
Alicloud Ai Audio Asr Test
- 280 installs
- 396 repo stars
- Updated July 18, 2026
- cinience/alicloud-skills
alicloud-ai-audio-asr-test is a Claude Code test harness skill that smoke-tests Alibaba Cloud Model Studio non-realtime Qwen ASR by running one minimal transcribe_audio.py request before production voice features ship.
About
alicloud-ai-audio-asr-test is a minimal viable test skill in cinience/alicloud-skills for non-realtime speech recognition. It verifies only that the ASR request chain works: authenticate, send one small audio job, and record pass or fail without guessing parameters. The recommended command runs `transcribe_audio.py` against a public welcome.mp3 with `--model qwen3-asr-flash --print-response`. Results follow a dated template noting skill path, conclusion, and error details. The parent skill documents five Qwen ASR model strings including sync and async filetrans variants. Reach for alicloud-ai-audio-asr-test when wiring DashScope ASR and need a sanity check before building UI or batch pipelines. Skip it for production transcription features—use aliyun-qwen-asr instead.
- ASR accuracy fixtures
- Latency benchmarking
- Quota and error tests
- Multi-locale audio samples
- Pre-release regression suite
Alicloud Ai Audio Asr Test by the numbers
- 280 all-time installs (skills.sh)
- Ranked #724 of 2,153 Testing & QA skills by installs in the Skillselion catalog
- Data as of Aug 5, 2026 (Skillselion catalog sync)
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| Installs | 280 |
|---|---|
| repo stars | ★ 396 |
| Last updated | July 18, 2026 |
| Repository | cinience/alicloud-skills ↗ |
How do you smoke test Alibaba Cloud Qwen ASR?
Validate ASR accuracy, latency, quotas, and error handling across representative audio samples before releasing voice transcription to production users.
Who is it for?
Developers integrating Alibaba Cloud DashScope Qwen ASR who need a one-command connectivity check before building transcription features.
Skip if: Skip alicloud-ai-audio-asr-test when you need production transcription, batch jobs, or realtime streaming ASR—use aliyun-qwen-asr instead.
When should I use this skill?
The user wants to validate ASR accuracy, latency, quotas, or error handling with a minimal audio sample before release.
What you get
Dated test log with request summary, response summary, and pass or fail conclusion for the ASR pipeline.
- pass/fail test log
- sample ASR response
By the numbers
- Parent aliyun-qwen-asr documents 5 exact Qwen ASR model name strings
- Recommended smoke test uses qwen3-asr-flash against a public welcome.mp3 URL
- Catalog reports 280 installs for alicloud-ai-audio-asr-test
Files
Category: service
Cloud Backup
Use Alibaba Cloud OpenAPI (RPC) with official SDKs or OpenAPI Explorer to manage resources for Cloud Backup.
Workflow
1) Confirm region, resource identifiers, and desired action. 2) Discover API list and required parameters (see references). 3) Call API with SDK or OpenAPI Explorer. 4) Verify results with describe/list APIs.
AccessKey priority (must follow)
1) Environment variables: ALIBABACLOUD_ACCESS_KEY_ID / ALIBABACLOUD_ACCESS_KEY_SECRET / ALIBABACLOUD_REGION_ID Region policy: ALIBABACLOUD_REGION_ID is an optional default. If unset, decide the most reasonable region for the task; if unclear, ask the user. 2) Shared config file: ~/.alibabacloud/credentials
API discovery
- Product code:
hbr - Default API version:
2017-09-08 - Use OpenAPI metadata endpoints to list APIs and get schemas (see references).
High-frequency operation patterns
1) Inventory/list: prefer List* / Describe* APIs to get current resources. 2) Change/configure: prefer Create* / Update* / Modify* / Set* APIs for mutations. 3) Status/troubleshoot: prefer Get* / Query* / Describe*Status APIs for diagnosis.
Minimal executable quickstart
Use metadata-first discovery before calling business APIs:
python scripts/list_openapi_meta_apis.pyOptional overrides:
python scripts/list_openapi_meta_apis.py --product-code <ProductCode> --version <Version>The script writes API inventory artifacts under the skill output directory.
Output policy
If you need to save responses or generated artifacts, write them under: output/aliyun-hbr-backup/
Validation
mkdir -p output/aliyun-hbr-backup
for f in skills/backup/aliyun-hbr-backup/scripts/*.py; do
python3 -m py_compile "$f"
done
echo "py_compile_ok" > output/aliyun-hbr-backup/validate.txtPass criteria: command exits 0 and output/aliyun-hbr-backup/validate.txt is generated.
