alibabacloud-flink-instance-manage

Q: How do I install alibabacloud-flink-instance-manage?

Run npx skills add https://github.com/aliyun/alibabacloud-aiops-skills --skill alibabacloud-flink-instance-manage in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/alibabacloud-flink-instance-manage/ (personal) or .claude/skills/alibabacloud-flink-instance-manage/ (project).

by aliyunData & Databases

Manage Alibaba Cloud Flink VVP instances and namespaces through create/query operations only. Use when user asks to create or query Flink instances, namespaces, regions, zones, or tags in Chinese or English. Reject Flink SQL/job requests, unrelated cloud services (ECS/Kafka/OSS/DataWorks), and all update/delete operations.

Installs: 234
Last 24h: —
Trending rank: —
Security: Not audited

Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/aliyun/alibabacloud-aiops-skills --skill alibabacloud-flink-instance-manage

01
Install
Run the command in your project. The CLI asks which agents to install for.
02
Describe the task
Ask your agent for something this skill covers. It loads alibabacloud-flink-instance-manage automatically when relevant.
03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

Alibaba Cloud Flink Instance Manage

Operate Alibaba Cloud Flink VVP resources with a strict create/query scope through one wrapper script.

Scope and Entrypoint

Always run operations through:

python scripts/instance_ops.py <command> [options]

Allowed commands: create, create_namespace, describe, describe_regions, describe_zones, describe_namespaces, list_tags
Out of scope: update/delete, Flink SQL/job runtime operations, and non-Flink services

Trigger Rules

Use this skill when prompts are about Flink instance/namespace lifecycle operations.

Positive intent examples:
- "Create a Flink instance in cn-beijing"
- "List Flink instances and status"
- "Describe namespaces for instance f-cn-xxx"
- "查询 Flink 实例标签"
- "Flink 可用区有哪些"
Negative intent examples:
- ECS/Kafka/OSS/DataWorks operations
- Generic questions (weather, translation, etc.)
- Flink SQL / Flink job authoring or runtime tuning
Ambiguous prompts:
- Ask one clarification question: instance/namespace management vs SQL/job operations.

Intent to Command Mapping

User intent	Command
Query all instances in a region	`describe --region_id <REGION>`
Create instance	`create ... --confirm`
Query namespaces under an instance	`describe_namespaces --region_id <REGION> --instance_id <ID>`
Create namespace	`create_namespace ... --confirm`
Query supported regions/zones	`describe_regions` / `describe_zones --region_id <REGION>`
Query tags	`list_tags --region_id <REGION> --resource_type <TYPE> [--resource_ids ...]`

Operating Rules

Confirmation is mandatory for create commands
- create and create_namespace must include --confirm.
Verify create results with read-back
- Do not conclude success from create response alone.
Retry policy is strict
- Maximum 2 attempts for the same command (initial + one corrected retry).
No automatic operation switching
- If an operation fails, do not switch to a different operation without user approval.
Lifecycle target lock
- In create -> create_namespace flow, namespace must target the same newly created InstanceId unless user approves fallback.
Namespace pre-check is required
- Before create_namespace, check instance status/resources and existing namespace allocation.
No secret exposure
- Do not output or request plaintext AK/SK. Use default credential chain guidance.
Do not invent parameters
- Never fabricate VPC/VSwitch/instance IDs.
Keep auditable confirmation evidence
- Lifecycle outputs must contain SafetyCheckRequired or explicit --confirm evidence.
No partial-completion claims for lifecycle flows

For flows requiring both create and create_namespace, overall status can be completed only when both create operations succeed.

No automatic capacity scaling

If create_namespace fails due to insufficient resources, report it clearly and ask user to manually scale resources outside this skill scope.

Execution Protocol

Step 1: Classify request

In-scope create/query for Flink instance/namespace/tag/region/zone -> continue.
Out-of-scope or non-Flink -> reject or route with explanation.

