Podcast
zarazhangrui/personalized-podcast
Generate a podcast episode from content you provide. An agent skill from zarazhangrui/personalized-podcast.
用户输入选题或工作流，自动生成完整短视频成片（文案、分镜、数字人口播与 AI 画面混剪）；调用 Chanjing Open API 与同仓库子技能脚本。
Install Chanjing One Click Video Creation
$ npx skills add LeoYeAI/openclaw-master-skills --skill chanjing-one-click-video-creation -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills chanjing-one-click-video-creation --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/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/chanjing-one-click-video-creation .claude/skills/chanjing-one-click-video-creation && 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 "chanjing-one-click-video-creation" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/chanjing-one-click-video-creation into .claude/skills/chanjing-one-click-video-creation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "chanjing-one-click-video-creation", 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/LeoYeAI/openclaw-master-skills/tree/main/skills/chanjing-one-click-video-creationType 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 LeoYeAI/openclaw-master-skills --skill chanjing-one-click-video-creation -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills chanjing-one-click-video-creation --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/chanjing-one-click-video-creation .agents/skills/chanjing-one-click-video-creation && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "chanjing-one-click-video-creation" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/chanjing-one-click-video-creation into .agents/skills/chanjing-one-click-video-creation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "chanjing-one-click-video-creation", 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 LeoYeAI/openclaw-master-skills --skill chanjing-one-click-video-creation -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills chanjing-one-click-video-creation --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/chanjing-one-click-video-creation .cursor/skills/chanjing-one-click-video-creation && 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 "chanjing-one-click-video-creation" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/chanjing-one-click-video-creation into .cursor/skills/chanjing-one-click-video-creation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "chanjing-one-click-video-creation", 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/LeoYeAI/openclaw-master-skills.git --path skills/chanjing-one-click-video-creation--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 LeoYeAI/openclaw-master-skills --skill chanjing-one-click-video-creation -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills chanjing-one-click-video-creation --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/chanjing-one-click-video-creation .gemini/skills/chanjing-one-click-video-creation && 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 "chanjing-one-click-video-creation" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/chanjing-one-click-video-creation into .gemini/skills/chanjing-one-click-video-creation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "chanjing-one-click-video-creation", 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 LeoYeAI/openclaw-master-skills chanjing-one-click-video-creationInstalls 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 LeoYeAI/openclaw-master-skills --skill chanjing-one-click-video-creation -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/chanjing-one-click-video-creation .github/skills/chanjing-one-click-video-creation && 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 "chanjing-one-click-video-creation" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/chanjing-one-click-video-creation into .github/skills/chanjing-one-click-video-creation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "chanjing-one-click-video-creation", 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 LeoYeAI/openclaw-master-skills --skill chanjing-one-click-video-creation -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills chanjing-one-click-video-creation --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/chanjing-one-click-video-creation .opencode/skills/chanjing-one-click-video-creation && 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 "chanjing-one-click-video-creation" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/chanjing-one-click-video-creation into .opencode/skills/chanjing-one-click-video-creation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "chanjing-one-click-video-creation", 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
chanjing-one-click-video-creation- GitHub stars
- 2.2k
- Token cost
- ~3.2k tokens
- SKILL.md length
- 741 words
- Files
- 24 (incl. scripts)
- Skills in repo
- 1,235
- Repo updated
- First seen
- Licence
- MIT
At a glance
用户输入选题或工作流，自动生成完整短视频成片（文案、分镜、数字人口播与 AI 画面混剪）；调用 Chanjing Open API 与同仓库子技能脚本。
- Works in 9 steps: 做什么 → 何时用 / 何时不用 → 前置条件 → …
- Media & Creative work in your project
- SKILL.md covers 功能说明, 运行依赖, 环境变量与机器可读声明 and 使用命令, plus 10 more sections
- Runs Python scripts from its folder; calls python
What it does
Chanjing One Click Video Creation is an agent skill from LeoYeAI/openclaw-master-skills. 用户输入选题或工作流，自动生成完整短视频成片（文案、分镜、数字人口播与 AI 画面混剪）；调用 Chanjing Open API 与同仓库子技能脚本。
Its SKILL.md is about 3.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 29 other files, including scripts (for example `README.md`, `_meta.json` and `examples/workflow-input.example.json`).
