Skill: sdk-team/alibabacloud-analyticdb-postgresql-ai-coaching-best-practice (version 0.0.2)

--- name: alibabacloud-analyticdb-postgresql-ai-coaching-best-practice description: | Implement AI Coaching best practices on AnalyticDB for PostgreSQL (ADBPG): Leverage Supabase projects (training data management) + ADBPG instances with vector optimization to build RAG-driven coaching systems that guide users through domain-specific workflows, decision-making, or skill development. Use when: User wants to create Supabase projects (spb-xxx), ADBPG instances (gp-xxx), vector knowledge bases, or RAG-driven coaching systems on ADBPG. Triggers: "Supabase", "ADBPG", "vector database", "knowledge base", "RAG", "AI coaching", "coaching system", "spb-xxx", "gp-xxx" --- # ADBPG AI Coaching Best Practice Build RAG-driven coaching systems using **ADBPG Supabase** (training data management) + **ADBPG Vector Knowledge Base** (RAG-driven intelligent coaching). **Core Capabilities**: - **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 --- ## Pre-check: Aliyun CLI >= 3.3.3 Required > **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](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. --- ## [MUST] CLI User-Agent > **Every `aliyun` CLI command invocation must include:** > `--user-agent AlibabaCloud-Agent-Skills/alibabacloud-analyticdb-postgresql-ai-coaching-best-practice` --- ## [MUST] CLI AI-Mode Configuration At the **start** of the Core Workflow (before any CLI invocation): **[MUST] Enable AI-Mode** — AI-mode is required for Agent Skill execution. Run the following commands before any CLI invocation: ```bash aliyun configure ai-mode enable aliyun configure ai-mode set-user-agent --user-agent [REDACTED_SECRET] ``` **[MUST] Disable AI-Mode at EVERY exit point** — Before delivering the final response for ANY reason, always disable AI-mode first. This applies to ALL exit paths: workflow success, workflow failure, error/exception, user cancellation, session end, or any other scenario where no further CLI commands will be executed. AI-mode is only used for Agent Skill invocation scenarios and MUST NOT remain enabled after the skill stops running. ```bash aliyun configure ai-mode disable ``` --- ## Pre-check: Alibaba Cloud Credentials Required > **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***`) ```bash aliyun configure list ``` **If no valid profile exists, STOP here.** Configure credentials outside of this session via `aliyun configure` or environment variables. --- ## Scenario Description | Scenario | Use Case | Target Users | |----------|----------|--------------| | **Workflow Coaching** | Guide professionals through structured business processes (sales cycles, project management) | Sales teams, project managers | | **Decision Support** | Help engineers evaluate trade-offs and make informed technical decisions | Engineers, architects | | **Skill Development** | Develop communication, negotiation, or technical skills through guided practice | Professionals, new hires | | **Onboarding** | Systematically guide new team members through technical and process onboarding | New employees, mentors | ### Architecture ``` User (Web / Terminal / Agent) │ ┌──────┴──────┐ v v ┌─────────────┐ ┌────────────────────────┐ │ Supabase │ │ Agent Mode │ │ (spb-xxx) │ │ ChatWithKnowledgeBase │ │ - Domains │ └───────────┬────────────┘ │ - Sessions │ │ └──────┬──────┘ │ v v ┌────────────────────────────────────────┐ │ ADBPG Instance (gp-xxx) + KB │ │ Domain Knowledge + RAG + LLM │ └────────────────────────────────────────┘ ``` --- ## RAM Policy ### Required Permissions | Operation | RAM Permission | |-----------|----------------| | Supabase Project Management | `gpdb:CreateSupabaseProject`, `gpdb:GetSupabaseProject`, `gpdb:ModifySupabaseProjectSecurityIps` | | ADBPG Instance Management | `gpdb:CreateDBInstance`, `gpdb:DescribeDBInstances`, `gpdb:ModifySecurityIps` | | Account Management | `gpdb:DescribeAccounts`, `gpdb:CreateAccount` | | Knowledge Base Operations | `gpdb:InitVectorDatabase`, `gpdb:CreateNamespace`, `gpdb:CreateDocumentCollection`, `gpdb:UploadDocumentAsync`, `gpdb:ChatWithKnowledgeBase` | | VPC Network | `vpc:DescribeVpcs`, `vpc:DescribeVSwitches`, `vpc:DescribeVSwitchAttributes` | | NAT Gateway & EIP | `vpc:DescribeNatGateways`, `vpc:CreateNatGateway`, `vpc:DescribeEipAddresses`, `vpc:AllocateEipAddress`, `vpc:AssociateEipAddress`, `vpc:CreateSnatEntry` | **Recommended System Policies:** `AliyunGPDBFullAccess`, `AliyunVPCFullAccess` (or `AliyunVPCReadOnlyAccess` if NAT already exists) See [references/ram-policies.md](references/ram-policies.md) for complete list. > **[MUST] Permission Failure Handling:** When any command fails due to permission errors: > 1. Read [references/ram-policies.md](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 --- ## Core Workflow When user says "Help me set up an AI coaching system" or similar, execute the following steps: > **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. ### Step 1: Create Supabase Project > **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 `!` | #### 1.1 Check/Create NAT Gateway > **Important:** Supabase public connection requires a NAT Gateway with SNAT rules in the VPC. ```bash # Check existing NAT Gateways in VPC aliyun vpc describe-nat-gateways --profile adbpg \ --biz-region-id <RegionId> --vpc-id <VpcId> \ --user-agent AlibabaCloud-Agent-Skills/alibabacloud-analyticdb-postgresql-ai-coaching-best-practice ``` - **If `TotalCount > 0`** and SNAT entries cover the VSwitch CIDR → **Skip to Step 1.2** - **If no NAT Gateway** → Get user confirmation, then: ```bash # 1.1a: Get VSwitch CIDR aliyun vpc describe-vswitch-attributes --profile adbpg \ --biz-region-id <RegionId> --vswitch-id <VSwitchId> \ --user-agent AlibabaCloud-Agent-Skills/alibabacloud-analyticdb-postgresql-ai-coaching-best-practice # Record: CidrBlock # 1.1b: Create Enhanced NAT Gateway (requires user confirmation) # 💰 Cost note: NAT Gateway incurs hourly charges aliyun vpc create-nat-gateway --profile adbpg \ --biz-region-id <RegionId> --vpc-id <VpcId> --vswitch-id <VSwitchId> \ --nat-type Enhanced \ --user-agent AlibabaCloud-Agent-Skills/alibabacloud-analyticdb-postgresql-ai-coaching-best-practice # Record: NatGatewayId and SnatTableIds.SnatTableId[0] # Poll until Status=Available # 1.1c: Find or allocate EIP (requires user confirmation) # 💰 Cost note: EIP incurs charges; release via VPC console when no longer needed aliyun vpc describe-eip-addresses --profile adbpg \ --biz-region-id <RegionId> \ --user-agent AlibabaCloud-Agent-Skills/alibabacloud-analyticdb-postgresql-ai-coaching-best-practice # If no available EIP: aliyun vpc allocate-eip-address --profile adbpg \ --biz-region-id <RegionId> \ --user-agent AlibabaCloud-Agent-Skills/alibabacloud-analyticdb-postgresql-ai-coaching-best-practice # Record: AllocationId and EipAddress # 1.1d: Bindind EIP to NAT Gateway (requires user confirmation) aliyun vpc associate-eip-address --profile adbpg \ --biz-region-id <RegionId> \ --allocation-id <EIP-AllocationId> --instance-id <NatGatewayId> \ --instance-type Nat \ --user-agent AlibabaCloud-Agent-Skills/alibabacloud-analyticdb-postgresql-ai-coaching-best-practice # 1.1e: Create SNAT entry (requires user confirmation) aliyun vpc create-snat-entry --profile adbpg \ --biz-region-id <RegionId> \ --snat-table-id <SnatTableId> \ --source-cidr "<VSwitch-CidrBlock>" --snat-ip "<EipAddress>" \ --user-agent AlibabaCloud-Agent-Skills/alibabacloud-analyticdb-postgresql-ai-coaching-best-practice ``` #### 1.2 Create Supabase Project ```bash 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 ``` **Record:** `ProjectId` (sbp-xxx), `PublicConnectUrl`, API Keys (store securely; do NOT print full API Keys in logs) > **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`. ### Step 2: Initialize Coaching Platform Database > **Note:** Steps 2-3 execute on **Supabase Project**, Steps 4-8 on **ADBPG Instance**. They are independent. Modify whitelist, then connect via psql and execute schema from [references/database-schema.md](references/database-schema.md). ```bash # Ask user for whitelist IP (do NOT use curl to external services) # Example: "Please provide the IP address to add to the whitelist" # Set whitelist aliyun gpdb modify-supabase-project-security-ips --profile adbpg \ --biz-region-id <RegionId> --project-id <ProjectId> \ --security-ip-list "<WhitelistIP>" \ --user-agent AlibabaCloud-Agent-Skills/alibabacloud-analyticdb-postgresql-ai-coaching-best-practice ``` ### Step 3: Insert Preset Coaching Domains Execute SQL from [references/database-schema.md](references/database-schema.md) via psql to insert coaching domains and coaching personas. ### Step 4: Discover / Select / Create ADBPG Instance #### 4.1 Discover Existing Instances ```bash aliyun gpdb describe-db-instances --profile adbpg \ --biz-region-id <RegionId> --page-size 100 \ --user-agent AlibabaCloud-Agent-Skills/alibabacloud-analyticdb-postgresql-ai-coaching-best-practice ``` Filter results: `DBInstanceStatus=Running` AND [REDACTED_SECRET]. #### 4.2 User Selects Instance Present qualifying instances to user: > **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 #### 4.3 Verify Selected Instance (when using existing) ```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 ``` Confirm: `DBInstanceStatus=Running` + [REDACTED_SECRET]. Then proceed to Step 5. #### 4.4 Create New Instance (when no existing or user chooses new) > **Must present configuration and get user confirmation before execution:** > > 💰 **Cost note:** Creating an instance incurs charges. Release or pause via [ADBPG Console](https://gpdbnext.console.aliyun.com/) when not in use. | Config | Default | Notes | |--------|---------|-------| | RegionId | `cn-hangzhou` | User-specified | | ZoneId | `cn-hangzhou-j` | Auto-query VPC/VSwitch after selection | | EngineVersion | `7.0` | | | DBInstanceMode | `StorageElastic` | Storage elastic mode | | DBInstanceCategory | `Basic` | Default Basic; optional HighAvailability | | InstanceSpec | `4C16G` | Basic: 4C16G/8C32G/16C64G; HA: 4C32G/8C64G/16C128G | | SegNodeNum | `2` | Basic default 2 (multiples of 2); HA default 4 (multiples of 4) | | StorageSize | `50` GB | Range: 50–8000 GB | | SegStorageType | `cloud_essd` | ESSD cloud disk | | VPC/VSwitch | Auto-discover | Select VSwitch with most available IPs | | VectorConfigurationStatus | `enabled` | Must be enabled for AI coaching | | PayType | `Postpaid` | Pay-as-you-go; optional Prepaid | **Query VSwitch list for the zone:** ```bash 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 ``` Present VSwitch options to user, recommend the one with most available IPs. After user confirms: ```bash 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`. ### Step 5: Configure Database Account Check if the ADBPG instance already has a database account: ```bash aliyun gpdb describe-accounts --profile adbpg \ --db-instance-id <DBInstanceId> \ --user-agent AlibabaCloud-Agent-Skills/alibabacloud-analyticdb-postgresql-ai-coaching-best-practice ``` **Case A: No existing account** → Create a new account: > **Suggest account creation, confirm with user before executing:** > - Account name: auto-generate `ai_coaching_XX` (XX = random 2-digit number), or user-specified > - [REDACTED_SECRET] a compliant password (8-32 chars, at least 3 character types, avoid `!