narrator-ai-cli

2 files shipped with this skill. Inline text is the catalog copy. The upstream link is the source repository.

• SKILL.md8.7 KBupstream ↗

  ---
  name: narrator-ai-cli
  version: "1.0.5"
  license: MIT
  description: >-
    AI 电影/短剧解说视频自动生成（AI 解说大师 CLI Skill）。当用户需要创建电影解说视频、短剧解说、影视二创、AI 配音旁白视频、film commentary、video narration、drama dubbing、movie narration 时触发。内置电影素材库、BGM、多语种配音、解说模板。通过 narrator-ai-cli 命令行实现：搜片→选模板→选 BGM→选配音→生成文案→合成视频的全流程自动化。CLI client for Narrator AI video narration API.
  user-invocable: true
  tags:
    - video-narration
    - film-commentary
    - ai-video
    - short-drama
    - content-creation
    - dubbing
    - tts
    - video-production
  metadata:
    openclaw:
      emoji: "🎬"
      primaryEnv: NARRATOR_APP_KEY
      install:
        - name: narrator-ai-cli
          type: pip
          spec: "narrator-ai-cli @ https://github.com/NarratorAI-Studio/narrator-ai-cli/archive/refs/tags/v1.0.0.zip"
      requires:
        bins:
          - narrator-ai-cli
        env:
          - NARRATOR_APP_KEY
  ---
  
  # narrator-ai-cli — AI Video Narration CLI Skill
  
  CLI client for [Narrator AI](https://openapi.jieshuo.cn) video narration API. Designed for AI agents and developers.
  
  - **CLI repo**: https://github.com/NarratorAI-Studio/narrator-ai-cli
  - **Resources preview** (BGM / dubbing / templates): https://ceex7z9m67.feishu.cn/wiki/WLPnwBysairenFkZDbicZOfKnbc
  
  ## Reference Index
  
  This file covers decision flow, the common workflow, and pointers. Detailed lookups live in `references/`:
  
  | Topic | File |
  |---|---|
  | Resource selection (material / BGM / dubbing / templates) — list commands, response formats, field mapping | `references/resources.md` |
  | Full workflow steps with parameter tables and JSON examples (Fast Path + Standard Path) | `references/workflows.md` |
  | Magic Video — optional visual template step (catalog, params, language rules) | `references/magic-video.md` |
  | Polling pattern, task types, file ops, user account, error codes | `references/operations.md` |
  
  ## Pipeline at a Glance
  
  ```
                      ┌─── Fast Path (原创文案, cheaper) ───┐
                      │   fast-writing → fast-clip-data     │
    Source material ──┤              ↓                      ├──→ video-composing ──→ (magic-video)
    (material list /  │   [video-composing keys off         │   final MP4 URL       optional visual
     search-movie /   │    fast-clip-data.task_order_num]   │                        template pass
     file upload)     └─────────────────────────────────────┘
                      ┌─── Standard Path (二创文案) ────────┐
                      │   popular-learning → generate-      │
                      │   writing → clip-data               │
                      │              ↓                      │
                      │   [video-composing keys off         │
                      │    generate-writing.task_order_num] │
                      └─────────────────────────────────────┘
  ```
  
  ## Agent Rules (mandatory — apply across all steps)
  
  > **Always:**
  > - **Confirm before acting.** Every resource (source, BGM, dubbing, template) and every `magic-video` submission requires explicit user approval. Never auto-select, never auto-submit.
  > - **Source data, never invent.** Construct `confirmed_movie_json` from `material list` fields or `task search-movie` output. If neither yields it, ask the user — do not fabricate.
  > - **Honor the language chain.** The dubbing voice's language defines the writing task `language` param AND every `magic-video` text param. All three must match. → `references/magic-video.md` § Language Awareness
  > - **Paginate `material list` to exhaustion, search programmatically.** Fetch all pages until `total` is consumed, then `grep -i` or `python3 -c` on the JSON. Never trust truncated terminal display.
  > - **Poll with the canonical `while` loop at 5-second intervals.** Never use a fixed-iteration `for` loop. → `references/operations.md` § Task Polling
  >
  > **Never:**
  > - **Submit `magic-video` without showing the full request body** (templates + every `template_params` value) and getting user confirmation. The cost is 30 pts/minute and irreversible.
  > - **Submit Chinese default values for `magic-video` text params when narration language is non-Chinese.** The defaults are hardcoded Chinese and will appear as Chinese text in a non-Chinese video.
  > - **Submit `.task_id` (32-char hex) as `order_num`.** Downstream tasks want `.task_order_num` (the prefixed string like `generate_writing_xxxxx`), not `.task_id`. Submitting the hex returns `10001 任务关联记录数据异常`. The other look-alike — `.results.order_info.order_num` (`script_xxxxx`) — is also wrong; see `references/operations.md` § Task Query Response Shape.
  > - **Auto-switch paths after a failure.** If a step fails, surface the error to the user and ask explicitly: retry the same path, switch to the other path, or abort. Never infer a path switch on the agent's own initiative.
  
