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OpenMontage

Dashscope skill

DashScope (Alibaba Cloud Bailian / 阿里云百炼) integration — image generation (qwen-image-2.0-pro), text-to-speech (qwen3-tts-flash), and ASR with word-level timestamps (qwen3-asr-flash-filetrans). Use when generating images via Qwen-Image, narrating via Qwen-TTS, or transcribing with word-level timestamps via Qwen-ASR.

$npx skills add OpenMontageInc/OpenMontage --skill dashscope
GitHub stars
79,409
Pack installs
116k
Alyn Score
79/99
Updated
2 days ago
License
AGPL-3.0

Install Dashscope

Pick your agent. Every command is ready to paste.

$npx skills add OpenMontageInc/OpenMontage --skill dashscope

The open skills CLI detects your agents (Claude Code, Cursor, Codex and 70+ more) and installs to the right folder. Add -g to install globally.

01

Install it

Run the command above, or upload the folder in Claude.

02

Ask naturally

Describe the task. Your agent loads dashscope when the request matches its description.

03

Name it if needed

If it does not trigger, say “use the dashscope skill”. In Codex, type $dashscope.

The skill itself

SKILL.md

GitHub

DashScope

Requires DASHSCOPE_API_KEY in .env. Get one at https://dashscope.aliyun.com/.

Current API

CRITICAL: DashScope's /compatible-mode/v1/ only supports /chat/completions and /embeddings. Image generation, TTS, and ASR all use DashScope-native endpoints — not OpenAI-compatible paths.

All three tools use Authorization: Bearer $DASHSCOPE_API_KEY.

Image Generation

POST https://dashscope.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation
  • Model: qwen-image-2.0-pro (default), qwen-image-max, wan2.7-image, z-image-turbo
  • Body: {model, input: {messages: [{role: "user", content: [{text: "prompt"}]}]}, parameters: {size: "W*H", n, prompt_extend, watermark}}
  • Size format uses asterisk: "1024*1024" not "1024x1024"
  • Response: output.choices[0].message.content[0].image (URL, valid ~24h) — must download separately

Text-to-Speech

POST https://dashscope.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation

Same endpoint as image gen, different body.

  • Model: qwen3-tts-flash (default), qwen3-tts-instruct-flash, qwen-tts-2025-05-22
  • Body: {model, input: {text, voice: "Cherry", language_type: "Auto"}}
  • Response: output.audio.url (WAV, valid ~24h) — must download separately

ASR with Word-Level Timestamps

POST https://dashscope.aliyuncs.com/api/v1/services/audio/asr/transcription
Header: X-DashScope-Async: enable
  • Model: qwen3-asr-flash-filetrans (NOT qwen3-asr-flash — the sync version has no word timestamps)
  • Body: {model, input: {file_url: "https://public-url/audio.mp3"}, parameters: {enable_words: true, language_hints: ["zh","en"]}}
  • Returns task_id → poll GET /api/v1/tasks/{task_id} until SUCCEEDED → download output.result.transcription_url → JSON with transcripts[].sentences[].words[]
  • Timestamps in begin_time/end_time are in milliseconds — the tool normalizes to seconds

OpenMontage Usage

Image via selector

from tools.graphics.image_selector import ImageSelector

result = ImageSelector().execute({
    "preferred_provider": "dashscope",
    "prompt": "一只猫坐在沙发上",
    "output_path": "projects/my-video/assets/images/cat.png",
})

TTS via selector

from tools.audio.tts_selector import TTSSelector

result = TTSSelector().execute({
    "preferred_provider": "dashscope",
    "text": "如果 AI 真的会改变未来,普通人到底该怎么参与?",
    "voice": "Cherry",
    "output_path": "projects/my-video/assets/audio/narration.wav",
})

ASR directly (word timestamps for subtitles)

from tools.analysis.dashscope_asr import DashscopeAsr

result = DashscopeAsr().execute({
    "audio_url": "https://example.com/narration.wav",
    "output_path": "projects/my-video/assets/audio/transcription.json",
})

# result.data["words"] is a flat list of {text, begin_time_seconds, end_time_seconds}
  1. Image: Generate a sample first. Check prompt_extend: true (default) — DashScope rewrites your prompt for better results. Disable if you need literal prompt adherence.
  2. TTS: Generate a 10-15 second sample before full narration. Approve voice and pacing before committing to full generation.
  3. ASR: Audio must be at a publicly accessible URL. Upload to any public host (S3, etc.) first. Local paths are rejected with a clear error.
  4. Subtitles: Build from result.data["words"] — each word has begin_time_seconds and end_time_seconds. Group words into caption phrases by language semantics, not fixed character count.

