
Alicloud Ai Misc Crawl And Skill
- 267 installs
- 396 repo stars
- Updated July 18, 2026
- cinience/alicloud-skills
alicloud-ai-misc-crawl-and-skill is a cinience alicloud-skills agent skill that crawls Alibaba Model Studio model pages and regenerates skills/ai skills from discovered APIs and SDK metadata for developers maintaining Al
About
alicloud-ai-misc-crawl-and-skill is a cinience/alicloud-skills task skill—catalog id alicloud-ai-misc-crawl-and-skill, source name aliyun-modelstudio-crawl-and-skill—that refreshes Alibaba Cloud Model Studio coverage for coding agents. The three-step workflow crawls the models page with npx @just-every/crawl, rebuilds a structured summary via refresh_models_summary.py, then regenerates skills under skills/ai/** using refresh_alicloud_skills.py. Outputs include alicloud-model-studio-models.md raw crawl, output/alicloud-model-studio-models-summary.md, output/alicloud-model-studio-models.json structured model list, output/alicloud-model-studio-skill-scan.md coverage report, and updated skills/ai/** generated skills. Prerequisites are Node.js for npx, Python 3, and network access. Developers reach for alicloud-ai-misc-crawl-and-skill when the Model Studio models list or generated skills must be updated without inventing model IDs or API endpoints absent from the crawled page.
- Doc and sample crawling for Alibaba AI
- Skill scaffolding from API metadata
- SDK snippet extraction workflows
- Reusable agent tool generation
- Faster provider-specific skill authoring
Alicloud Ai Misc Crawl And Skill by the numbers
- 267 all-time installs (skills.sh)
- Ranked #156 of 782 Skill Development skills by installs in the Skillselion catalog
- Data as of Aug 5, 2026 (Skillselion catalog sync)
npx skills add https://github.com/cinience/alicloud-skills --skill alicloud-ai-misc-crawl-and-skillAdd your badge
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| Installs | 267 |
|---|---|
| repo stars | ★ 396 |
| Last updated | July 18, 2026 |
| Repository | cinience/alicloud-skills ↗ |
How do you regenerate Alibaba Cloud agent skills from docs?
Crawl Alibaba AI docs and samples, then scaffold agent skills from discovered APIs, SDK snippets, and service metadata for faster Claude Code automation.
Who is it for?
Developers maintaining cinience/alicloud-skills who need automated Model Studio doc crawls and skills/ai/** regeneration when Alibaba APIs or model lists change.
Skip if: Application teams consuming finished alicloud-skills integrations who do not need to crawl docs or regenerate the skill catalog from source pages.
When should I use this skill?
A maintainer asks to refresh Model Studio model crawls, regenerate alicloud skills/ai entries, or update generated summaries after Alibaba documentation changes.
What you get
Crawled models markdown, structured JSON model list, skill coverage scan report, and regenerated skills/ai/** SKILL.md tree.
- Structured models JSON
- Skill coverage scan report
- Regenerated skills/ai/** catalog
By the numbers
- 3-step crawl, summarize, and regenerate workflow
- 4 output artifact types including JSON model list and skill scan report
Files
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)
npx -y @just-every/crawl \"https://help.aliyun.com/zh/model-studio/models\" > alicloud-model-studio-models.md2) Rebuild summary (models + API/usage links)
python3 skills/ai/misc/alicloud-ai-misc-crawl-and-skill/scripts/refresh_models_summary.py3) Regenerate skills (creates/updates skills/ai/**)
python3 skills/ai/misc/alicloud-ai-misc-crawl-and-skill/scripts/refresh_alicloud_skills.pyOutputs
alicloud-model-studio-models.md: raw crawl outputoutput/alicloud-model-studio-models-summary.md: cleaned summaryoutput/alicloud-model-studio-models.json: structured model listoutput/alicloud-model-studio-skill-scan.md: skill coverage reportskills/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, andREADME.zh-TW.mdif skills list changed.
Validation
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.txtPass 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
interface:
display_name: "Alibaba Cloud AI Misc Crawl And Skill"
short_description: "Model discovery and skill refresh workflows"
default_prompt: "Use $alicloud-ai-misc-crawl-and-skill to complete this ai/misc task on Alibaba Cloud."
官方文档来源(用于后续更新) ============================
- https://help.aliyun.com/zh/model-studio/models
#!/usr/bin/env python3
"""Analyze Model Studio models summary and suggest skill coverage.
Inputs:
- output/alicloud-model-studio-models.json
Outputs:
- output/alicloud-model-studio-skill-scan.md
"""
from __future__ import annotations
import json
from pathlib import Path
ROOT = Path(__file__).resolve().parents[5]
MODELS_JSON = ROOT / "output" / "alicloud-model-studio-models.json"
OUTPUT_MD = ROOT / "output" / "alicloud-model-studio-skill-scan.md"
KEYWORDS = {
"image": ["image", "图像", "img", "vision"],
"video": ["video", "视频", "i2v", "t2v"],
"audio": ["audio", "语音", "tts", "speech"],
"asr": ["asr", "语音识别", "转写", "stt"],
"embedding": ["embedding", "向量", "embed"],
"rerank": ["rerank", "重排"],
"llm": ["llm", "qwen", "chat", "对话", "文本生成"],
}
KNOWN_SKILLS = {
"image": "skills/ai/image/alicloud-ai-image-qwen-image",
"video": "skills/ai/video/alicloud-ai-video-wan-video",
"audio": "skills/ai/audio/alicloud-ai-audio-tts",
"embedding": "skills/ai/search/alicloud-ai-search-text-embedding",
"rerank": "skills/ai/search/alicloud-ai-search-rerank",
"asr": "skills/ai/audio/alicloud-ai-audio-asr",
"llm": "(missing)",
}
def classify(name: str) -> set[str]:
name_l = (name or "").lower()
hits = set()
for k, words in KEYWORDS.items():
if any(w in name_l for w in words):
hits.add(k)
return hits
def main() -> None:
if not MODELS_JSON.exists():
raise SystemExit(f"Missing input: {MODELS_JSON}. Run refresh_models_summary.py first.")