  ## Prerequisites
  
  This skill assumes the `narrator-ai-cli` binary is installed and configured with a valid `NARRATOR_APP_KEY`. See [README.md](README.md) for install / setup. Agents can verify with `narrator-ai-cli user balance`.
  
  ## Core Concepts
  
  | Concept | Description |
  |---|---|
  | **file_id** | 32-char hex string for uploaded files. Via `file upload` or task results |
  | **task_id** | 32-char hex string returned on task creation. Poll with `task query` |
  | **task_order_num** | Assigned after task creation. Used as `order_num` for downstream tasks |
  | **files[]** | Output files in the completed task response (flat, top-level array). Each entry has `file_id`, `file_path`, `suffix`. Read `.files[0].file_id` for the next step's input |
  | **learning_model_id** | Narration style model — from a pre-built template (90+) or `popular-learning` result |
  | **learning_srt** | Reference SRT file_id. **Mutually exclusive** with `learning_model_id` |
  
  ## Conversation Initiation
  
  > ⚠️ **Agent behavior — first message of a session**: Before asking the user for a movie title or workflow path, **proactively orient them** about what the skill offers. Most users assume they need to upload their own video + SRT and don't realize a pre-built material library ships with the skill. Skipping this step often results in unnecessary uploads or aborted sessions.
  
  **Required opening (adapt to the conversation language):**
  
  1. **Lead with the pre-built material library.** Mention upfront that ~100 ready-to-use movies are available with video + SRT already loaded — no upload needed in most cases.
  2. **Offer three concrete entry points** (let the user pick one):
     - "I have a specific movie in mind" → take the title, search materials first, fall back to `task search-movie` only if not found
     - "Show me what's available" → run `material list --json` and present 5–8 titles spanning varied genres; offer to filter by genre on request
     - "I'll upload my own video + SRT" → guide through `file upload`
  3. **Defer the Fast vs Standard path question** until source material is confirmed. Asking both at once forces a decision the user has no context for yet.
  4. **Optionally share the visual resources preview link** (BGM / dubbing / templates browsable visually): https://ceex7z9m67.feishu.cn/wiki/WLPnwBysairenFkZDbicZOfKnbc — but only if the user wants to browse, not as a wall of links upfront.
  
  **Example opening (Chinese conversation):**
  
  > 你好，欢迎使用 AI 解说大师。这个技能可以帮你生成电影/短剧解说视频。我这边内置了约 100 部电影素材（视频 + 字幕都是现成的），所以大多数情况你**不需要自己上传任何文件**。
  >
  > 你想怎么开始？
  > 1. **直接告诉我片名** — 我先查内置素材库，没有再去外部搜
  > 2. **让我列一些内置素材** — 你可以按类型挑（喜剧 / 动作 / 悬疑 / 科幻…）
  > 3. **自己上传视频 + 字幕** — 我引导你完成上传流程
  
  After source material is confirmed, walk the user through the **decision sequence below — one question per turn, in order**. Do NOT collapse multiple decisions into one message; users cannot reason about `target_mode` before they've picked a path.
  
  **Decision sequence** (each step waits for explicit user confirmation):
  
  1. **Source material** — covered above.
  2. **Workflow path** — Fast (原创文案) or Standard (二创文案). See "Two Workflow Paths" below.
  3. **`target_mode`** — *only ask if path = Fast*. Choose mode 1 / 2 / 3 (see "Fast Path internal: `target_mode`" below). If path = Standard, **skip this ques

• README.mdupstream ↗

  Contents are not inlined in the catalog. Open the upstream file.

Plain-text copy, no login: /skill-bundles/narratorai-studio-narrator-ai-cli-skill.md