alicloud-ai-recommend-airec

Original source / Raw SKILL.md

---
name: alicloud-ai-recommend-airec
description: Manage Alibaba Cloud AIRec (Airec) via OpenAPI/SDK. Use whenever the user needs recommendation-engine resource operations in Alibaba Cloud, including list/create/update flows, status inspection, and troubleshooting AIRec configuration or runtime issues.
version: 1.0.0
---

Category: service

# AIRec

Use Alibaba Cloud OpenAPI (RPC) with official SDKs or OpenAPI Explorer to manage resources for AIRec.

## 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: `ALICLOUD_ACCESS_KEY_ID` / `ALICLOUD_ACCESS_KEY_SECRET` / `ALICLOUD_REGION_ID`
Region policy: `ALICLOUD_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: `Airec`
- Default API version: `2020-11-26`
- 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:

```bash
python scripts/list_openapi_meta_apis.py
```

Optional overrides:

```bash
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/alicloud-ai-recommend-airec/`

## Validation

```bash
mkdir -p output/alicloud-ai-recommend-airec
for f in skills/ai/recommendation/alicloud-ai-recommend-airec/scripts/*.py; do
  python3 -m py_compile "$f"
done
echo "py_compile_ok" > output/alicloud-ai-recommend-airec/validate.txt
```

Pass criteria: command exits 0 and `output/alicloud-ai-recommend-airec/validate.txt` is generated.

## Output And Evidence

- Save artifacts, command outputs, and API response summaries under `output/alicloud-ai-recommend-airec/`.
- 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: `ALICLOUD_ACCESS_KEY_ID`, `ALICLOUD_ACCESS_KEY_SECRET`, optional `ALICLOUD_REGION_ID`.
- If region is unclear, ask the user before running mutating operations.

## References

- Sources: `references/sources.md`


---

## Referenced Files

> The following files are referenced in this skill and included for context.

### scripts/list_openapi_meta_apis.py

```python
#!/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 = "Airec"
DEFAULT_VERSION = "2020-11-26"
OUTPUT_DIR = pathlib.Path("output/alicloud-ai-recommend-airec")


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()

```

### references/sources.md

```markdown
# Sources

- OpenAPI product page: `https://api.aliyun.com/product/Airec`
- API list (metadata): `https://api.aliyun.com/meta/v1/products/Airec/versions/2020-11-26/api-docs.json`
- API definition (single API): `https://api.aliyun.com/meta/v1/products/Airec/versions/2020-11-26/apis/{ApiName}/api.json`

```



---

## Skill Companion Files

> Additional files collected from the skill directory layout.

### _meta.json

```json
{
  "owner": "cinience",
  "slug": "alicloud-ai-recommend-airec",
  "displayName": "Alicloud Ai Recommend Airec",
  "latest": {
    "version": "1.0.3",
    "publishedAt": 1773221874572,
    "commit": "https://github.com/openclaw/skills/commit/0adb6486d7eefae7250996868913d7cbf037e246"
  },
  "history": [
    {
      "version": "1.0.2",
      "publishedAt": 1770973175802,
      "commit": "https://github.com/openclaw/skills/commit/1ec37134a00e6d57de7aa64a44f565e42127a285"
    },
    {
      "version": "1.0.1",
      "publishedAt": 1770768429994,
      "commit": "https://github.com/openclaw/skills/commit/1683b0b96115f5d69151d5270e4ebe120d75b2c9"
    }
  ]
}

```