Video Podcast Maker
Agents365-ai/video-podcast-maker
A skill your agent uses when the user gives a topic and wants an automated topic-driven narrated explainer, podcast, or knowledge-summary video (Bilibili / YouTube / Xiaohongshu / Douyin / WeChat…
End-to-end Chinese video washing pipeline. An agent skill from Pluviobyte/rnskill.
Install Ra Video Wash Pipeline
$ npx skills add Pluviobyte/rnskill --skill ra-video-wash-pipeline -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install Pluviobyte/rnskill ra-video-wash-pipeline --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/Pluviobyte/rnskill.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/ra-video-wash-pipeline .claude/skills/ra-video-wash-pipeline && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "ra-video-wash-pipeline" agent skill from https://github.com/Pluviobyte/rnskill/tree/main/skills/ra-video-wash-pipeline into .claude/skills/ra-video-wash-pipeline/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ra-video-wash-pipeline", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/Pluviobyte/rnskill/tree/main/skills/ra-video-wash-pipelineType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add Pluviobyte/rnskill --skill ra-video-wash-pipeline -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install Pluviobyte/rnskill ra-video-wash-pipeline --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Pluviobyte/rnskill.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/ra-video-wash-pipeline .agents/skills/ra-video-wash-pipeline && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "ra-video-wash-pipeline" agent skill from https://github.com/Pluviobyte/rnskill/tree/main/skills/ra-video-wash-pipeline into .agents/skills/ra-video-wash-pipeline/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ra-video-wash-pipeline", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add Pluviobyte/rnskill --skill ra-video-wash-pipeline -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install Pluviobyte/rnskill ra-video-wash-pipeline --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Pluviobyte/rnskill.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/ra-video-wash-pipeline .cursor/skills/ra-video-wash-pipeline && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "ra-video-wash-pipeline" agent skill from https://github.com/Pluviobyte/rnskill/tree/main/skills/ra-video-wash-pipeline into .cursor/skills/ra-video-wash-pipeline/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ra-video-wash-pipeline", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/Pluviobyte/rnskill.git --path skills/ra-video-wash-pipeline--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add Pluviobyte/rnskill --skill ra-video-wash-pipeline -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install Pluviobyte/rnskill ra-video-wash-pipeline --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Pluviobyte/rnskill.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/ra-video-wash-pipeline .gemini/skills/ra-video-wash-pipeline && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "ra-video-wash-pipeline" agent skill from https://github.com/Pluviobyte/rnskill/tree/main/skills/ra-video-wash-pipeline into .gemini/skills/ra-video-wash-pipeline/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ra-video-wash-pipeline", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install Pluviobyte/rnskill ra-video-wash-pipelineInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add Pluviobyte/rnskill --skill ra-video-wash-pipeline -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/Pluviobyte/rnskill.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/ra-video-wash-pipeline .github/skills/ra-video-wash-pipeline && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "ra-video-wash-pipeline" agent skill from https://github.com/Pluviobyte/rnskill/tree/main/skills/ra-video-wash-pipeline into .github/skills/ra-video-wash-pipeline/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ra-video-wash-pipeline", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add Pluviobyte/rnskill --skill ra-video-wash-pipeline -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install Pluviobyte/rnskill ra-video-wash-pipeline --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Pluviobyte/rnskill.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/ra-video-wash-pipeline .opencode/skills/ra-video-wash-pipeline && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "ra-video-wash-pipeline" agent skill from https://github.com/Pluviobyte/rnskill/tree/main/skills/ra-video-wash-pipeline into .opencode/skills/ra-video-wash-pipeline/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ra-video-wash-pipeline", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
ra-video-wash-pipeline- GitHub stars
- 1.6k
- Token cost
- ~2.4k tokens
- SKILL.md length
- 1,163 words
- Files
- 2
- Skills in repo
- 45
- Repo updated
- First seen
- Licence
- Custom licence
At a glance
End-to-end Chinese video washing pipeline. An agent skill from Pluviobyte/rnskill.
- Works in 6 steps: Intake → Extract Transcript → Rewrite Script → …
- The user provides a Bilibili
- SKILL.md covers Goal, Source Privacy Boundary, Route and Workflow, plus 1 more section
- Calls python3
What it does
Ra Video Wash Pipeline is an agent skill from Pluviobyte/rnskill. End-to-end Chinese video washing pipeline. Use when the user provides a Bilibili, Douyin, Xiaohongshu, YouTube, web video URL, or local video file and asks for 视频洗稿, 视频二创, 洗稿并制作视频, 链接视频改写, 提取逐字稿后洗稿, or producing a new AI video from a source video. Orchestrates ra-逐字稿提取skill and ra-洗稿, ending at the 01-内容生产/视频工作台/待制作/ handoff queue; production continues through ra-video-production-director only on explicit request (直接制作/直接出片/一条龙).
Its SKILL.md is about 2.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `agents/openai.yaml`).
It sits in Media & Creative, covering Video production and AI video generation. It works with Bilibili, Douyin, Xiaohongshu and YouTube. The repository describes itself as: 雪踏乌云的 AI Agent Skills 集合.
