MCPInstall

dashscope

by calesthioMedia & Creative

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.

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Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/calesthio/openmontage --skill dashscope
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads dashscope automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

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}

Recommended Workflow

  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.

FAQ

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 https://github.com/calesthio/openmontage --skill dashscope in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/dashscope/ (personal) or .claude/skills/dashscope/ (project).

Which AI agents can use dashscope?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is dashscope safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains dashscope?

It is published by calesthio in calesthio/openmontage. It has 836 recorded installs.

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