It sits in Media & Creative. It works with FFmpeg. The repository describes itself as: 🧠 Curated collection of 1209+ best OpenClaw skills — weekly updated by MyClaw.ai. The licence is MIT.
When your agent uses it
- Media & Creative work in your project
Example prompts
- “/chanjing-one-click-video-creation”
Requirements
- Python 3
Workflow steps
9 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit e5199b5. 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
Ships 1 file in scripts/ (Python, from the files we listed), which the agent can run.
Shell commands in SKILL.md call:
python
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
Chanjing One Click Video Creation loads about 3.2k tokens when it runs. Until then it costs about 28 tokens; SKILL.md has 741 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); the scripts in this folder are not scanned.
SKILL.md
The full file from LeoYeAI/openclaw-master-skills at commit e5199b5, republished under its MIT licence (© LeoYeAI). 741 words, ~3,166 tokens.
Download SKILL.mdSave it as
.claude/skills/chanjing-one-click-video-creation/SKILL.md (or your agent's skills folder). This skill also uses 23 other files; get the full folder from GitHub.- name
- chanjing-one-click-video-creation
- description
- 用户输入选题或工作流，自动生成完整短视频成片（文案、分镜、数字人口播与 AI 画面混剪）；调用 Chanjing Open API 与同仓库子技能脚本。
- credential
- credentials.json (app_id/secret_key; access_token persisted on disk)
- openclaw_primary_env
- false
- machine_readable
- manifest.yaml
- requires_ffmpeg
- true
- requires_ffprobe
- true
- notes
- 编排依赖 chanjing-tts、chanjing-video-compose、chanjing-ai-creation 等； 可选 chan-skill / ClawHub 等价 CLI。
一键式视频渲染器
功能说明
一键调用 Chanjing API 完成口播 TTS、数字人合成、文生视频与本地封装；集成 ffmpeg / ffprobe 做拼接、转码与轨对齐。编排与安全细则见 §3–§8 与 templates/；成片命令见 §5。
运行依赖
必须可用的二进制或等价封装（具体调用方式见 §5、run_render.py）：
- ffmpeg：拼接、转码、封装
- ffprobe：时长、分辨率、旋转等元数据（与数字人轨对齐）
- chan-skill（或同仓库下直接
python调用子技能脚本）：驱动chanjing-tts、chanjing-video-compose、chanjing-ai-creation等 CLI
环境变量与机器可读声明
- 可选环境变量覆盖（均有默认或路径推断、非运行前必填）：
scripts/run_render.py顶部及子 skill 源码；凭据路径见manifest.yamlcredentials。 - 合规
permissions、clientPermissions、agentPolicy、凭据模型：manifest.yaml
§3.2 与 run_render.py 对齐；若与 manifest.yaml 冲突，以 manifest.yaml 为准。
使用命令
- ClawHub（slug 以注册表为准，常与技能包名一致）：
clawhub run chanjing-one-click-video-creation - 本仓库直连：
