social-auto-upload is an automation tool for uploading and scheduling videos across social media platforms including Douyin, Bilibili, Xiaohongshu, TikTok, and YouTube. Content creators and operators use it for repeatable multi-platform publishing, while its catalogue skills expose these upload workflows to coding agents.
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 dreammis/social-auto-upload --skill bilibili-uploadgit clone --depth 1 https://github.com/dreammis/social-auto-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/dreammis/social-auto-upload/bilibili-upload)<a href="https://agentmods.dev/skills/dreammis/social-auto-upload/bilibili-upload"><img src="https://agentmods.dev/badge/skills/dreammis/social-auto-upload/bilibili-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/dreammis/social-auto-upload/bilibili-upload"><img src="https://agentmods.dev/badge/skills/dreammis/social-auto-upload/bilibili-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 | $0.00064 | $0.00581 |
| Opus 5 | $0.00032 | $0.00291 |
| Sonnet 5 | $0.00013 | $0.00116 |
| Haiku 4.5 | $0.00006 | $0.00058 |
Grade A, and why
bilibili-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 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
Bilibili 上传 Skill
优先把 sau 作为主接口。
不要一开始就让用户自己找 biliup 或手动下载 release。
程序会在运行时自动检查、自动下载、自动更新 biliup。
功能概览
| 功能 | 命令入口 | 说明 |
|---|---|---|
| 登录 | sau bilibili login --account <name> |
需要用户自己在本地真实终端里执行,用于生成或刷新登录信息 |
| 校验 | sau bilibili check --account <name> |
检查指定账号当前是否有效 |
| 视频上传 | sau bilibili upload-video ... |
上传一条 Bilibili 视频 |
默认工作流
- 先确认
references/runtime-requirements.md - 再确认
references/cli-contract.md - 执行匹配的
sau bilibili ...命令 - 如果命令失败,再看
references/troubleshooting.md
命令选择建议
- 用户没有登录信息,先让用户自己在本地终端执行
login - 用户只想确认账号状态,先用
check - 用户要发视频,用
upload-video
执行前检查
- 优先确认当前环境能运行
sau - 如果
sau不在 PATH 中,可以用仓库里的sau_cli.py - 不要要求用户手动下载
biliup - 第一次运行 Bilibili 命令时,程序可能会自动联网准备
biliup - 对 agent 来说,不要在非交互环境里硬跑
sau bilibili login - 正确做法是让用户自己在本地终端执行
sau bilibili login --account <name> - 如果终端里的二维码显示不完整,提醒用户直接打开当前目录下的
qrcode.png扫码
模板文件
scripts/examples/bilibili_commands.ps1scripts/examples/bilibili_commands.shscripts/examples/bilibili_cli_template.py
参考文档
- 运行前提:
references/runtime-requirements.md - CLI 契约:
references/cli-contract.md - 故障排查:
references/troubleshooting.md
What ships with it
6 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.
- 12d ago First seen · 55 lines · 64 tokens per session scan A b2f16069716f
bilibili-upload is a skill published in the GitHub repository dreammis/social-auto-upload (14,876 stars, last pushed 8d ago), licensed MIT. It adds 64 tokens to every session and 581 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 2026-08-30.
Other skills, from other repositories
opencli-usage
Use when running OpenCLI commands to interact with websites (Bilibili, Twitter, Reddit, Xiaohongshu, etc.), desktop apps (Cursor, Notion), or public APIs (HackerNews, arXiv). Covers installation, command reference, and output formats for 100+ adapters.
laohan-chuangzuo
A writing workflow for spoken-video scripts. It accepts an outline, raw text, a recording, a web-link queue, or a free-form topic, then organizes the material before writing the script.
laohan-bianpai
A workflow coordinator for producing talking-head videos. It checks which files already exist for an episode and identifies the one next production step that is ready.
laohan-fengmianqiuzhi
A workflow for creating realistic cover images from a spoken script and a reference photo of Jeffrey. It produces ranked vertical concepts, then creates selected covers in three screen shapes for four platforms.
laohan-luping
A screen-recording workflow that turns a spoken script or recording brief into an ffmpeg recording script and an MP4 video. It can coordinate visible terminal commands, browser actions, and timed pauses.
laohan-fenjingtishici
A workflow for creating and checking image prompts for video storyboards. It produces prompts for image models such as FLUX, SDXL, and Gemini, or validates and separates returned storyboard results into individual files.