data = json.loads(MODELS_JSON.read_text(encoding="utf-8"))
models = data.get("models", [])
buckets = {k: [] for k in KEYWORDS}
unknown = []
for m in models:
name = m.get("name") or m.get("model_id") or m.get("desc") or ""
hits = classify(name)
if not hits:
unknown.append(m)
continue
for h in hits:
buckets[h].append(m)
lines = ["# Model Studio 技能覆盖扫描", "", f"- 模型总数: {len(models)}", ""]
lines.append("## 覆盖建议")
for k in KEYWORDS:
lines.append(f"- {k}: {KNOWN_SKILLS.get(k, '(unknown)')}")
lines.append("")
lines.append("## 分组统计")
for k in KEYWORDS:
lines.append(f"- {k}: {len(buckets[k])}")
if unknown:
lines.append("")
lines.append("## 未分类模型")
for m in unknown[:50]:
lines.append(f"- {m.get('name')} | {m.get('url')}")
if len(unknown) > 50:
lines.append(f"- ... {len(unknown) - 50} more")
OUTPUT_MD.write_text("\n".join(lines) + "\n", encoding="utf-8")
print(f"Saved: {OUTPUT_MD}")
if __name__ == "__main__":
main()
#!/usr/bin/env python3
"""Build a concise summary from the Model Studio models crawl markdown.
Input:
- alicloud-model-studio-models.md (from npx @just-every/crawl)
Outputs:
- output/alicloud-model-studio-models-summary.md
- output/alicloud-model-studio-models.json
"""
from __future__ import annotations
import json
import re
import urllib.parse
from pathlib import Path
ROOT = Path(__file__).resolve().parents[5]
RAW_MD = ROOT / "alicloud-model-studio-models.md"
OUTPUT_DIR = ROOT / "output"
LINK_RE = re.compile(r"\[([^\]]+)\]\((https?://[^)]+)\)")
MODEL_ID_RE = re.compile(r"[?&]modelId=([^&]+)")
BOLD_RE = re.compile(r"\*\*([^*]{2,50})\*\*")
STOPWORDS = {
"中国内地",
"全球",
"国际",
"美国部署模式",
"旗舰模型",
"最大上下文长度",
"最低输入价格",
"最低输出价格",
"每百万 Token",
"Token数",
"Token 数",
"Token",
"输入价格",
"输出价格",
}
def main() -> None:
if not RAW_MD.exists():
raise SystemExit(f"Missing input: {RAW_MD}")
lines = RAW_MD.read_text(encoding="utf-8", errors="ignore").splitlines()
items = []
seen_ids = set()
for line in lines:
for _, url in LINK_RE.findall(line):
match = MODEL_ID_RE.search(url)
if not match:
continue
model_id = urllib.parse.unquote(match.group(1).strip())
if model_id in seen_ids:
continue
seen_ids.add(model_id)
raw = line.strip()
# Try to extract a short description from the line (before the first link separator).
desc = raw.split("|", 1)[0].strip()
desc = re.sub(r"\[.*?\]\(.*?\)", "", desc).strip()
items.append(
{
"model_id": model_id,
"url": url.strip(),
"desc": desc,
"raw": raw,
}
)
# Add bold model names as additional candidates (no model_id).
seen_names = set()
for line in lines:
for name in BOLD_RE.findall(line):
name = name.strip()
if not name or name in STOPWORDS:
continue
if any(w in name for w in ("元", "Token", "价格")):
continue
if name.isdigit():
continue
if name in seen_names:
continue
seen_names.add(name)
items.append({"model_id": None, "url": None, "desc": name, "raw": line.strip()})
OUTPUT_DIR.mkdir(parents=True, exist_ok=True)
json_path = OUTPUT_DIR / "alicloud-model-studio-models.json"
md_path = OUTPUT_DIR / "alicloud-model-studio-models-summary.md"
json_path.write_text(json.dumps({"count": len(items), "models": items}, ensure_ascii=False, indent=2), encoding="utf-8")
md_lines = ["# Model Studio 模型清单(简表)", "", f"- 总数: {len(items)}", ""]
for item in items:
if item.get("model_id"):
label = item.get("desc") or item.get("model_id")
md_lines.append(f"- `{item['model_id']}` {label} ({item['url']})")
else:
md_lines.append(f"- {item.get('desc')}")
md_path.write_text("\n".join(md_lines) + "\n", encoding="utf-8")
print(f"Saved: {md_path}")
print(f"Saved: {json_path}")
if __name__ == "__main__":
main()
Related skills
How it compares
Use alicloud-ai-misc-crawl-and-skill to maintain the alicloud-skills catalog; pick individual alicloud service skills when integrating one Alibaba API without regenerating the full skills tree.
FAQ
What does alicloud-ai-misc-crawl-and-skill output after a run?
alicloud-ai-misc-crawl-and-skill writes raw crawl markdown, a cleaned summary, structured JSON model list, a skill coverage scan report, and regenerated skills under skills/ai/**. Maintainers should update README files if the skills list changes.
What prerequisites does alicloud-ai-misc-crawl-and-skill need?
alicloud-ai-misc-crawl-and-skill requires Node.js for npx crawling, Python 3 for refresh scripts, and network access to the Alibaba Model Studio models documentation page before regeneration begins.