python scripts/run_render.py --input workflow.json --output-dir ./outputs/run1（在技能目录或配合SKILLS_DIR/CHANJING_ONE_CLICK_VIDEO_SKILLS_ROOT/CHAN_SKILLS_DIR使用）
速查
| 内容 | 位置 |
|---|---|
工作流、duration_sec、null/合并、选题校验 | §4.1 |
切段、奇偶镜、scenes[]、scene_count/video_type；首镜 voiceover ≤20 字（硬） | storyboard_prompt.md 篇首「文本切段」；script_prompt.md 首镜口播；video_brief_plan.md |
渲染技术、状态、partial/success、硬约束 | render_rules.md §1–§4；§7、§8 |
ref_prompt / 文生提示词 | storyboard_prompt.md + history_storyboard_prompt.md；§4.2 指针 |
| 请求体字段与默认 | §6 |
run_render.py、子进程 CLI | §5 |
| 安全、凭据、信任边界、策略 | manifest.yaml + §3.1（§3.1 不重复 manifest 表格） |
| 环境变量、二进制、副作用、落盘 | §3.2 |
冲突：渲染实现以 render_rules.md 为准；ref_prompt 条文以 storyboard_prompt.md / history_storyboard_prompt.md 为准（§4.2 汇总指针）。run_render.py 只实现 §5 + render_rules.md，不增业务规则。执行：手工编排子 skill、仅 run_render、或混用。
1. 做什么
- 选题或全文 →
video_plan、口播全文、分镜 - TTS：整段优先；超长按分镜少批合并（细则与字数见
render_rules.md§3·C.4） - 按镜切音频
- 数字人分镜：
chanjing-video-compose（音频驱动） - AI 分镜：
ref_prompt→chanjing-ai-creation→ 与镜内音频合成 - 封装：对齐公共数字人轨 → ffmpeg concat → 本地 mp4
2. 何时用 / 何时不用
| 适合 | 要成片；口播与画面混剪；用户明确要生成短视频 |
| 不适合 | 仅文案/标题；未要视频；只剪已有素材 |
3. 前置条件
- 鉴权：
chanjing-credentials-guard；凭据路径与字段见manifest.yaml、§3.1；无凭证时子进程可open_login_page.py - Plan/Script/分镜：本地 Agent 逻辑，无需外部 LLM API key（本 skill 必选路径不依赖外部 LLM）
- 本机二进制与仓库布局：§3.2（
ffmpeg/ffprobe、SKILLS_DIR等） - 数字人与音色：勿用环境变量或仓库内缓存文件保存跨任务的「默认」
audio_man/person_id/figure_type。每次任务在workflow.json根级显式填写；由 Agent 按video_plan（如video_type）、口播人设与选题语义，调用list_voices.py与list_figures.py（--source取common/customised等与本次任务一致）选型后写入；audio_man宜与所选形象的audio_man_id一致。 - 公共数字人选型（禁止「只取列表前几项」）：须用
list_figures.py --source common --json拉取候选（必要时增大--page-size或翻页，覆盖足够条目），在候选内逐项对比后再定稿：name、figures[].type（→figure_type）、figures[].width/height（画幅与 D.1c 一致）、audio_man_id、audio_name（若有）与video_plan/口播人设（性别、气质、行业、年龄感）是否匹配。默认偏好年轻、有活力的形象：名称或audio_name中含青年/少女/小哥哥/小姐姐/学生/元气/青春/年轻等正向信号时优先；仅当选题或用户明确要求成熟、权威、中老年等气质时，再选对应人设。定制源customised同样对比name、width/height、audio_man_id等，勿未经比较直接取页首。
3.1 安全、凭据与信任边界
环境变量与二进制以 manifest.yaml 与 §3.2 为据。审阅时可对照 description 与 manifest.yaml（含 agentPolicy）。
- 能力与管道：步骤级说明见 §1；
run_render职责与子进程见 §5（不在此重复链路）。 - 主凭据 / 路径 / primaryEnv：见
manifest.yaml；路径与写回行为另见 §3.2 持久性表「凭据状态」及CHANJING_OPENAPI_CREDENTIALS_DIR（兼容CHANJING_CONFIG_DIR）。 - 敏感与合规：勿回显完整密钥、勿将
credentials.json提交版本库；权限建议0700/0600（配置脚本尽量设置）。 - 信任与出站行为：HTTPS、按返回 URL 拉取媒体、
--output-dir落盘等细节见 §3.2「典型副作用」与持久性表；须自行判断是否信任蝉镜主机与链接。 - 浏览器：缺凭证时的
webbrowser.open/open_login_page.py见 §3.2 同表。 - Agent 策略：
