alibabacloud-milvus-manage
Alibaba Cloud Milvus full-stack Skill for two planes: control-plane instance management via aliyun CLI, and data-plane Milvus operations via pymilvus. Use when users want to create, inspect, scale, configure, network-enable, or whitelist Alibaba Cloud Milvus instances; or connect to Milvus and perform collection management, vector insert/search, hybrid search, full-text search, index management, partition/database management, or RBAC with Python.
What this skill does
# Alibaba Cloud Milvus Full-Stack Skill
## Prerequisites
**[MUST] CLI User-Agent** — Every `aliyun` CLI command invocation must include:
`--user-agent AlibabaCloud-Agent-Skills/alibabacloud-milvus-manage`
**[MUST] PyMilvus User-Agent** — Every `pymilvus` SDK connection must include:
`grpc_options={"grpc.primary_user_agent": "AlibabaCloud-Agent-Skills/alibabacloud-milvus-manage"}`
Alibaba Cloud CLI version must be `>= 3.3.3`.
Handle two distinct planes:
- **Control-plane**: manage Alibaba Cloud managed Milvus instances with `aliyun` CLI.
- **Data-plane**: operate Milvus with `pymilvus` Python code.
Treat `SKILL.md` as the router. Load `references/*.md` for detailed commands, parameters, and examples.
## Scope
Use this skill for:
- Alibaba Cloud managed Milvus instance lifecycle: create, inspect, scale, rename, configure, network, whitelist.
- Milvus Python SDK workflows with `pymilvus`: connect, collections, vectors, search, indexes, partitions, databases, RBAC.
- Retrieval use cases built on Milvus: semantic search, hybrid search, full-text search, RAG patterns.
Do not use this skill for:
- self-hosted Milvus deployment on Docker, Helm, Kubernetes, or Milvus Operator,
- Milvus Java / Go / Node SDKs,
- other Alibaba Cloud products such as ECS, RDS, OSS, EMR, Kafka, StarRocks,
- other vector databases such as Zilliz Cloud, Pinecone, Qdrant, or Weaviate.
## Route The Request
### Control-plane
Route here when the user asks about:
- creating, scaling, renaming, or inspecting a Milvus instance,
- connection address, component spec, configuration, public network, whitelist,
- VPC/VSwitch prerequisites for Alibaba Cloud Milvus,
- Milvus REST-style CLI APIs, creation parameters, or control-plane troubleshooting.
Read:
- first-time flow: [references/getting-started.md](references/getting-started.md)
- create / list / detail / scale / release: [references/instance-lifecycle.md](references/instance-lifecycle.md)
- config / network / inspection / troubleshooting: [references/operations.md](references/operations.md)
- creation field meanings and templates: [references/create-params.md](references/create-params.md)
- raw API field reference: [references/api-reference.md](references/api-reference.md)
- RAM permissions: [references/ram-policies.md](references/ram-policies.md)
### Data-plane
Route here when the user asks about:
- connecting to Milvus with Python,
- creating collections or schemas,
- inserting, upserting, querying, deleting, or searching vectors,
- hybrid search, BM25 full-text search, iterators, indexes,
- partitions, databases, users, roles, or privileges,
- Milvus-based RAG or semantic retrieval patterns.
Read:
- collection schema and lifecycle: [references/collection.md](references/collection.md)
- vector CRUD, search, hybrid search, full-text search: [references/vector.md](references/vector.md)
- index types and metrics: [references/index.md](references/index.md)
- partitions: [references/partition.md](references/partition.md)
- databases: [references/database.md](references/database.md)
- RBAC: [references/user-role.md](references/user-role.md)
- common solution patterns: [references/patterns.md](references/patterns.md)
## Shared Guardrails
- Decide the plane first. Do not mix control-plane instance operations with data-plane SDK code.
- Confirm destructive actions before execution.
- Validate untrusted user input before passing it into shell commands or code.
- Prefer loading a targeted reference doc instead of keeping large inline examples in this file.
## Control-Plane Rules
### Required Environment
- Reuse the configured `aliyun` profile. Verify credentials are configured before API calls.