Step 2: Validate parameters

Apply references/parameter-validation.md.
If required parameters are missing, ask user or return clear remediation.

Step 3: Execute command

Query commands: run once unless transient query error.
Create commands: construct final command string and verify --confirm is present before execution.

Step 4: Verify create outcomes

For create: verify with describe --region_id <REGION>.
For create_namespace: verify with describe_namespaces --region_id <REGION> --instance_id <ID>.
Use up to 3 read checks with short backoff before concluding the create is not reflected yet.
For chained create -> create_namespace:
- poll describe --region_id <REGION> on the same InstanceId every 30 seconds
- max wait: 10 minutes
- if still not RUNNING, stop and provide next action (wait/retry later)
- do not switch to another instance without explicit user approval
- if namespace create fails, mark lifecycle chain as failed/not_ready, not completed
- for InsufficientResources, ask user to manually scale the instance and retry later

Key References

Start here:
- references/README.md
- references/quick-start.md
- references/trigger-recognition-guide.md
- references/core-execution-flow.md
- references/command-templates.md

Document	Purpose
`references/parameter-validation.md`	Pre-execution validation checklist
`references/e2e-playbooks.md`	Complete execution sequences
`references/common-failures.md`	Typical mistakes and fixes
`references/required-confirmation-model.md`	Confirmation gate rules
`references/instance-state-management.md`	Instance state and readiness checks
`references/output-handling.md`	Output parsing and retry policy
`references/verification-method.md`	Verification patterns after create/query
`references/acceptance-criteria.md`	Completion checklist for normal operations
`references/python-environment-setup.md`	Python dependency and auth setup
`references/cli-installation-guide.md`	Aliyun CLI diagnostics setup
`references/ram-policies.md`	Required RAM permissions
`references/related-apis.md`	API and command mapping

Output Format

All commands return JSON:

{
  "success": true,
  "operation": "<command>",
  "confirmation_check": {
    "required_flag": "--confirm",
    "provided": true,
    "status": "passed"
  },
  "data": {},
  "request_id": "..."
}

confirmation_check appears on create operations and is used for auditable safety evidence.

Exit codes: 0 = success, 1 = error.

FAQ

What does the alibabacloud-flink-instance-manage skill do?

How do I install alibabacloud-flink-instance-manage?

Run npx skills add https://github.com/aliyun/alibabacloud-aiops-skills --skill alibabacloud-flink-instance-manage in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/alibabacloud-flink-instance-manage/ (personal) or .claude/skills/alibabacloud-flink-instance-manage/ (project).

Which AI agents can use alibabacloud-flink-instance-manage?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is alibabacloud-flink-instance-manage safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains alibabacloud-flink-instance-manage?

It is published by aliyun in aliyun/alibabacloud-aiops-skills. It has 234 recorded installs.

Source

aliyun/alibabacloud-aiops-skills $View on skills.sh

Works with

Claude CodeCodexCursorGitHub CopilotGemini CLIWindsurfClineOpenCodeRoo CodeGooseAmpKiro

Files 22 · 103.8 KB

SKILL.md6.6 KB
assets/requirements.txt134 B
references/acceptance-criteria.md1.8 KB
references/cli-installation-guide.md11.6 KB
references/command-templates.md2.7 KB
references/common-failures.md11.6 KB
references/core-execution-flow.md3.3 KB
references/e2e-playbooks.md5.0 KB
references/evaluation-deliverables.md2.0 KB
references/instance-state-management.md4.8 KB
references/output-handling.md3.2 KB
references/parameter-validation.md3.5 KB
references/python-environment-setup.md4.9 KB
references/quick-start.md2.5 KB
references/ram-policies.md3.1 KB
references/README.md1.1 KB
references/related-apis.md1.1 KB
references/required-confirmation-model.md687 B
references/trigger-recognition-guide.md3.2 KB
references/verification-method.md2.3 KB
scripts/instance_ops.py26.7 KB
scripts/prepare_trigger_batch.py2.1 KB