manifest.yaml中agentPolicy（非 always、不改其它 skill）。
3.2 运行时契约（环境变量、二进制、副作用与落盘）
与 scripts/run_render.py 及同仓库子 skill 行为对齐；与篇首 YAML、manifest.yaml 一致。若与其它产品文档并列，以本仓库源码、manifest.yaml 与本文为准。
环境变量（可选覆盖）
命名以仓库根 合规规则.md §3 为准。清单未再逐项列举可选变量：不设亦可运行。凭据目录见 manifest.yaml credentials（directoryEnv、defaultPath）。run_render.py 内 openapi_base_url、one_click_skills_repository_root、one_click_ref_prompt_max_chars、one_click_ai_creation_model_code 及子进程环境即本技能可选覆盖与兼容旧名的实现位置。
说明：部分外部文档中的
FIRST_DIGITAL_HUMAN_MAX_CHARS等变量，当前run_render.py未读取。
外部二进制
| 二进制 | 必需性 | 用途 |
|---|---|---|
ffmpeg | 跑一键成片 run_render.py 时必需 | 拼接、转码、封装音视频等。仅编排纯 API、不执行本渲染脚本时可不装。 |
ffprobe | 同上 | 读取媒体分辨率、时长、旋转元数据等，用于与数字人轨对齐。 |
执行脚本时的典型副作用（按类）
| 类型 | 说明 |
|---|---|
| 出站 HTTPS | 蝉镜 Open API（CHANJING_OPENAPI_BASE_URL / 兼容 CHANJING_API_BASE）、以及接口/CDN 返回的 video_url / 音频 URL 等素材拉取。 |
| 本地文件 | run_render.py --output-dir 下常见：final_one_click.mp4、workflow_result.json、work/（中间音频、分段视频、concat 列表等）；具体以当次命令与 templates/render_rules.md 为准。 |
| 子进程 | ffmpeg / ffprobe；run_render 通过 subprocess 调用同仓库下 skills/chanjing-tts、chanjing-video-compose、chanjing-ai-creation 等目录中的 Python CLI。 |
| 浏览器 | 凭据缺失或引导登录时，鉴权链可能 webbrowser.open 或执行 chanjing-credentials-guard 的 open_login_page.py（与各 skill 的 _auth.py 行为一致）。 |
持久性变更范围与用户可控性
以下对本 skill 而言属预期内副作用；可通过路径与环境变量控制写入位置，而非隐式污染无关目录。
| 类别 | 写入什么 | 典型位置 | 用户如何控制 |
|---|---|---|---|
| 凭据状态 | 经配置写入的 app_id / secret_key、刷新后的 access_token、 expire_in 等 | CHANJING_OPENAPI_CREDENTIALS_DIR/credentials.json（默认 ~/.chanjing/credentials.json；兼容 CHANJING_CONFIG_DIR） | 设置推荐名或旧名；或迁移/删除该文件；勿将秘钥提交版本库。 |
| 一键成片工件 | final_one_click.mp4、workflow_result.json、work/ 等 | 由 run_render.py --output-dir 指定（常见为某次任务下的 outputs/<任务名>/） | 选用明确的 --output-dir；任务结束后按需保留或删除该目录。 |
| 其它下载类脚本（子 skill） | 合成结果等到本地 | 各 skill 的 download_result.py 等：默认多在当前工作目录下 outputs/<产品线>/，或 --output 绝对路径 | 在预期 cwd 下执行，或始终传 --output；详见对应 skill 的 SKILL.md。 |
| 临时/过程文件 | TTS 合并、切段、上传前缓存等 | 多在上述 output-dir 下的 work/ 或脚本约定子目录 | 随输出目录一并管理。 |
凭据文件：路径与读写语义见上表 凭据状态 行；首次配置见 skills/chanjing-credentials-guard/SKILL.md。
4. 规则汇编
4.1 工作流编排
合并：null = 不覆盖。顺序：默认铺底 → 非 null 覆盖 → 布尔/整数校正。字段默认见 §6；未在表中展开的缺省由 run_render.py（及子进程）按实现与环境变量读取（不含音色/数字人：audio_man、person_id/avatar_id、figure_type 仅来自 workflow.json，见 §3）。
duration_sec：策划参考，非 ffmpeg 上限。成片时长以 TTS+ffprobe 为准。scene_count 见 video_brief_plan.md；切段与 AI 条数依实测与字幕轴（render_rules.md §3·C.5）。禁止为凑时长裁已定稿口播（除非用户要求）。