- Every `aliyun` CLI invocation must include the required User-Agent flag:
```bash
aliyun ... --user-agent AlibabaCloud-Agent-Skills/alibabacloud-milvus-manage
```
- Milvus OpenAPI calls through `aliyun` must include `--force`.
### Preconditions
Before create or major modify operations:
1. Confirm `RegionId` with the user.
2. Verify VPC and VSwitch resources in that region.
3. For create, record `ZoneId`, `VpcId`, and `VSwitchId`.
4. If the request is ambiguous, ask whether the user wants dev/test standalone or production HA cluster.
Baseline decision rule:
- `standalone_pro` is the default for dev/test.
- HA cluster is for production.
- In HA mode, `streaming`, `data`, `mix_coordinator`, and `query` must use at least 4 CU; `proxy` must use at least 2 CU.
Detailed templates and field definitions live in [references/instance-lifecycle.md](references/instance-lifecycle.md) and [references/create-params.md](references/create-params.md).
### CLI Calling Modes
Use the API's expected parameter mode. Do not improvise.
```bash
# get / delete: business params in URL query
aliyun milvus get "/path?RegionId=<region>&instanceId=<id>" --RegionId <region> --force --user-agent AlibabaCloud-Agent-Skills/alibabacloud-milvus-manage
# post / put with request body: business params in --body JSON
aliyun milvus post "/path?RegionId=<region>" --RegionId <region> --body '{...}' --force --user-agent AlibabaCloud-Agent-Skills/alibabacloud-milvus-manage
# post with query-style flags: business params as --Flag value
aliyun milvus post "/path" --RegionId <region> --InstanceId <id> --force --user-agent AlibabaCloud-Agent-Skills/alibabacloud-milvus-manage
```
Rules:
- Always pass `--RegionId <region>`.
- For `CreateInstance` and `UpdateInstance`, use `--body`.
- For query-style POST APIs such as detail, config, network, ACL, and rename operations, use `--Flag value`.
- Do not put user-provided raw text directly into a shell command unless it has been validated.
### Runtime Safety
- Do not download and execute remote scripts or unaudited dependencies during control-plane work.
- Do not use `eval` or `source` with untrusted input.
- Set reasonable timeouts on CLI calls. Prefer short timeouts for reads and bounded polling for long-running async operations.
- For list APIs, do not trust `total` blindly; inspect the returned array.
- Read the full error message before retrying. Automatic retry is appropriate for throttling, not for arbitrary failures.
### Forbidden Operations
- **Instance deletion (DeleteInstance) is strictly forbidden through this Skill.** If the user requests to delete/release a Milvus instance, do **not** execute the Milvus delete command through `aliyun` CLI. Instead, instruct the user to delete the instance via the [Alibaba Cloud Milvus Console](https://milvus.console.aliyun.com/#/overview).
### Destructive Operations
Require explicit confirmation before:
- modifying instance config,
- disabling public network access.
Use this template:
> About to execute: `<API>`, Target: `<InstanceId>`, Impact: `<Description>`. Continue?
For config change and network troubleshooting flows, read [references/operations.md](references/operations.md) or [references/instance-lifecycle.md](references/instance-lifecycle.md) first.
### Output Style
- Summarize instance lists as a compact table.
- Highlight `instanceId`, `instanceName`, `status`, `dbVersion`, `ha`, `paymentType`, and connection endpoints when relevant.
- Convert timestamps to readable time.
- Use `--cli-query` or `jq` to trim noisy payloads when useful.
## Data-Plane Rules
### Connection First
Before writing any `pymilvus` code, ask for:
1. deployment type: Milvus Lite, self-hosted standalone/cluster, or Alibaba Cloud managed instance,
2. URI or endpoint,
3. authentication method and credentials if needed,
4. database name if not using `default`.
Do not assume connection parameters. Use Milvus Lite only when the user explicitly wants local embedded mode.
