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Model Studio Skills Minimal Test

Run minimal validation for currently available Model Studio skills in this repo and record results.

Prerequisites

• Install SDK (virtual environment recommended to avoid PEP 668 restrictions):

  python3 -m venv .venv . .venv/bin/activate python -m pip install dashscope

• Configure DASHSCOPE_API_KEY (environment variable preferred; or dashscope_api_key in ~/.alibabacloud/credentials).

Test Matrix (currently supported)

1. Text-to-image → skills/ai/image/alicloud-ai-image-qwen-image/
2. Image editing → skills/ai/image/alicloud-ai-image-qwen-image-edit/
3. Text-to-video / Image-to-video (i2v) → skills/ai/video/alicloud-ai-video-wan-video/
4. Reference-to-video (r2v) → skills/ai/video/alicloud-ai-video-wan-r2v/
5. TTS → skills/ai/audio/alicloud-ai-audio-tts/
6. ASR transcription (non-realtime) → skills/ai/audio/alicloud-ai-audio-asr/
7. Realtime TTS → skills/ai/audio/alicloud-ai-audio-tts-realtime/
8. Voice clone → skills/ai/audio/alicloud-ai-audio-tts-voice-clone/
9. Voice design → skills/ai/audio/alicloud-ai-audio-tts-voice-design/

If new capability tests are needed, create corresponding skill first (use skills/ai/misc/alicloud-ai-misc-crawl-and-skill/ to refresh model list).

Minimal Flow Per Capability

1. Open target sub-skill directory and read SKILL.md.
2. Choose one minimal input example and recommended model.
3. Run SDK call or script.
4. Record model, request summary, response summary, duration, and status.

Result Template

Save as output/alicloud-ai-entry-modelstudio-test-results.md:

# Model Studio Skill Test Results

- Date: YYYY-MM-DD
- Environment: region / API_BASE / auth method

| Capability | Sub-skill | Model | Request summary | Result summary | Status | Notes |
| --- | --- | --- | --- | --- | --- | --- |
| Text-to-image | alicloud-ai-image-qwen-image | <model-id> | ... | ... | pass/fail | ... |
| Image editing | alicloud-ai-image-qwen-image-edit | <model-id> | ... | ... | pass/fail | ... |
| Image-to-video (i2v) | alicloud-ai-video-wan-video | <model-id> | ... | ... | pass/fail | ... |
| Reference-to-video (r2v) | alicloud-ai-video-wan-r2v | <model-id> | ... | ... | pass/fail | ... |
| TTS | alicloud-ai-audio-tts | <model-id> | ... | ... | pass/fail | ... |
| ASR (non-realtime) | alicloud-ai-audio-asr | <model-id> | ... | ... | pass/fail | ... |
| Realtime TTS | alicloud-ai-audio-tts-realtime | <model-id> | ... | ... | pass/fail | ... |
| Voice clone | alicloud-ai-audio-tts-voice-clone | <model-id> | ... | ... | pass/fail | ... |
| Voice design | alicloud-ai-audio-tts-voice-design | <model-id> | ... | ... | pass/fail | ... |

Failure Handling

• If parameters are unclear, check target sub-skill SKILL.md or references/*.md.
• If model is unavailable, refresh model list and retry.
• For auth issues, verify DASHSCOPE_API_KEY (env var or ~/.alibabacloud/credentials).

Validation

mkdir -p output/alicloud-ai-entry-modelstudio-test
echo "validation_placeholder" > output/alicloud-ai-entry-modelstudio-test/validate.txt

Pass criteria: command exits 0 and output/alicloud-ai-entry-modelstudio-test/validate.txt is generated.

Output And Evidence

• Save artifacts, command outputs, and API response summaries under output/alicloud-ai-entry-modelstudio-test/.
• Include key parameters (region/resource id/time range) in evidence files for reproducibility.

Workflow

1. Confirm user intent, region, identifiers, and whether the operation is read-only or mutating.
2. Run one minimal read-only query first to verify connectivity and permissions.
3. Execute the target operation with explicit parameters and bounded scope.
4. Verify results and save output/evidence files.

References

• Source list: references/sources.md

Weekly Installs

171

Repository

cinience/alicloud-skills

GitHub Stars

340

First Seen

13 days ago

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