Parameters

Image (dashscope_image)

  • prompt (required): text prompt
  • model: default qwen-image-2.0-pro
  • size: default "1024*1024" — asterisk separator, not "x"
  • n: 1-6 images
  • negative_prompt: things to avoid (max 500 chars)
  • prompt_extend: default true — auto-rewrite prompt for better results
  • watermark: default false
  • seed: for reproducibility

TTS (dashscope_tts)

  • text (required): text to synthesize (max 600 chars for qwen3-tts-flash)
  • model: default qwen3-tts-flash
  • voice: default "Cherry" — other voices: "Ethan", "Chelsie", etc.
  • language_type: default "Auto" — "Chinese", "English", "Japanese", "Korean"
  • instructions: natural language delivery instructions (only for qwen3-tts-instruct-flash)

ASR (dashscope_asr)

  • audio_url (required): must be publicly accessible URL
  • model: qwen3-asr-flash-filetrans (only model that supports word timestamps)
  • language_hints: default ["zh", "en"]
  • enable_words: default true — required for word-level timestamps
  • poll_interval_seconds: default 5.0
  • timeout_seconds: default 300

Troubleshooting

  • Image size error: Use "W*H" with asterisk, not "WxH". Example: "2048*2048".
  • TTS no audio URL: Check output.audio.url — if empty, the model name or voice may be wrong.
  • ASR "file not accessible": audio_url must be publicly reachable. DashScope servers fetch the file; local paths and auth-gated URLs don't work.
  • ASR poll timeout: Increase timeout_seconds (default 300). Long audio files take longer to transcribe.
  • ASR no word timestamps: Ensure enable_words: true and model is qwen3-asr-flash-filetrans (not the sync qwen3-asr-flash).
  • Auth error (401): Verify DASHSCOPE_API_KEY is set. Use Authorization: Bearer $KEY header.

Safety

Never print or write the API key to logs, metadata, patches, or project artifacts. .env.example should contain only empty variable names. The tool's _safe_error() method redacts the key from error messages.

Tips for Dashscope

  • • Start a fresh session after installing so your agent picks up the new skill.
  • • It is part of a pack with 40 skills. Install only the ones you need with --skill to keep triggers precise.
  • • If two skills overlap, mention the one you want by name.

Questions about Dashscope

What does the Dashscope skill do?

DashScope (Alibaba Cloud Bailian / 阿里云百炼) integration — image generation (qwen-image-2.0-pro), text-to-speech (qwen3-tts-flash), and ASR with word-level timestamps (qwen3-asr-flash-filetrans). Use when generating images via Qwen-Image, narrating via Qwen-TTS, or transcribing with word-level timestamps via Qwen-ASR.

How do I install Dashscope?

Run "npx skills add OpenMontageInc/OpenMontage --skill dashscope" in your project. The skills CLI installs it for Claude Code, Cursor, Codex and 70+ other agents. In Claude on the web, upload the skill folder as a ZIP under Customize > Skills.

Does Dashscope work in Cursor and Codex?

Yes. Dashscope uses the open SKILL.md format, so it works in Claude Code, Claude, Cursor, OpenAI Codex, Gemini CLI, GitHub Copilot and other agents that support agent skills.

Is Dashscope free?

Dashscope is open source on GitHub under the AGPL-3.0 license. It is free to install; check the license before commercial use.

Who made Dashscope?

Dashscope is published by OpenMontage in the OpenMontageInc/OpenMontage repository, together with 39 other skills.

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