When your agent uses it
- The user provides a Bilibili
- Local video file and asks for 视频洗稿
- Producing a new AI video from a source video
Example prompts
- “/ra-video-wash-pipeline”
Requirements
- Python 3
Workflow steps
6 steps, taken from the step headings in SKILL.md.
- Intake
- Extract Transcript
- Rewrite Script
- Queue The Handoff (default endpoint)
- Produce Video (only on explicit request)
- QC And Archive (explicit production only)
What it can do on your machine
Read from SKILL.md and the folder at commit 83d1783. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
python3
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Ra Video Wash Pipeline loads about 2.4k tokens when it runs. Until then it costs about 114 tokens; SKILL.md has 1,163 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
Its licence (Custom licence) doesn't allow us to republish the file, so here is its outline and opening line. It has 1,163 words (~2,407 tokens).
“Turn a source video link or local video file into a production-ready washed script: extract the faithful transcript, rewrite it through the established ra-洗稿 stack, then queue the approved script into 01-内容生产/视频工作台/待制作/ as the binding production contract. Video production is…”
- name
- ra-video-wash-pipeline
Files
SKILL.md and 1 other file in skills/ra-video-wash-pipeline of Pluviobyte/rnskill.
- SKILL.md
- agents/openai.yaml
Open the folder on GitHubat commit 83d1783
Compare with similar skills
Ra Video Wash Pipeline next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Ra Video Wash Pipeline this skillPluviobyte/rnskill | 1.6k | — | ~2.4k | Automated safety check: Pass | Custom licence | |
| Video Podcast MakerAgents365-ai/video-podcast-maker | 1.7k | — | ~4.9k | Automated safety check: Pass | MIT | |
| Video Downloaderkangarooking/kangarooking-skills | 662 | — | ~8.3k | Automated safety check: Pass | None | |
| Media To TranscriptbozhouDev/video-skills-toolkit | 150 | — | ~1.8k | Automated safety check: Notes | MIT | |
| Video DownloaderidiotLeoLYJ/Daliu-Awesome-Skills | 140 | — | ~475 | Automated safety check: Warn | None | |
| Video Thumbnail Generator0xsline/OpenChatCut | 2.2k | — | ~713 | Automated safety check: Pass | AGPL-3.0 |
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Related
Works with
Categories
Questions about Ra Video Wash Pipeline
What does Ra Video Wash Pipeline do?
End-to-end Chinese video washing pipeline. An agent skill from Pluviobyte/rnskill. Ra Video Wash Pipeline is an agent skill from Pluviobyte/rnskill. End-to-end Chinese video washing pipeline.
When should I use Ra Video Wash Pipeline?
Ra Video Wash Pipeline fits situations like: the user provides a Bilibili; local video file and asks for 视频洗稿; producing a new AI video from a source video.
How do I install Ra Video Wash Pipeline in Claude Code?
Run `npx skills add Pluviobyte/rnskill --skill ra-video-wash-pipeline -a claude-code`. Or copy the skill folder (skills/ra-video-wash-pipeline in Pluviobyte/rnskill) into .claude/skills/ra-video-wash-pipeline in your project. Claude Code loads it when a task matches its description.
How do I install Ra Video Wash Pipeline in Codex?
Run `npx skills add Pluviobyte/rnskill --skill ra-video-wash-pipeline -a codex`. Or copy the skill folder (skills/ra-video-wash-pipeline in Pluviobyte/rnskill) into .agents/skills/ra-video-wash-pipeline in your project. Codex loads it when a task matches its description.
Can I use Ra Video Wash Pipeline in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Pluviobyte/rnskill --skill ra-video-wash-pipeline -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ra-video-wash-pipeline, .gemini/skills/ra-video-wash-pipeline, .github/skills/ra-video-wash-pipeline and .opencode/skills/ra-video-wash-pipeline in your project.
What does Ra Video Wash Pipeline need to run?
Going by SKILL.md and its folder, Ra Video Wash Pipeline needs the command-line tools its instructions call (python3). Our summary lists: Python 3.
Does Ra Video Wash Pipeline access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Ra Video Wash Pipeline safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Ra Video Wash Pipeline use?
Ra Video Wash Pipeline has a licence file (the repository's licence) that doesn't match a standard licence. Read it on GitHub before reusing the skill.
How many tokens does Ra Video Wash Pipeline use?
About 2.4k tokens (SKILL.md is roughly 9.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Ra Video Wash Pipeline?
Skills that share tags, products or a category with Ra Video Wash Pipeline: Video Podcast Maker (Agents365-ai/video-podcast-maker, 1.7k stars), Video Downloader (kangarooking/kangarooking-skills, 662 stars), Media To Transcript (bozhouDev/video-skills-toolkit, 150 stars) and Video Downloader (idiotLeoLYJ/Daliu-Awesome-Skills, 140 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Ra Video Wash Pipeline?
Pluviobyte (a GitHub user) maintains it in Pluviobyte/rnskill, which has 1,639 GitHub stars. The repository holds 45 skills in this directory. The repository was last updated on September 21, 2026.
Source: Pluviobyte/rnskill on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.