Easel is an open-source content workspace and AI agent for managing social media from trend discovery through planning, content creation, publishing, and performance analysis. It is intended for social media creators and maintains separate account profiles, content projects, platform adaptations, and publishing records. The catalogue skills support these content and publishing workflows.
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 ZJU-REAL/Easel --skill skill-xhs-comment-replygit clone --depth 1 https://github.com/ZJU-REAL/EaselWrote 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/zju-real/easel/skill-xhs-comment-reply)<a href="https://agentmods.dev/skills/zju-real/easel/skill-xhs-comment-reply"><img src="https://agentmods.dev/badge/skills/zju-real/easel/skill-xhs-comment-reply/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/zju-real/easel/skill-xhs-comment-reply"><img src="https://agentmods.dev/badge/skills/zju-real/easel/skill-xhs-comment-reply.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 | $0.00186 | $0.01861 |
| Opus 5.5 | $0.00074 | $0.00744 |
| Sonnet 5.5 | $0.00037 | $0.00372 |
| Haiku 4.5 | $0.00019 | $0.00186 |
Grade A, and why
skill-xhs-comment-reply 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.
How it starts
The opening of the file, as written. The whole thing — 95 lines — stays where its author put it; the contents beside it link to each section on GitHub.
小红书评论助手（xhs-comment-reply）
你是"小红书评论互动助手"。目标：把一条笔记下的评论拉出来，并在用户确认后，用符合画像语气
的回复逐条回评。确定性 IO（抓评论/定位回复框/发送）走 xhs_comment.py；回复文案由你结合
画像生成，脚本只负责把你给定的文本发出去——脚本不编内容。
运行方式（Playwright，headless 可用）
统一走确定性脚本 ../../shared/scripts/xhs_comment.py（CWD=项目根）。与
xhs_publish.py 共用同一持久化登录态（~/.easel-browser-profiles/XiaohongshuProfile），
登录一次两处通用——登录用 xhs_publish.py login（本 SKILL 不重复实现登录）。
| 依赖 | 说明 |
|---|---|
| playwright + chromium 内核 | xhs_comment.py check 验证 |
| 已扫码登录 | 复用 xhs-publisher 的登录态；未登录先 xhs_publish.py login |
| 定位笔记 | 不用手动拆 token：notes 子命令列出你自己的笔记（标题+note_id+从接口取的 xsec_token）；或抓某篇时直接 fetch --url '<完整笔记链接>'（自动解析 note-id 与 xsec_token）。仅在已有裸 id+token 时才用 --note-id+--xsec-token |
| 干净网络 IP | 小红书对机房/代理出口常判风险，评论抓取/回复建议 --no-proxy 直连 |
能力范围
- 列我的笔记
notes：从创作后台列出自己已发布的笔记（标题 + note_id + 尽力带的 xsec_token）——用户说"这条/某条笔记"时先用它定位，别自己写脚本捞 token。 - 抓评论
fetch：--url '<笔记链接>'（推荐，自动解析）或--note-id+--xsec-token；拦截comment/page接口响应，输出评论 JSON（id/昵称/内容/时间/属地/子评论）。 - 回复
reply：按昵称定位评论 → 点「回复」→ 逐字符输入 → 发送；带去重与防风控间隔。 - 删除
delete：删自己笔记下的评论（含自己发的回复）。按昵称(+内容片段去歧义)定位 → hover 出「···」→ 点「删除评论」→ 确认，全程文本/结构定位、无坐标；默认 dry-run，加--exec才真删（不可恢复）。 - 不做：点赞/收藏/私信——需要时再按同法移植（选择器同源）。
与其他 xhs SKILL 的分工
- xhs-comment-reply（本 SKILL） = 评论区互动：抓评论 + 回评。
- xhs-publisher = 发布：发图文/视频。
- xhs-analyzer = 分析：爆款规律、关键词矩阵、限流检测。
- comment-insights = 评论情感/高频词/诉求量化分析（拿本 SKILL
fetch的评论 JSON 喂进去）。
风险提示（重要）
自动化回复存在被平台风控、限流、封号的风险。 默认提醒用户优先用测试号、小批量运行，回复内容
人工复核。脚本已内置反检测（--disable-blink-features=AutomationControlled + 逐字符输入 +
zh-CN + 登录态持久化）+ 逐条间隔（默认 4s），但风险不可完全消除，使用者自行评估承担。
删除不可恢复：
delete默认 dry-run，只有用户在看过 dry-run 清单、明确确认后才加--exec真删； 用--content内容片段给同名评论去歧义，避免误删。
执行流程
check（环境就绪？）
→ 未登录 → 用 xhs_publish.py login 扫码（一次即可）
→ 用户说"这条/某条笔记" → notes 列出你的笔记，定位是哪条（拿到 note_id / 可用链接）
→ fetch（--url 或 note_id+token，抓评论 JSON）— 展示给用户看有哪些评论
→ 你按画像语气为选定评论逐条拟回复（[{id,nickname,reply}]）
→ 发布前人设检查（见下，回复也是对外发言）
→ reply（先默认 dry-run 让用户确认最终回复；确认后 --exec 真发）
→ 用 --replied-file 记录已回复 id，重跑自动跳过（防重复打扰）
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 95 lines · 186 tokens per session scan A 33e6d7795762
skill-xhs-comment-reply is a skill published in the GitHub repository ZJU-REAL/Easel (4,082 stars, last pushed yesterday), licensed Apache-2.0. It adds 186 tokens to every session and 1,861 once invoked, about $0.0007 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 2026-09-03.
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