Alibaba Cloud AI Misc Crawl And Skill

Model discovery and skill refresh workflows

Category: task

Alibaba Cloud Model Studio Crawl and Skill Generation

Prerequisites

• Node.js (for npx)
• Python 3
• Network access to the models page

Workflow

1. Crawl models page (raw markdown)

bash

npx -y @just-every/crawl \"https://help.aliyun.com/zh/model-studio/models\" > alicloud-model-studio-models.md

2. Rebuild summary (models + API/usage links)

bash

python3 skills/ai/misc/alicloud-ai-misc-crawl-and-skill/scripts/refresh_models_summary.py

3. Regenerate skills (creates/updates skills/ai/**)

bash

python3 skills/ai/misc/alicloud-ai-misc-crawl-and-skill/scripts/refresh_alicloud_skills.py

Outputs

• alicloud-model-studio-models.md: raw crawl output
• output/alicloud-model-studio-models-summary.md: cleaned summary
• output/alicloud-model-studio-models.json: structured model list
• output/alicloud-model-studio-skill-scan.md: skill coverage report
• skills/ai/**: generated skills

Notes

• Do not invent model IDs or API endpoints; only use links present on the models page.
• After regeneration, update README.md, README.en.md, and README.zh-TW.md if skills list changed.

Validation

bash

mkdir -p output/alicloud-ai-misc-crawl-and-skill
for f in skills/ai/misc/alicloud-ai-misc-crawl-and-skill/scripts/*.py; do
  python3 -m py_compile "$f"
done
echo "py_compile_ok" > output/alicloud-ai-misc-crawl-and-skill/validate.txt

Pass criteria: command exits 0 and output/alicloud-ai-misc-crawl-and-skill/validate.txt is generated.

Output And Evidence

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

References

• Source list: references/sources.md