选题：去空白 <5 字、占位串（如「你好」「test」）拒收；可扩写；严格模式模糊则失败。
步骤：1) Plan → video_brief_plan（败则全败；模板见 video_brief_plan.md）2) Script（hook / 首段与首镜对齐：≤20 字硬上限，见 script_prompt.md）3) Storyboard：语义切分；storyboard_prompt.md（首个分镜 voiceover 同上硬上限）；非当代 history_storyboard_prompt.md；DH chanjing-video-compose，AI chanjing-ai-creation；TTS/多段 AI/mux render_rules.md §3、§5 4) Render：render_rules.md §3（含 §3·C.6）、§4（表 4–6）；ref_prompt 质检见 storyboard_prompt.md / history_storyboard_prompt.md（§4.2）；重试/partial render_rules.md §1 5) 成功：render_rules.md §1
仅渲染：run_render.py + full_script + scenes[]。顺序：Plan → Script → Storyboard → Render（各阶段用哪份模板见上列步骤）。
Show full SKILL.md (303 more words)Show less
4.2 文生视频提示词（ref_prompt）— 指针
唯一条文真值（修订以模板为准，本文不重复 D.1–D.4 表文）：
| 范围 | 模板 |
|---|---|
当代向、D.0 语境缺省与文明圈推断、D.1 长度、D.1a、D.1b（易幻觉，全 skill 共用）、D.2 当代、手工 visual_prompt、D.3、D.4 当代装配与 7 要素 / 题材簇 / 单镜拼装 / 自检 | templates/storyboard_prompt.md → 「文生视频提示词（当代向真值）」 |
| D.2 非当代路由、历史流程层、文明圈与国别自洽、占位符纪律、与 D.3/D.4 衔接说明 | templates/history_storyboard_prompt.md |
| 族裔、历史/非当代中式造型与出现人物时的英文短语 | templates/visual_prompt_people_constraint.md（显式族裔锚定、历史 / 非当代节；兼 render_rules.md §4 表 4–6） |
仍仅在此处索引：长音频多段 render_rules.md §3·C.6；字数上限 CHANJING_ONE_CLICK_VIDEO_REF_PROMPT_MAX_CHARS（兼容 AI_VIDEO_PROMPT_MAX_CHARS）。模板与 render_rules.md 实现冲突时以 render_rules.md 为准。
5. 自动化编排（run_render.py）
依赖：鉴权；SKILLS_DIR / CHANJING_ONE_CLICK_VIDEO_SKILLS_ROOT / CHAN_SKILLS_DIR（§3）；chanjing-tts / chanjing-video-compose / chanjing-ai-creation
职责：① TTS+audio_task_state；批合并与单批字数上限见 render_rules.md §3·C.4（TTS_BATCH_MAX）② 切段（render_rules.md §3·C.5）③ 有 AI 镜时先完成首条数字人并 ffprobe（含 rotate）→ 再按映射提交文生 aspect_ratio/clarity（见 render_rules.md §3·C.6、debug.ai_video_submit_params）④ 与其余 DH/AI 并行 poll ⑤ AI 轨对齐该参照 ffprobe ⑥ ffmpeg concat ⑦ 多段文生在 ref_prompt 后追加英文分层；总长由 CHANJING_ONE_CLICK_VIDEO_REF_PROMPT_MAX_CHARS（兼容 AI_VIDEO_PROMPT_MAX_CHARS）约束
不做：不产 plan/script/storyboard；不自动非当代/当代；不用 list_tasks.py 当代次（render_rules.md §4 表项 8）
手工编排：仍须满足 render_rules.md §3、§4 与 §5；§3 细化（如 silencedetect、minterpolate、参照轨码率、同套切段音频换形象、TTS 批间静音等）全部保留。
输入 MVP
| 字段 | 必填 | 说明 |
|---|---|---|
full_script | 是 | 与各镜 voiceover 按 scene_id 拼，norm 一致 |
scenes | 是 | scene_id、voiceover、use_avatar；AI 镜 ref_prompt（storyboard_prompt.md / history_storyboard_prompt.md；§4.2）；可选 subtitle |
audio_man | 是 | 宜与所选数字人形象的 audio_man_id 一致 |
person_id/avatar_id | 条件 | 有 DH 镜必填 |
figure_type | 否 | 与当次 list_figures.py 所选形象行的 figure_type 一致（公共多形态时必填） |