Minimal connection shape:
```python
from pymilvus import MilvusClient
PYMILVUS_GRPC_OPTIONS = {
"grpc.primary_user_agent": "AlibabaCloud-Agent-Skills/alibabacloud-milvus-manage"
}
client = MilvusClient(
uri="<USER_URI>",
token="<USER_TOKEN>",
grpc_options=PYMILVUS_GRPC_OPTIONS,
)
```
- Every `MiRelated in Cloud & DevOps
appbuilder-action-scaffolder
IncludedCreate, implement, deploy, and debug Adobe Runtime actions with consistent layout, validation, and error handling. Use this skill whenever the user needs to add actions to an App Builder project, understand action structure (params, response format, web/raw actions), configure actions in the manifest, use App Builder SDKs (State, Files, Events, database), deploy and invoke actions via CLI, debug action issues, or implement patterns such as webhook receivers, custom event providers, journaling consumers, large payload redirects, action sequence pipelines, and Asset Compute workers. Also trigger when users mention serverless functions in Adobe context, action logging, IMS authentication for actions, or cron-style scheduled actions.
orchestrating-datacloud
IncludedSalesforce Data Cloud product orchestrator for connect→prepare→harmonize→segment→act workflows. Use this skill when the user needs a multi-step Data Cloud pipeline, cross-phase troubleshooting, or data space and data kit management. TRIGGER when: user needs a multi-step Data Cloud pipeline, asks to set up or troubleshoot Data Cloud across phases, manages data spaces or data kits, or wants a cross-phase sf data360 workflow. DO NOT TRIGGER when: work is isolated to a single phase (use the matching phase-specific skill), the task is STDM/session tracing/parquet telemetry (use observing-agentforce), standard CRM SOQL (use querying-soql), or Apex implementation (use generating-apex).
github-project-automation
IncludedAutomate GitHub repository setup with CI/CD workflows, issue templates, Dependabot, and CodeQL security scanning. Includes 12 production-tested workflows and prevents 18 errors: YAML syntax, action pinning, and configuration. Use when: setting up GitHub Actions CI/CD, creating issue/PR templates, enabling Dependabot or CodeQL scanning, deploying to Cloudflare Workers, implementing matrix testing, or troubleshooting YAML indentation, action version pinning, secrets syntax, runner versions, or CodeQL configuration. Keywords: github actions, github workflow, ci/cd, issue templates, pull request templates, dependabot, codeql, security scanning, yaml syntax, github automation, repository setup, workflow templates, github actions matrix, secrets management, branch protection, codeowners, github projects, continuous integration, continuous deployment, workflow syntax error, action version pinning, runner version, github context, yaml indentation error
sf-datacloud
IncludedSalesforce Data Cloud product orchestrator for connect→prepare→harmonize→segment→act workflows. TRIGGER when: user needs a multi-step Data Cloud pipeline, asks to set up or troubleshoot Data Cloud across phases, manages data spaces or data kits, or wants a cross-phase `sf data360` workflow. DO NOT TRIGGER when: work is isolated to a single phase (use the matching sf-datacloud-* skill), the task is STDM/session tracing/parquet telemetry (use sf-ai-agentforce-observability), standard CRM SOQL (use sf-soql), or Apex implementation (use sf-apex).
fabric-cli
IncludedUse this skill for Fabric.so CLI workflows with the `fabric` terminal command: diagnose/install/login, search or browse a Fabric library, save notes/links/files, create folders, ask the Fabric AI assistant, manage tasks/workspaces, generate shell completion, check subscription usage, produce JSON output, and use Fabric as persistent agent memory. Do not use for Microsoft Fabric/Azure/Power BI `fab`, Daniel Miessler's Fabric framework, Python Fabric SSH, Fabric.js, or textile/fashion fabric.
lark
IncludedLark/Feishu CLI skills: lark-cli operations for docs, markdown, sheets, base, calendar, im, mail, task, okr, drive, wiki, slides, whiteboard, apps, approval, attendance, contact, vc, minutes, event. Use when the user needs to operate Lark/Feishu resources via lark-cli, send messages, manage documents, spreadsheets, calendars, tasks, OKRs, deploy web pages, or any Feishu/Lark workspace operations.