Agent skill

Aliyun Dashvector Search

A skill your agent uses when building vector retrieval with DashVector using the Python SDK.

MITAuto-check passedDatabases

Install Aliyun Dashvector Search

skills CLI

$ npx skills add cinience/alicloud-skills --skill aliyun-dashvector-search -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install cinience/alicloud-skills aliyun-dashvector-search --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/cinience/alicloud-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/ai/search/aliyun-dashvector-search .claude/skills/aliyun-dashvector-search && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Paste into Claude Code

Install the "aliyun-dashvector-search" agent skill from https://github.com/cinience/alicloud-skills/tree/main/skills/ai/search/aliyun-dashvector-search into .claude/skills/aliyun-dashvector-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aliyun-dashvector-search", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/cinience/alicloud-skills/tree/main/skills/ai/search/aliyun-dashvector-search

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add cinience/alicloud-skills --skill aliyun-dashvector-search -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install cinience/alicloud-skills aliyun-dashvector-search --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/cinience/alicloud-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/ai/search/aliyun-dashvector-search .agents/skills/aliyun-dashvector-search && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "aliyun-dashvector-search" agent skill from https://github.com/cinience/alicloud-skills/tree/main/skills/ai/search/aliyun-dashvector-search into .agents/skills/aliyun-dashvector-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aliyun-dashvector-search", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add cinience/alicloud-skills --skill aliyun-dashvector-search -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install cinience/alicloud-skills aliyun-dashvector-search --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/cinience/alicloud-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/ai/search/aliyun-dashvector-search .cursor/skills/aliyun-dashvector-search && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "aliyun-dashvector-search" agent skill from https://github.com/cinience/alicloud-skills/tree/main/skills/ai/search/aliyun-dashvector-search into .cursor/skills/aliyun-dashvector-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aliyun-dashvector-search", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/cinience/alicloud-skills.git --path skills/ai/search/aliyun-dashvector-search

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add cinience/alicloud-skills --skill aliyun-dashvector-search -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install cinience/alicloud-skills aliyun-dashvector-search --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/cinience/alicloud-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/ai/search/aliyun-dashvector-search .gemini/skills/aliyun-dashvector-search && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "aliyun-dashvector-search" agent skill from https://github.com/cinience/alicloud-skills/tree/main/skills/ai/search/aliyun-dashvector-search into .gemini/skills/aliyun-dashvector-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aliyun-dashvector-search", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install cinience/alicloud-skills aliyun-dashvector-search

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add cinience/alicloud-skills --skill aliyun-dashvector-search -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/cinience/alicloud-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/ai/search/aliyun-dashvector-search .github/skills/aliyun-dashvector-search && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "aliyun-dashvector-search" agent skill from https://github.com/cinience/alicloud-skills/tree/main/skills/ai/search/aliyun-dashvector-search into .github/skills/aliyun-dashvector-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aliyun-dashvector-search", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add cinience/alicloud-skills --skill aliyun-dashvector-search -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install cinience/alicloud-skills aliyun-dashvector-search --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/cinience/alicloud-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/ai/search/aliyun-dashvector-search .opencode/skills/aliyun-dashvector-search && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "aliyun-dashvector-search" agent skill from https://github.com/cinience/alicloud-skills/tree/main/skills/ai/search/aliyun-dashvector-search into .opencode/skills/aliyun-dashvector-search/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aliyun-dashvector-search", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: aliyun-dashvector-search
GitHub stars: 397
Token cost: ~990 tokens
SKILL.md length: 265 words
Files: 4 (incl. scripts, references)
Skills in repo: 96
Repo updated: Aug 11, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

A skill your agent uses when building vector retrieval with DashVector using the Python SDK.

Works in 4 steps: Confirm user intent, region,… → Run one minimal read-only query first to… → Execute the target operation with… → …
Building vector retrieval with DashVector using the Python SDK
SKILL.md covers Prerequisites, Normalized operations, Quickstart (Python SDK) and Script quickstart, plus 6 more sections
Runs Python scripts from its folder; calls python3 and python; needs DASHVECTOR_API_KEY

What it does

Aliyun Dashvector Search is an agent skill from cinience/alicloud-skills. Use when building vector retrieval with DashVector using the Python SDK. Use when creating collections, upserting docs, and running similarity search with filters in Claude Code/Codex.

Its SKILL.md is about 990 tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including scripts and reference files (for example `agents/openai.yaml`, `references/sources.md` and `scripts/quickstart.py`).