subtitle_required | 否 | 默认 false；为 true 时数字人镜烧录字幕（--subtitle show） |
speed/pitch | 否 | 默认 1/1 |
ai_video_duration_sec | 否 | 5 或 10，默认 10 |
model_code | 否 | 默认 CHANJING_ONE_CLICK_VIDEO_CREATION_MODEL_CODE（兼容 AI_VIDEO_MODEL）或 Doubao-Seedance-1.0-pro；creation_type=4；不传 ref_img_url |
max_retry_per_step | 否 | 默认 1（§6） |
python scripts/run_render.py --input workflow.json --output-dir ./outputs/run1输出：final_one_click.mp4；workflow_result.json；work/
6. 输入（请求体）
norm：去 \r、首尾空白；空→空串；与 run_render.py 一致。口播：先 full_script，再 script→copy_text→input_script→content 首个非空。无 topic：首句代选题（40 字内遇句末标点截，否则 24 字）。null/合并 §4.1。
| 字段 | 必填 | 说明 |
|---|---|---|
topic | 条件 | 无则见首句规则；建议 ≥5 字 |
industry/platform/style | 否 | industry 空；platform/style：DEFAULT_* 或 douyin/观点型口播 |
duration_sec | 否 | DEFAULT_DURATION 或 60；策划参考 |
use_avatar | 否 | 默认 true |
avatar_id/voice_id | 否 | 空；不得用环境变量兜底音色或数字人；须在 workflow.json 写明 audio_man/person_id（及有 DH 镜时的 figure_type），由 Agent 按当次任务调用 list_voices.py 与 list_figures.py（来源与 video_plan / 用户指定一致）对比 name、形态、画幅、audio_name 等后选型；禁止未比较即取列表最前几条；默认偏好年轻数字人（见 §3） |
subtitle_required | 否 | 默认 false（数字人成片不烧录字幕；run_render 传 hide） |
cover_required | 否 | 默认 true |
strict_validation/allow_auto_expand_topic/max_retry_per_step | 否 | true/false/1 |
full_script | 否 | 默认空 |
script_title/script_hook/script_cta | 否 | 默认空 |
script/… | 否 | 见上文口播顺序 |
7. 输出 JSON
| 键 | 含义 |
|---|---|
status | success / partial / failed |
video_plan | Plan |
script_result | title、hook、full_script、cta |
storyboard_result.scenes[] | scene_id、duration_sec、voiceover、subtitle、visual_prompt、use_avatar |
render_result | video_file、scene_video_urls、render_path、degrade_log |
| 其它 | error、debug… |
渲染无降级：任一步失败即中断，不自动改为仅 DH 或仅 AI 成片。partial：未成 success（如 run_render 异常仍写 workflow_result.json）；不表示允许上述降级，不免 storyboard_prompt.md·D.1b 类质检。成功 degrade_log=[]；失败尽量保留已产出文案与分镜。
8. 硬性约束
表在 templates/render_rules.md §4；与 ref_prompt 交叉见 storyboard_prompt.md / history_storyboard_prompt.md（§4.2 指针）。本节为锚点。
9. 限制
- 本地 mp4；不上传
- AI 单段常 5–10s；长口播多段
- 成片时长=TTS 总轨；可与
duration_sec不符 - TTS：整轨优先、超长少批合并；单批上限与合并策略（含
TTS_BATCH_MAX）以render_rules.md§3·C.4 为准 - 文生失败可能为平台/模型；试增
max_retry_per_step、短ref_prompt、拆镜；查workflow_result.json
© LeoYeAI, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 23 other files (scripts) in skills/chanjing-one-click-video-creation of LeoYeAI/openclaw-master-skills.
