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Alicloud Ai Recommend Airec

  • 265 installs
  • 396 repo stars
  • Updated July 18, 2026
  • cinience/alicloud-skills

alicloud-ai-recommend-airec is an Alibaba Cloud skills package skill that integrates AiRec recommendation APIs for personalized feeds, product ranking, and behavioral recall in apps, storefronts, and content surfaces.

About

alicloud-ai-recommend-airec is a backend integration skill from cinience/alicloud-skills for Alibaba Cloud AiRec personalization APIs. The skill guides wiring recommendation endpoints for personalized content feeds, product ranking, and behavioral recall across mobile apps, e-commerce storefronts, and media surfaces. Developers reach for alicloud-ai-recommend-airec when adding Alibaba-native recommendation to existing Alibaba Cloud deployments or migrating from manual ranking rules. It focuses on API integration patterns, request schemas, and recall configuration rather than training custom ML models from scratch.

  • AiRec event and behavior ingestion
  • Personalized ranking API integration
  • Recall and filter policy configuration
  • Ecommerce and feed recommendation hooks
  • Real-time inference client patterns

Alicloud Ai Recommend Airec by the numbers

  • 265 all-time installs (skills.sh)
  • Ranked #2,452 of 16,546 AI & Agent Building 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-recommend-airec

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Listed on Skillselion
Installs265
repo stars396
Last updatedJuly 18, 2026
Repositorycinience/alicloud-skills

How do you integrate Alibaba AiRec recommendation APIs?

Integrate Alibaba AiRec recommendation APIs for personalized feeds, product ranking, and behavioral recall in apps, storefronts, and content surfaces.

Who is it for?

Backend engineers on Alibaba Cloud adding AiRec-powered personalization to apps, storefronts, or content feeds.

Skip if: Teams on AWS or GCP only, or projects building fully custom recommendation models without Alibaba AiRec.

When should I use this skill?

A developer integrates Alibaba AiRec APIs for personalized feeds, product ranking, or behavioral recall in production apps.

What you get

AiRec API integration with personalized feed endpoints, product ranking config, and behavioral recall wiring.

  • api integration code
  • ranking config
  • feed endpoint wiring

Files

SKILL.mdMarkdownGitHub ↗

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:

python scripts/list_openapi_meta_apis.py

Optional overrides:

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

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

Related skills

FAQ

What does alicloud-ai-recommend-airec integrate?

The alicloud-ai-recommend-airec skill integrates Alibaba Cloud AiRec recommendation APIs for personalized feeds, product ranking, and behavioral recall in apps, storefronts, and content surfaces on Alibaba Cloud.

When should developers use AiRec versus custom ML models?

Use alicloud-ai-recommend-airec when Alibaba Cloud AiRec managed recommendation fits the stack and speed-to-ship matters. Build custom models when recommendation logic must be fully proprietary outside Alibaba services.

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