• Supabase Project: PostgreSQL-based platform for managing coaching domains, learners, and session records
• Vector Knowledge Base: ADBPG instance with vector optimization for RAG-driven coaching
• Seamless Integration: Supabase stores structured data, ADBPG powers intelligent AI coaching dialogue

IMPORTANT: Run

aliyun version

to verify >= 3.3.3. If not installed or version too low, run

curl -fsSL https://aliyuncli.alicdn.com/setup.sh | bash

to update, or see references/cli-installation-guide.md for installation instructions.

Then [MUST] run

aliyun configure set --auto-plugin-install true

to enable automatic plugin installation. [MUST] run

aliyun plugin update

to ensure that any existing plugins on your local machine are always up-to-date.

Every

aliyun

CLI command invocation must include:

--user-agent AlibabaCloud-Agent-Skills/alibabacloud-analyticdb-postgresql-ai-coaching-best-practice

Security Rules:

• NEVER read, echo, or print AK/SK values
• NEVER ask the user to input AK/SK directly
• NEVER print passwords or API Keys in plain text in logs or stdout
• ONLY use

  aliyun configure list

  to check credential status
• When displaying API Keys, show only the first 6 characters +

  ***

  (e.g.,

  sk-abc1***

  )

aliyun configure list

aliyun configure

gpdb:CreateSupabaseProject

gpdb:GetSupabaseProject

gpdb:ModifySupabaseProjectSecurityIps

gpdb:CreateDBInstance

gpdb:DescribeDBInstances

gpdb:ModifySecurityIps

gpdb:DescribeAccounts

gpdb:CreateAccount

gpdb:InitVectorDatabase

gpdb:CreateNamespace

gpdb:CreateDocumentCollection

gpdb:UploadDocumentAsync

gpdb:ChatWithKnowledgeBase

vpc:DescribeVpcs

vpc:DescribeVSwitches

vpc:DescribeVSwitchAttributes

vpc:DescribeNatGateways

vpc:CreateNatGateway

vpc:DescribeEipAddresses

vpc:AllocateEipAddress

vpc:AssociateEipAddress

vpc:CreateSnatEntry

AliyunGPDBFullAccess

AliyunVPCFullAccess

AliyunVPCReadOnlyAccess

[MUST] Permission Failure Handling: When any command fails due to permission errors:

1. Read references/ram-policies.md for required permissions
2. Use

   ram-permission-diagnose

   skill to guide the user
3. Pause and wait until user confirms permissions granted

Smart Defaults Mode: User only needs minimal input (e.g., "北京i"). The agent auto-parses region, discovers VPC/VSwitch, generates passwords, and presents all parameters for one-click confirmation.

Parameters to confirm for this step:

Parameter	Default	Notes
RegionId	Auto-parse	"北京i" → cn-beijing , "上海b" → cn-shanghai , "杭州" → cn-hangzhou , "深圳" → cn-shenzhen
ZoneId	Auto-parse	"北京i" → cn-beijing-i ; query zones when only city provided
VpcId	Auto-discover	Query available VPCs, select one with most available IPs
VSwitchId	Auto-discover	Query VSwitches in target zone, select one with most available IPs
ProjectName	ai_coaching	Supabase project name
AccountPassword	Auto-generate	Password rules: 8-32 chars, at least 3 of uppercase/lowercase/digits/special ( @#$%^&* ), avoid !

Important: Supabase public connection requires a NAT Gateway with SNAT rules in the VPC.

undefined

aliyun gpdb create-supabase-project --profile adbpg \
  --biz-region-id <RegionId> --zone-id <ZoneId> \
  --project-name <ProjectName> --account-password '<AccountPassword>' \
  --security-ip-list "127.0.0.1" --vpc-id <VpcId> --vswitch-id <VSwitchId> \
  --project-spec 2C4G --storage-size 20 --pay-type Postpaid \
  --user-agent AlibabaCloud-Agent-Skills/alibabacloud-analyticdb-postgresql-ai-coaching-best-practice

ProjectId

PublicConnectUrl

Timeout: Supabase project creation takes 5-10 minutes. Poll status until

running

:

bash

aliyun gpdb get-supabase-project --profile adbpg \
  --biz-region-id <RegionId> --project-id <ProjectId> \
  --user-agent AlibabaCloud-Agent-Skills/alibabacloud-analyticdb-postgresql-ai-coaching-best-practice

Check

Status

field. Retry every 30 seconds until

Status=running

.

Note: Steps 2-3 execute on Supabase Project, Steps 4-8 on ADBPG Instance. They are independent.

undefined

Available Instances (Running + Vector Enabled):

#	Instance ID	Spec	Region	Status	Description
1	gp-xxxxx	4C32G	cn-hangzhou	Running	Production
2	gp-yyyyy	8C64G	cn-hangzhou	Running	Testing

Select an instance, or enter "Create New".