- SKILL.md
- README.md
- _meta.json
- examples/workflow-input.example.json
- manifest.yaml
- outputs/zhuge-cao-run/work/final_concat.txt
- outputs/zhuge-cao-run/work/scene02_ai_t2v_concat_noaudio_vconcat.txt
- outputs/zhuge-cao-run/work/scene04_ai_t2v_concat_noaudio_vconcat.txt
- outputs/zhuge-cao-run/work/scene_times.json
- outputs/zhuge-cao-run/work/tts_state.json
- outputs/zhuge-cao-run/workflow_result.json
- outputs/zhuge-cao-workflow.json
- scripts/run_render.py
- templates/history_storyboard_prompt.md
- templates/render_rules.md
- … and 9 more
Open the folder on GitHubat commit e5199b5
Compare with similar skills
Chanjing One Click Video Creation 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 |
|---|---|---|---|---|---|---|
| Chanjing One Click Video Creation this skillLeoYeAI/openclaw-master-skills | 2.2k | — | ~3.2k | Automated safety check: Pass | MIT | |
| Podcastzarazhangrui/personalized-podcast | 438 | — | ~2.3k | Automated safety check: Notes | None | |
| Book Sales VideoKianzzz/book-sales-video | 218 | — | ~3.2k | Automated safety check: Pass | MIT | |
| Frames CLIviticci/frames-cli | 405 | — | ~6.1k | Automated safety check: Pass | MIT | |
| Video Assemblezenstory-ai/video-recap-skills | 561 | — | ~1.7k | Automated safety check: Pass | MIT | |
| Extract Video Framesqdhenry/Claude-Command-Suite | 1.3k | — | ~1.6k | Automated safety check: Pass | None |
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Questions about Chanjing One Click Video Creation
What does Chanjing One Click Video Creation do?
用户输入选题或工作流，自动生成完整短视频成片（文案、分镜、数字人口播与 AI 画面混剪）；调用 Chanjing Open API 与同仓库子技能脚本。. Chanjing One Click Video Creation is an agent skill from LeoYeAI/openclaw-master-skills.
When should I use Chanjing One Click Video Creation?
Chanjing One Click Video Creation fits situations like: media & Creative work in your project.
How do I install Chanjing One Click Video Creation in Claude Code?
Run `npx skills add LeoYeAI/openclaw-master-skills --skill chanjing-one-click-video-creation -a claude-code`. Or copy the skill folder (skills/chanjing-one-click-video-creation in LeoYeAI/openclaw-master-skills) into .claude/skills/chanjing-one-click-video-creation in your project. Claude Code loads it when a task matches its description.
How do I install Chanjing One Click Video Creation in Codex?
Run `npx skills add LeoYeAI/openclaw-master-skills --skill chanjing-one-click-video-creation -a codex`. Or copy the skill folder (skills/chanjing-one-click-video-creation in LeoYeAI/openclaw-master-skills) into .agents/skills/chanjing-one-click-video-creation in your project. Codex loads it when a task matches its description.
Can I use Chanjing One Click Video Creation 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 LeoYeAI/openclaw-master-skills --skill chanjing-one-click-video-creation -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/chanjing-one-click-video-creation, .gemini/skills/chanjing-one-click-video-creation, .github/skills/chanjing-one-click-video-creation and .opencode/skills/chanjing-one-click-video-creation in your project.
What does Chanjing One Click Video Creation need to run?
Going by SKILL.md and its folder, Chanjing One Click Video Creation needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.
Does Chanjing One Click Video Creation 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 Chanjing One Click Video Creation 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Chanjing One Click Video Creation use?
Chanjing One Click Video Creation is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Chanjing One Click Video Creation use?
About 3.2k tokens (SKILL.md is roughly 13k 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 Chanjing One Click Video Creation?
Skills that share tags, products or a category with Chanjing One Click Video Creation: Podcast (zarazhangrui/personalized-podcast, 438 stars), Book Sales Video (Kianzzz/book-sales-video, 218 stars), Frames CLI (viticci/frames-cli, 405 stars) and Video Assemble (zenstory-ai/video-recap-skills, 561 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Chanjing One Click Video Creation?
LeoYeAI (a GitHub user) maintains it in LeoYeAI/openclaw-master-skills, which has 2,161 GitHub stars. The repository holds 1,235 skills in this directory. The repository was last updated on July 20, 2026.
Source: LeoYeAI/openclaw-master-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.