Skill: sdk-team/alibabacloud-milvus-manage (version 0.0.3)

--- name: alibabacloud-milvus-manage description: > 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. license: MIT AND Apache-2.0 compatibility: > Control-plane requires Alibaba Cloud CLI (`aliyun` >= 3.3.3) with valid credentials; every aliyun CLI call must include `--user-agent AlibabaCloud-Agent-Skills/alibabacloud-milvus-manage`, and Milvus calls must use `--force`. Data-plane requires Python 3.8+ and `pymilvus`. Works on macOS and Linux. metadata: domain: vector-database owner: milvus-team data-plane-author: jinchen allowed-tools: Bash Read Write --- # 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": [REDACTED_SECRET]}` 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": [REDACTED_SECRET] } client = MilvusClient( uri="<USER_URI>", [REDACTED_SECRET]", grpc_options=PYMILVUS_GRPC_OPTIONS, ) ``` - Every `MilvusClient(...)` and `connections.connect(...)` example must pass [REDACTED_SECRET]. - Do not emit `pymilvus` SDK connection code without [REDACTED_SECRET]. For async usage, schema details, and deployment-specific patterns, load the relevant reference doc. ### Data Safety And Correctness - Never generate fake or placeholder vectors. Always use a real embedding model. - The query embedding model must match the model used to create stored vectors. - Vector dimensions must exactly match the collection schema. - A collection must be loaded before search or query. - Confirm destructive operations such as `drop_collection`, `drop_database`, or large deletes before executing. - Prefer `AUTOINDEX` unless the user has explicit performance requirements. ### Minimal Workflow For most SDK tasks: 1. load [references/collection.md](references/collection.md) for schema and collection operations, 2. load [references/vector.md](references/vector.md) for insert/search/query/delete patterns, 3. load [references/index.md](references/index.md) if the user cares about index type, metric, or tuning, 4. add partition/database/RBAC references only if the task actually needs them. ### Common Patterns - quick prototype collection: [references/collection.md](references/collection.md) - vector CRUD and similarity search: [references/vector.md](references/vector.md) - hybrid search or full-text search: [references/vector.md](references/vector.md) - RAG / semantic retrieval patterns: [references/patterns.md](references/patterns.md) - index tuning: [references/index.md](references/index.md) ## Suggested Response Flow ### If control-plane 1. Confirm region and target instance scope. 2. Read the matching control-plane reference. 3. Run the command with the correct parameter mode. 4. Report the key fields, next state, and any follow-up wait conditions. ### If data-plane 1. Ask for connection details first. 2. Read only the references needed for the requested SDK task. 3. Write or explain `pymilvus` code with real embeddings, real connection placeholders, and [REDACTED_SECRET]. 4. Call out schema, load-state, index, and dimension pitfalls if they matter. ## Reference Map - [references/getting-started.md](references/getting-started.md): first Milvus instance from scratch - [references/instance-lifecycle.md](references/instance-lifecycle.md): create, inspect, scale, rename, release - [references/operations.md](references/operations.md): config, network, ACL, inspection, troubleshooting - [references/create-params.md](references/create-params.md): create body fields and component templates - [references/api-reference.md](references/api-reference.md): raw API signatures and return fields - [references/collection.md](references/collection.md): schema and collection lifecycle - [references/vector.md](references/vector.md): insert, search, hybrid search, BM25, iterators - [references/index.md](references/index.md): index types and metric guidance - [references/partition.md](references/partition.md): partition operations - [references/database.md](references/database.md): database operations - [references/user-role.md](references/user-role.md): users, roles, privileges - [references/patterns.md](references/patterns.md): RAG and semantic search patterns - [references/ram-policies.md](references/ram-policies.md): IAM/RAM policies


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)