It sits in Databases, covering Vector databases. It works with Alibaba Cloud and Python. The repository describes itself as: alibaba cloud skills，qwen ，wan and all skills. The licence is MIT.

When your agent uses it

Building vector retrieval with DashVector using the Python SDK
Creating collections
Running similarity search with filters in Claude Code/Codex

Example prompts

“/aliyun-dashvector-search”

Requirements

Python 3
A credential in DASHVECTOR_API_KEY

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

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

What it can do on your machine

Read from SKILL.md and the folder at commit 1818263. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 1 file in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
- python3
- python
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names these keys or tokens, usually read from environment variables:
- DASHVECTOR_API_KEY
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Aliyun Dashvector Search loads about 990 tokens when it runs, and up to ~1k if it reads all its reference files. Until then it costs about 52 tokens; SKILL.md has 265 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~52
When it runs · the whole SKILL.md, loaded when a task matches: ~990
With references · SKILL.md plus every file in references/, read only if the agent opens them: ~1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from cinience/alicloud-skills at commit 1818263, republished under its MIT licence (© cinience). 265 words, ~990 tokens.

Download SKILL.mdSave it as .claude/skills/aliyun-dashvector-search/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.

name: aliyun-dashvector-search
description: Use when building vector retrieval with DashVector using the Python SDK. Use when creating collections, upserting docs, and running similarity search with filters in Claude Code/Codex.
version: 1.0.0

Category: provider

DashVector Vector Search

Use DashVector to manage collections and perform vector similarity search with optional filters and sparse vectors.

Prerequisites

Install SDK (recommended in a venv to avoid PEP 668 limits):

bash

python3 -m venv .venv
. .venv/bin/activate
python -m pip install dashvector

Provide credentials and endpoint via environment variables:
- DASHVECTOR_API_KEY
- DASHVECTOR_ENDPOINT (cluster endpoint)

Normalized operations

Create collection

name (str)
dimension (int)
metric (str: cosine | dotproduct | euclidean)
fields_schema (optional dict of field types)

Upsert docs

docs list of {id, vector, fields} or tuples
Supports sparse_vector and multi-vector collections

Query docs

vector or id (one required; if both empty, only filter is applied)
topk (int)
filter (SQL-like where clause)
output_fields (list of field names)
include_vector (bool)

Quickstart (Python SDK)

python

import os
import dashvector
from dashvector import Doc

client = dashvector.Client(
    api_key=os.getenv("DASHVECTOR_API_KEY"),
    endpoint=os.getenv("DASHVECTOR_ENDPOINT"),
)

# 1) Create a collection
ret = client.create(
    name="docs",
    dimension=768,
    metric="cosine",
    fields_schema={"title": str, "source": str, "chunk": int},
)
assert ret

# 2) Upsert docs
collection = client.get(name="docs")
ret = collection.upsert(
    [
        Doc(id="1", vector=[0.01] * 768, fields={"title": "Intro", "source": "kb", "chunk": 0}),
        Doc(id="2", vector=[0.02] * 768, fields={"title": "FAQ", "source": "kb", "chunk": 1}),
    ]
)
assert ret

# 3) Query
ret = collection.query(
    vector=[0.01] * 768,
    topk=5,
    filter="source = 'kb' AND chunk >= 0",
    output_fields=["title", "source", "chunk"],
    include_vector=False,
)
for doc in ret:
    print(doc.id, doc.fields)

Script quickstart

bash

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

Environment variables:

DASHVECTOR_API_KEY
DASHVECTOR_ENDPOINT
DASHVECTOR_COLLECTION (optional)
DASHVECTOR_DIMENSION (optional)

Optional args: --collection, --dimension, --topk, --filter.

Notes for Claude Code/Codex

Prefer upsert for idempotent ingestion.
Keep dimension aligned to your embedding model output size.
Use filters to enforce tenant or dataset scoping.
If using sparse vectors, pass sparse_vector={token_id: weight, ...} when upserting/querying.

Error handling

401/403: invalid DASHVECTOR_API_KEY
400: invalid collection schema or dimension mismatch
429/5xx: retry with exponential backoff

Validation

bash

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

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

Output And Evidence

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

Workflow

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

References

DashVector Python SDK: Client.create, Collection.upsert, Collection.query
Source list: references/sources.md

Files

SKILL.md and 3 other files (scripts, references) in skills/ai/search/aliyun-dashvector-search of cinience/alicloud-skills.

