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Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionalicloud-ai-audio-asrExecute the skills CLI command in your project's root directory to begin installation:
Fetches alicloud-ai-audio-asr from cinience/alicloud-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate alicloud-ai-audio-asr. Access via /alicloud-ai-audio-asr in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
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Category: provider
mkdir -p output/alicloud-ai-audio-asr
python -m py_compile skills/ai/audio/alicloud-ai-audio-asr/scripts/transcribe_audio.py && echo "py_compile_ok" > output/alicloud-ai-audio-asr/validate.txt
Pass criteria: command exits 0 and output/alicloud-ai-audio-asr/validate.txt is generated.
output/alicloud-ai-audio-asr/.Use Qwen ASR for recorded audio transcription (non-realtime), including short audio sync calls and long audio async jobs.
Use one of these exact model strings:
qwen3-asr-flashqwen3-asr-flash-2026-02-10qwen-audio-asrqwen3-asr-flash-filetransqwen3-asr-flash-filetrans-2025-11-17Selection guidance:
qwen3-asr-flash, qwen3-asr-flash-2026-02-10, or qwen-audio-asr for short/normal recordings (sync).qwen3-asr-flash-filetrans or qwen3-asr-flash-filetrans-2025-11-17 for long-file transcription (async task workflow).python3 -m venv .venv
. .venv/bin/activate
DASHSCOPE_API_KEY in environment, or add dashscope_api_key to ~/.alibabacloud/credentials.audio (string, required): public URL or local file path.model (string, optional): default qwen3-asr-flash.language_hints (array, optional): e.g. zh, en.sample_rate (number, optional)vocabulary_id (string, optional)disfluency_removal_enabled (bool, optional)timestamp_granularities (array, optional): e.g. sentence.async (bool, optional): default false for sync models, true for qwen3-asr-flash-filetrans.text (string): normalized transcript text.task_id (string, optional): present for async submission.status (string): SUCCEEDED or submission status.raw (object): original API response.Sync transcription (OpenAI-compatible protocol):
curl -sS --location 'https://dashscope.aliyuncs.com/compatible-mode/v1/chat/completions' \
--header "Authorization: Bearer $DASHSCOPE_API_KEY" \
--header 'Content-Type: application/json' \
--data '{
"model": "qwen3-asr-flash",
"messages": [
{
"role": "user",
"content": [
{
"type": "input_audio",
"input_audio": {
"data": "https://dashscope.oss-cn-beijing.aliyuncs.com/audios/welcome.mp3"
}
}
]
}
],
"stream": false,
"asr_options": {
"enable_itn": false
}
}'
Async long-file transcription (DashScope protocol):
curl -sS --location 'https://dashscope.aliyuncs.com/api/v1/services/audio/asr/transcription' \
--header "Authorization: Bearer $DASHSCOPE_API_KEY" \
--header 'X-DashScope-Async: enable' \
--header 'Content-Type: application/json' \
--data '{
"model": "qwen3-asr-flash-filetrans",
"input": {
"file_url": "https://dashscope.oss-cn-beijing.aliyuncs.com/audios/welcome.mp3"
}
}'
Poll task result:
curl -sS --location "https://dashscope.aliyuncs.com/api/v1/tasks/<task_id>" \
--header "Authorization: Bearer $DASHSCOPE_API_KEY"
Use the bundled script for URL/local-file input and optional async polling:
python skills/ai/audio/alicloud-ai-audio-asr/scripts/transcribe_audio.py \
--audio "https://dashscope.oss-cn-beijing.aliyuncs.com/audios/welcome.mp3" \
--model qwen3-asr-flash \
--language-hints zh,en \
--print-response
Long-file mode:
python skills/ai/audio/alicloud-ai-audio-asr/scripts/transcribe_audio.py \
--audio "https://dashscope.oss-cn-beijing.aliyuncs.com/audios/welcome.mp3" \
--model qwen3-asr-flash-filetrans \
--async \
--wait
input_audio.data (data URI) when direct URL is unavailable.language_hints minimal to reduce recognition ambiguity.output/alicloud-ai-audio-asr/transcripts/.output/alicloud-ai-audio-asr/transcripts/OUTPUT_DIR.references/api_reference.mdreferences/sources.mdskills/ai/audio/alicloud-ai-audio-tts-realtime/.Prerequisites
Time Estimate
15-45 minutes depending on use case complexity
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
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alicloud-ai-audio-asr is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Keeps context tight: alicloud-ai-audio-asr is the kind of skill you can hand to a new teammate without a long onboarding doc.
alicloud-ai-audio-asr has been reliable in day-to-day use. Documentation quality is above average for community skills.
Solid pick for teams standardizing on skills: alicloud-ai-audio-asr is focused, and the summary matches what you get after install.
Solid pick for teams standardizing on skills: alicloud-ai-audio-asr is focused, and the summary matches what you get after install.
alicloud-ai-audio-asr has been reliable in day-to-day use. Documentation quality is above average for community skills.
alicloud-ai-audio-asr fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
We added alicloud-ai-audio-asr from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Solid pick for teams standardizing on skills: alicloud-ai-audio-asr is focused, and the summary matches what you get after install.
Registry listing for alicloud-ai-audio-asr matched our evaluation — installs cleanly and behaves as described in the markdown.
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