Output And Evidence
- Save artifacts, command outputs, and API response summaries under
output/aliyun-hbr-backup/. - Include key parameters (region/resource id/time range) in evidence files for reproducibility.
Prerequisites
- Configure least-privilege Alibaba Cloud credentials before execution.
- Prefer environment variables:
ALIBABACLOUD_ACCESS_KEY_ID,ALIBABACLOUD_ACCESS_KEY_SECRET, optionalALIBABACLOUD_REGION_ID. - If region is unclear, ask the user before running mutating operations.
References
- Sources:
references/sources.md
interface:
display_name: "Alibaba Cloud Backup HBR"
short_description: "Cloud Backup vault and job workflows"
default_prompt: "Use $aliyun-hbr-backup to complete this backup task on Alibaba Cloud."
Sources
- OpenAPI product page:
https://api.aliyun.com/product/hbr - API list (metadata):
https://api.aliyun.com/meta/v1/products/hbr/versions/2017-09-08/api-docs.json - API definition (single API):
https://api.aliyun.com/meta/v1/products/hbr/versions/2017-09-08/apis/{ApiName}/api.json
#!/usr/bin/env python3
"""Fetch OpenAPI metadata API list for one product/version and save to output/.
Env:
- OPENAPI_META_TIMEOUT (seconds, default: 20)
"""
from __future__ import annotations
import argparse
import json
import os
import pathlib
import urllib.request
DEFAULT_PRODUCT_CODE = "hbr"
DEFAULT_VERSION = "2017-09-08"
OUTPUT_DIR = pathlib.Path("output/aliyun-hbr-backup")
def fetch_json(url: str, timeout: int) -> dict:
req = urllib.request.Request(url, headers={"User-Agent": "codex-skill"})
with urllib.request.urlopen(req, timeout=timeout) as resp:
return json.loads(resp.read().decode("utf-8"))
def main() -> None:
parser = argparse.ArgumentParser()
parser.add_argument("--product-code", default=DEFAULT_PRODUCT_CODE)
parser.add_argument("--version", default=DEFAULT_VERSION)
parser.add_argument("--output-dir", default=str(OUTPUT_DIR))
args = parser.parse_args()
timeout = int(os.getenv("OPENAPI_META_TIMEOUT", "20"))
output_dir = pathlib.Path(args.output_dir)
output_dir.mkdir(parents=True, exist_ok=True)
url = (
f"https://api.aliyun.com/meta/v1/products/{args.product_code}"
f"/versions/{args.version}/api-docs.json"
)
payload = fetch_json(url, timeout)
raw_apis = payload.get("apis", {})
if isinstance(raw_apis, dict):
api_names = sorted(raw_apis.keys())
elif isinstance(raw_apis, list):
names = []
for item in raw_apis:
if isinstance(item, dict):
name = item.get("name") or item.get("apiName")
if name:
names.append(name)
elif isinstance(item, str):
names.append(item)
api_names = sorted(set(names))
else:
api_names = []
json_file = output_dir / f"{args.product_code}_{args.version}_api_docs.json"
md_file = output_dir / f"{args.product_code}_{args.version}_api_list.md"
json_file.write_text(json.dumps(payload, ensure_ascii=False, indent=2), encoding="utf-8")
md_lines = [
f"# {args.product_code} {args.version} API List",
"",
f"- Source: {url}",
f"- API count: {len(api_names)}",
"",
]
md_lines.extend([f"- `{name}`" for name in api_names])
md_file.write_text("\n".join(md_lines) + "\n", encoding="utf-8")
print(f"Saved: {json_file}")
print(f"Saved: {md_file}")
if __name__ == "__main__":
main()
Related skills
How it compares
Run alicloud-ai-audio-asr-test before aliyun-qwen-asr when you only need to prove API keys and the minimal request path work, not full transcript features.
FAQ
What command does alicloud-ai-audio-asr-test recommend?
alicloud-ai-audio-asr-test recommends `python skills/ai/audio/aliyun-qwen-asr/scripts/transcribe_audio.py --audio https://dashscope.oss-cn-beijing.aliyuncs.com/audios/welcome.mp3 --model qwen3-asr-flash --print-response` to verify the non-realtime ASR chain end to end.
Is alicloud-ai-audio-asr-test a production transcription tool?
No. alicloud-ai-audio-asr-test is a minimal smoke harness that confirms credentials and request formatting work. Use the aliyun-qwen-asr skill for real transcription, timestamps, and async long-file jobs.
What should alicloud-ai-audio-asr-test output look like?
alicloud-ai-audio-asr-test expects a dated result noting the skill path, pass or fail conclusion, request summary, response summary, and exact error text on failure—without inventing missing parameters.