SKILL.md
agents/openai.yaml
references/sources.md
scripts/quickstart.py

Open the folder on GitHubat commit 1818263

Compare with similar skills

Aliyun Dashvector Search next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Aliyun Dashvector Search compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Aliyun Dashvector Search this skillcinience/alicloud-skills	397	—	~990	Automated safety check: Pass	MIT	1 mo ago
Pinecone Vector DatabaseOrchestra-Research/AI-Research-SKILLs	13k	5 repos	~2k	Automated safety check: Pass	MIT	3 mo ago
Qdrant Vector SearchOrchestra-Research/AI-Research-SKILLs	13k	4 repos	~3.4k	Automated safety check: Pass	MIT	3 mo ago
Ravendbravendb/docs	115	—	~2.3k	Automated safety check: Pass	MIT	today
Mem0 Oss To Platformmem0ai/mem0	67k	—	~2.2k	Automated safety check: Notes	Apache-2.0	today
DBoracle/skills	876	—	~1.4k	Automated safety check: Pass	UPL-1.0	3 days ago

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Works with

Questions about Aliyun Dashvector Search

What does Aliyun Dashvector Search do?

A skill your agent uses when building vector retrieval with DashVector using the Python SDK. Aliyun Dashvector Search is an agent skill from cinience/alicloud-skills. Use when building vector retrieval with DashVector using the Python SDK.

When should I use Aliyun Dashvector Search?

Aliyun Dashvector Search fits situations like: building vector retrieval with DashVector using the Python SDK; creating collections; running similarity search with filters in Claude Code/Codex.

How do I install Aliyun Dashvector Search in Claude Code?

Run `npx skills add cinience/alicloud-skills --skill aliyun-dashvector-search -a claude-code`. Or copy the skill folder (skills/ai/search/aliyun-dashvector-search in cinience/alicloud-skills) into .claude/skills/aliyun-dashvector-search in your project. Claude Code loads it when a task matches its description.

How do I install Aliyun Dashvector Search in Codex?

Run `npx skills add cinience/alicloud-skills --skill aliyun-dashvector-search -a codex`. Or copy the skill folder (skills/ai/search/aliyun-dashvector-search in cinience/alicloud-skills) into .agents/skills/aliyun-dashvector-search in your project. Codex loads it when a task matches its description.

Can I use Aliyun Dashvector Search in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add cinience/alicloud-skills --skill aliyun-dashvector-search -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/aliyun-dashvector-search, .gemini/skills/aliyun-dashvector-search, .github/skills/aliyun-dashvector-search and .opencode/skills/aliyun-dashvector-search in your project.

What does Aliyun Dashvector Search need to run?

Going by SKILL.md and its folder, Aliyun Dashvector Search needs Python for the scripts in its folder, the command-line tools its instructions call (python3 and python) and credentials named DASHVECTOR_API_KEY. Our summary lists: Python 3; A credential in DASHVECTOR_API_KEY.

Does Aliyun Dashvector Search access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Aliyun Dashvector Search safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Aliyun Dashvector Search use?

Aliyun Dashvector Search is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Aliyun Dashvector Search use?

About 990 tokens (SKILL.md is roughly 4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 27 tokens, read only when the agent opens those files.

What are the alternatives to Aliyun Dashvector Search?

Skills that share tags, products or a category with Aliyun Dashvector Search: Pinecone Vector Database (Orchestra-Research/AI-Research-SKILLs, 13k stars), Qdrant Vector Search (Orchestra-Research/AI-Research-SKILLs, 13k stars), Ravendb (ravendb/docs, 115 stars) and Mem0 Oss To Platform (mem0ai/mem0, 67k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Aliyun Dashvector Search?

cinience (a GitHub user) maintains it in cinience/alicloud-skills, which has 397 GitHub stars. The repository holds 96 skills in this directory. The repository was last updated on August 11, 2026.

Source: cinience/alicloud-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Aliyun Dashvector Search

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

DashVector Vector Search

Prerequisites

Normalized operations

Create collection

Upsert docs

Query docs

Quickstart (Python SDK)

Script quickstart

Notes for Claude Code/Codex

Error handling

Validation

Output And Evidence

Workflow

References

Files

Compare with similar skills

Similar skills

More from cinience/alicloud-skills

Related

Questions about Aliyun Dashvector Search