• User selects existing → Go to Step 4.3
• User selects "Create New" → Go to Step 4.4
• No qualifying instances → Inform user, go to Step 4.4

Must present configuration and get user confirmation before execution:

💰 Cost note: Creating an instance incurs charges. Release or pause via ADBPG Console when not in use.

cn-hangzhou

cn-hangzhou-j

7.0

StorageElastic

Basic

4C16G

2

50

cloud_essd

enabled

Postpaid

aliyun vpc describe-vswitches --profile adbpg \
  --biz-region-id <RegionId> --zone-id <ZoneId> \
  --user-agent AlibabaCloud-Agent-Skills/alibabacloud-analyticdb-postgresql-ai-coaching-best-practice

aliyun gpdb create-db-instance --profile adbpg \
  --biz-region-id <RegionId> --zone-id <ZoneId> \
  --engine gpdb --engine-version "7.0" \
  --db-instance-mode StorageElastic --db-instance-category Basic \
  --instance-spec 4C16G --seg-node-num 2 \
  --storage-size 50 --seg-storage-type cloud_essd \
  --vpc-id <VpcId> --vswitch-id <VSwitchId> \
  --vector-configuration-status enabled --pay-type Postpaid \
  --user-agent AlibabaCloud-Agent-Skills/alibabacloud-analyticdb-postgresql-ai-coaching-best-practice

Timeout: Instance creation takes 10–15 minutes (max 30 min). Poll every 30–60 seconds:

bash

aliyun gpdb describe-db-instance-attribute --profile adbpg \
  --db-instance-id <DBInstanceId> --region <RegionId> \
  --user-agent AlibabaCloud-Agent-Skills/alibabacloud-analyticdb-postgresql-ai-coaching-best-practice

Wait until

DBInstanceStatus=Running

.

aliyun gpdb describe-accounts --profile adbpg \
  --db-instance-id <DBInstanceId> \
  --user-agent AlibabaCloud-Agent-Skills/alibabacloud-analyticdb-postgresql-ai-coaching-best-practice

Suggest account creation, confirm with user before executing:

• Account name: auto-generate

  ai_coaching_XX

  (XX = random 2-digit number), or user-specified
• Password: auto-generate a compliant password (8-32 chars, at least 3 character types, avoid

  !

  ), or user-specified
• Example:

  Account: ai_coaching_01, Password: Coach3Acc#2x9K

  — Please confirm or provide your own.

⚠️ Important:

• Account name cannot be changed after creation — confirm carefully!
• Password can be reset via console, but save it securely now.
• This account will be used as

  ManagerAccount

  in Step 6.

aliyun gpdb create-account --profile adbpg \
  --db-instance-id <DBInstanceId> --region <RegionId> \
  --account-name <ManagerAccount> --account-password '<ManagerAccountPassword>' \
  --user-agent AlibabaCloud-Agent-Skills/alibabacloud-analyticdb-postgresql-ai-coaching-best-practice

Record:

ManagerAccount

and

ManagerAccountPassword

— these will be used in Step 6 for knowledge base initialization.

Parameters to confirm for this step: Auto-generate the following, present to user for confirmation (user may modify), then execute.

Parameter	Default	Notes
Namespace	ns_coaching	Namespace name, cannot be changed after creation
NamespacePassword	Auto-generate	Namespace password (same password rules); needed for uploads and coaching sessions
Collection	coaching_knowledge	Knowledge base name
EmbeddingModel	text-embedding-v4	Embedding model

ManagerAccount

ManagerAccountPassword

undefined

If the user has domain knowledge documents (PDF/TXT/Markdown, etc.), upload them to the knowledge base to enhance coaching quality. This step can be skipped — proceed directly to Step 8 to start coaching.

aliyun gpdb upload-document-async --profile adbpg \
  --biz-region-id <RegionId> --db-instance-id <DBInstanceId> \
  --namespace <Namespace> --namespace-password '<NamespacePassword>' \
  --collection <Collection> --file-name "domain_knowledge.pdf" \
  --file-url "https://example.com/knowledge.pdf" \
  --document-loader-name ADBPGLoader --chunk-size 500 --chunk-overlap 50 \
  --user-agent AlibabaCloud-Agent-Skills/alibabacloud-analyticdb-postgresql-ai-coaching-best-practice

Optional parameters for this step:

Parameter	Default	Notes
Model	qwen-max	LLM model; use qwen-turbo for daily practice (lower cost)
TopK	5	RAG retrieval count

Note:

SourceCollection

element MUST include

Namespace

field.

aliyun gpdb chat-with-knowledge-base --profile adbpg \
  --biz-region-id <RegionId> --db-instance-id <DBInstanceId> \
  --model-params '{"Model": "<Model>", "Messages": [
    {"Role": "system", "Content": "<system_prompt from coaching_personas>"},
    {"Role": "user", "Content": "<learner message>"}
  ]}' \
  --knowledge-params '{"SourceCollection": [{
    "Collection": "<Collection>", "Namespace": "<Namespace>",
    "NamespacePassword": "<NamespacePassword>", "QueryParams": {"TopK": <TopK>}
  }]}' \
  --user-agent AlibabaCloud-Agent-Skills/alibabacloud-analyticdb-postgresql-ai-coaching-best-practice

1. Supabase project exists and is

   Running

2. ADBPG instance has

   VectorConfigurationStatus=enabled

3. Database tables exist (coaching_domains, coaching_personas, learners, coaching_sessions)
4. Preset coaching domains are queryable

5. ChatWithKnowledgeBase

   returns meaningful coaching responses

1. Supabase for data, KB for AI — Session records through Supabase, coaching dialogue through RAG
2. Coaching persona is key — Quality of

   system_prompt

   determines coaching effectiveness
3. Always store session records — Write every coaching round for review and improvement
4. All operations use

   --profile adbpg

   — Consistent credential management
5. Team isolation with namespaces — Different teams use different

   Namespace

6. TopK recommendation: 5 — Reduces token consumption
7. Daily practice: qwen-turbo (low cost), assessments: qwen-max (high quality)
8. Idempotent write operations — Before any resource creation (CreateSupabaseProject, CreateDBInstance, CreateAccount, CreateNamespace, etc.), always query first (Describe/List) to check if the resource already exists. Only create when the resource does not exist. This prevents duplicate resources on retry