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/aliyun-opensearch-search

Use when working with OpenSearch vector search edition via the Python SDK (ha3engine) to push documents and run HA/SQL searches. Ideal for RAG and vector retrieval pipelines in Claude Code/Codex.

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$ npx -y skills add cinience/alicloud-skills --skill aliyun-opensearch-search --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/aliyun-opensearch-search

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Use when working with OpenSearch vector search edition via the Python SDK (ha3engine) to push documents and run HA/SQL searches. Ideal for RAG and vector retrieval pipelines in Claude Code/Codex.

SKILL.md

aliyun-opensearch-search.SKILL.md
name: aliyun-opensearch-search
description: Use when working with OpenSearch vector search edition via the Python SDK (ha3engine) to push documents and run HA/SQL searches. Ideal for RAG and vector retrieval pipelines in Claude Code/Codex.
version: 1.0.0

Category: provider

OpenSearch Vector Search Edition

Use the ha3engine SDK to push documents and execute HA/SQL searches. This skill focuses on API/SDK usage only (no console steps).

Prerequisites

  • Install SDK (recommended in a venv to avoid PEP 668 limits):
python3 -m venv .venv
. .venv/bin/activate
python -m pip install alibabacloud-ha3engine
  • Provide connection config via environment variables:
  • `OPENSEARCH_ENDPOINT` (API domain)
  • `OPENSEARCH_INSTANCE_ID`
  • `OPENSEARCH_USERNAME`
  • `OPENSEARCH_PASSWORD`
  • `OPENSEARCH_DATASOURCE` (data source name)
  • `OPENSEARCH_PK_FIELD` (primary key field name)

Quickstart (push + search)

import os
from alibabacloud_ha3engine import models, client
from Tea.exceptions import TeaException, RetryError

cfg = models.Config(
    endpoint=os.getenv("OPENSEARCH_ENDPOINT"),
    instance_id=os.getenv("OPENSEARCH_INSTANCE_ID"),
    protocol="http",
    access_user_name=os.getenv("OPENSEARCH_USERNAME"),
    access_pass_word=os.getenv("OPENSEARCH_PASSWORD"),
)
ha3 = client.Client(cfg)

def push_docs():
    data_source = os.getenv("OPENSEARCH_DATASOURCE")
    pk_field = os.getenv("OPENSEARCH_PK_FIELD", "id")

    documents = [
        {"fields": {"id": 1, "title": "hello", "content": "world"}, "cmd": "add"},
        {"fields": {"id": 2, "title": "faq", "content": "vector search"}, "cmd": "add"},
    ]
    req = models.PushDocumentsRequestModel({}, documents)
    return ha3.push_documents(data_source, pk_field, req)


def search_ha():
    # HA query example. Replace cluster/table names as needed.
    query_str = (
        "config=hit:5,format:json,qrs_chain:search"
        "&&query=title:hello"
        "&&cluster=general"
    )
    ha_query = models.SearchQuery(query=query_str)
    req = models.SearchRequestModel({}, ha_query)
    return ha3.search(req)

try:
    print(push_docs().body)
    print(search_ha())
except (TeaException, RetryError) as e:
    print(e)

Script quickstart

python skills/ai/search/aliyun-opensearch-search/scripts/quickstart.py

Environment variables:

  • `OPENSEARCH_ENDPOINT`
  • `OPENSEARCH_INSTANCE_ID`
  • `OPENSEARCH_USERNAME`
  • `OPENSEARCH_PASSWORD`
  • `OPENSEARCH_DATASOURCE`
  • `OPENSEARCH_PK_FIELD` (optional, default `id`)
  • `OPENSEARCH_CLUSTER` (optional, default `general`)

Optional args: `--cluster`, `--hit`, `--query`.

SQL-style search

from alibabacloud_ha3engine import models

sql = "select * from <indexTableName>&&kvpair=trace:INFO;formatType:json"
sql_query = models.SearchQuery(sql=sql)
req = models.SearchRequestModel({}, sql_query)
resp = ha3.search(req)
print(resp)

Notes for Claude Code/Codex

  • Use `push_documents` for add/delete updates.
  • Large query strings (>30KB) should use the RESTful search API.
  • HA queries are fast and flexible for vector + keyword retrieval; SQL is helpful for structured data.

Error handling

  • Auth errors: verify username/password and instance access.
  • 4xx on push: check schema fields and `pk_field` alignment.
  • 5xx: retry with backoff.

Validation

mkdir -p output/aliyun-opensearch-search
for f in skills/ai/search/aliyun-opensearch-search/scripts/*.py; do
  python3 -m py_compile "$f"
done
echo "py_compile_ok" > output/aliyun-opensearch-search/validate.txt

Pass criteria: command exits 0 and `output/aliyun-opensearch-search/validate.txt` is generated.

Output And Evidence

  • Save artifacts, command outputs, and API response summaries under `output/aliyun-opensearch-search/`.
  • Include key parameters (region/resource id/time range) in evidence files for reproducibility.

Workflow

1) Confirm user intent, region, identifiers, and whether the operation is read-only or mutating. 2) Run one minimal read-only query first to verify connectivity and permissions. 3) Execute the target operation with explicit parameters and bounded scope. 4) Verify results and save output/evidence files.

References

  • SDK package: `alibabacloud-ha3engine`
  • Demos: data push and HA/SQL search demos in OpenSearch docs
  • Source list: `references/sources.md`
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