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Coding
Alibaba Cloud AI Recommend AIRec
Manage and verify Alibaba Cloud AIRec resources through OpenAPI, official SDKs, or OpenAPI Explorer.
What it does
Manage Alibaba Cloud AIRec resources through RPC OpenAPI calls using official SDKs or OpenAPI Explorer. The workflow discovers Airec API schemas for version 2020-11-26, confirms region and resource IDs, performs list, configuration, or diagnostic operations, and verifies results with describe/list APIs. Artifacts and API response summaries are saved under output/alicloud-ai-recommend-airec/.
When to use it
- Inventorying AIRec resources
- Creating or updating AIRec configuration
- Checking resource status and troubleshooting
- Discovering Airec APIs and request schemas
The skill document
Category: service
AIRec
Use Alibaba Cloud OpenAPI (RPC) with official SDKs or OpenAPI Explorer to manage resources for AIRec.
Workflow
- Confirm region, resource identifiers, and desired action.
- Discover API list and required parameters (see references).
- Call API with SDK or OpenAPI Explorer.
- Verify results with describe/list APIs.
AccessKey priority (must follow)
- Environment variables:
ALICLOUD_ACCESS_KEY_ID/ALICLOUD_ACCESS_KEY_SECRET/ALICLOUD_REGION_IDRegion policy:ALICLOUD_REGION_IDis an optional default. If unset, decide the most reasonable region for the task; if unclear, ask the user. - 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
- Inventory/list: prefer
List*/Describe*APIs to get current resources. - Change/configure: prefer
Create*/Update*/Modify*/Set*APIs for mutations. - Status/troubleshoot: prefer
Get*/Query*/Describe*StatusAPIs for diagnosis.
Minimal executable quickstart
Use metadata-first discovery before calling business APIs:
python scripts/list_openapi_meta_apis.py
Optional overrides:
python scripts/list_openapi_meta_apis.py --product-code --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
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, optionalALICLOUD_REGION_ID. - If region is unclear, ask the user before running mutating operations.
References
- Sources:
references/sources.md
Questions people ask
- How does it determine which AIRec API and parameters to use?
- It uses OpenAPI metadata to list Airec APIs and retrieve their schemas, defaulting to API version 2020-11-26. A bundled Python script can write the discovered API inventory to the skill output directory.
- Which Alibaba Cloud credentials and region settings does it use?
- It prioritizes ALICLOUD_ACCESS_KEY_ID and ALICLOUD_ACCESS_KEY_SECRET environment variables, with ALICLOUD_REGION_ID as an optional default, then falls back to ~/.alibabacloud/credentials. If the region is unclear, it asks before mutating resources.
- How are operations checked and documented?
- Changes are verified with describe/list APIs. Artifacts, command output, API response summaries, and evidence containing key parameters such as region and resource ID are stored under output/alicloud-ai-recommend-airec/.
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