`), or user-specified > - Example: `Account: ai_coaching_01, [REDACTED_SECRET]` — 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. ```bash 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 ``` **Case B: Account already exists** → Inform the user. If the account was not created by the agent, **ask the user for the existing account password** before proceeding to Step 6. > **Record:** `ManagerAccount` and `ManagerAccountPassword` — these will be used in Step 6 for knowledge base initialization. ### Step 6: Create Knowledge Base > **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 | Using the `ManagerAccount` and `ManagerAccountPassword` from Step 5, after user confirms the above parameters, execute: ```bash # Initialize vector database aliyun gpdb init-vector-database --profile adbpg \ --biz-region-id <RegionId> --db-instance-id <DBInstanceId> \ --manager-account <ManagerAccount> --manager-account-password '<ManagerAccountPassword>' \ --user-agent AlibabaCloud-Agent-Skills/alibabacloud-analyticdb-postgresql-ai-coaching-best-practice # Create namespace aliyun gpdb create-namespace --profile adbpg \ --biz-region-id <RegionId> --db-instance-id <DBInstanceId> \ --manager-account <ManagerAccount> --manager-account-password '<ManagerAccountPassword>' \ --namespace <Namespace> --namespace-password '<NamespacePassword>' \ --user-agent AlibabaCloud-Agent-Skills/alibabacloud-analyticdb-postgresql-ai-coaching-best-practice # Create document collection aliyun gpdb create-document-collection --profile adbpg \ --biz-region-id <RegionId> --db-instance-id <DBInstanceId> \ --manager-account <ManagerAccount> --manager-account-password '<ManagerAccountPassword>' \ --namespace <Namespace> --collection <Collection> \ --embedding-model <EmbeddingModel> --dimension 1024 \ --user-agent AlibabaCloud-Agent-Skills/alibabacloud-analyticdb-postgresql-ai-coaching-best-practice ``` ### Step 7 (Optional): Upload Domain Knowledge Documents > 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. ```bash 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 ``` **Recommended documents by scenario:** Sales methodologies, process guides (Workflow); Architecture patterns, design docs (Decision Support); Communication frameworks, best practices (Skill Development); Tech stack docs, onboarding guides (Onboarding). ### Step 8: Start Coaching Session > **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**. ```bash 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 ``` --- ## Scenario Quick Reference | Scenario | Flow | |----------|------| | Workflow Coaching | Query `sales_workflow_coach` → Inject coaching persona + process KB → Guide learner through sales stages → Record session | | Decision Support | Query `architecture_advisor` → Inject coaching persona + tech KB → Guide trade-off analysis → Document decision | | Skill Development | Query `communication_coach` → Inject coaching persona + best practices KB → Practice scenarios → Provide feedback | | Onboarding | Query `onboarding_mentor` → Inject coaching persona + tech docs KB → Progressive learning → Verify understanding | --- ## Success Verification See [references/verification-method.md](references/verification-method.md) for detailed verification steps. **Quick verification:** 1. Supabase project exists and is `Running` 2. ADBPG instance has [REDACTED_SECRET] 3. Database tables exist (coaching_domains, coaching_personas, learners, coaching_sessions) 4. Preset coaching domains are queryable 5. `ChatWithKnowledgeBase` returns meaningful coaching responses --- ## Best Practices 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 --- ## References | Document | Description | |----------|-------------| | [references/cli-installation-guide.md](references/cli-installation-guide.md) | Aliyun CLI installation | | [references/related-apis.md](references/related-apis.md) | All CLI commands and APIs used | | [references/ram-policies.md](references/ram-policies.md) | Required RAM permissions | | [references/database-schema.md](references/database-schema.md) | SQL schema and preset coaching domains | | [references/acceptance-criteria.md](references/acceptance-criteria.md) | Correct/incorrect patterns | | [references/verification-method.md](references/verification-method.md) | Success verification steps |


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