Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add cinience/alicloud-skills --skill aliyun-opensearch-searchgit clone --depth 1 https://github.com/cinience/alicloud-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/cinience/alicloud-skills/aliyun-opensearch-search)<a href="https://agentmods.dev/skills/cinience/alicloud-skills/aliyun-opensearch-search"><img src="https://agentmods.dev/badge/skills/cinience/alicloud-skills/aliyun-opensearch-search/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/cinience/alicloud-skills/aliyun-opensearch-search"><img src="https://agentmods.dev/badge/skills/cinience/alicloud-skills/aliyun-opensearch-search.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00050 | $0.01121 |
| Opus 5 | $0.00025 | $0.00561 |
| Sonnet 5 | $0.00010 | $0.00224 |
| Haiku 4.5 | $0.00005 | $0.00112 |
Grade A, and why
aliyun-opensearch-search scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 13d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 148 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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_IDOPENSEARCH_USERNAMEOPENSEARCH_PASSWORDOPENSEARCH_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
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 13d ago First seen · 148 lines · 50 tokens per session scan A fbc378c4fda4
aliyun-opensearch-search is a skill published in the GitHub repository cinience/alicloud-skills (396 stars, last pushed 1mo ago), licensed MIT. It adds 50 tokens to every session and 1,121 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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