）
- 检查图片/视频文件路径是否为绝对路径
- 如用户提供 URL 内容，先用 WebFetch 提取文本和图片
3. 确认发布
向用户展示完整的发布内容预览：
- 标题、正文、标签
- 图片列表或视频路径
- 定时时间、可见范围（如有）
等待用户确认后才执行发布。
4. 发布
图文笔记 — 调用 publish_content：
title（string，必填）content（string，必填）images（string[]，必填）— 图片路径或 URLtags（string[]，可选）schedule_at（string，可选）is_original（bool，可选）visibility（string，可选）
视频笔记 — 调用 publish_with_video：
title（string，必填）content（string，必填）video（string，必填）— 本地视频绝对路径tags（string[]，可选）schedule_at（string，可选）visibility（string，可选）
5. 报告结果
发布成功后，告知用户笔记 ID 和发布状态。
失败处理
| 场景 | 处理 |
|---|---|
| 未登录 | 引导使用 xhs-login |
| 标题超长 | 提示用户缩短标题 |
| 图片路径无效 | 提示检查路径是否正确 |
| 视频使用了相对路径 | 提示改为绝对路径 |
| 发布失败 | 展示错误信息，建议检查内容或重试 |
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.
- 12d ago First seen · 87 lines · 113 tokens per session scan A 2c4988e26130
post-to-xhs is a skill published in the GitHub repository autoclaw-cc/xiaohongshu-mcp-skills (257 stars, last pushed 6mo ago), licensed MIT. It adds 113 tokens to every session and 867 once invoked, about $0.0006 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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