Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/ZJU-REAL/Easelnpx agentmods add skills/zju-real/easel/skill-channels-uploadWrote 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-channels-upload)<a href="https://agentmods.dev/skills/zju-real/easel/skill-channels-upload"><img src="https://agentmods.dev/badge/skills/zju-real/easel/skill-channels-upload/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-channels-upload"><img src="https://agentmods.dev/badge/skills/zju-real/easel/skill-channels-upload.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 | $0.00079 | $0.00576 |
| Opus 5 | $0.00039 | $0.00288 |
| Sonnet 5 | $0.00016 | $0.00115 |
| Haiku 4.5 | $0.00008 | $0.00058 |
Grade A, and why
skill-channels-upload scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
微信视频号发布
基于通用浏览器发布框架
../../shared/scripts/web_publisher.py（--platform weixin-channels）。
⚠️ 环境依赖
pip install playwright+playwright install chromium- 首次
login用微信扫码登录视频号助手，登录态持久化复用- 远程/headless 环境用
login-qr --platform weixin-channels（抠二维码成图轮询），或走 Web「账号」页登录
- 远程/headless 环境用
- 选择器时效：视频号发布页描述区可能是富文本 div 而非 textarea，内置选择器为最佳努力，
首次务必
plan+--headed校验，失效时更新web_publisher.py的 weixin-channels 配置。
无浏览器环境可用 platforms / plan / check。
执行
ROOT=<项目根>; WP=$ROOT/skills/shared/scripts/web_publisher.py
python $WP check
python $WP login --platform weixin-channels # 微信扫码
python $WP plan --platform weixin-channels --media out.mp4 --title "标题"
python $WP publish --platform weixin-channels --media out.mp4 --title "标题" --exec --headed
Profile 感知
- 有 Profile：标题短（≤22字）贴合人设；竖版 9:16；可带话题与合集。
- 无 Profile：按视频号通用规范（短标题、竖版、正向内容）。
规则
- 视频号竖版 9:16；横版先 video-reframe 转制。
- 标题要短（视频号标题偏短），正文可展开。
- 首次
--headed目视确认扫码与发布流程；选择器失效即更新配置。 - 视频号内容审核偏严，发布前过 skill-quality-gate 合规检查。
参考来源
视频号助手网页发布流程；复用统一 Playwright 框架。微信登录需扫码，选择器按平台现状维护。
What ships with it
1 file 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.
- 10d ago First seen · 49 lines · 79 tokens per session scan A 30787f34b786
skill-channels-upload is a skill published in the GitHub repository ZJU-REAL/Easel (710 stars, last pushed yesterday), licensed Apache-2.0. It adds 79 tokens to every session and 576 once invoked, about $0.0004 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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