azure-database-postgresql
- Repo stars 0
- Author updated Live
- Author repo skills-registry
- Domain
- DevOps
- Compatible agents
-
- Claude Code
- Cursor
- Cline
- Codex
- Windsurf
- Gemini CLI
- +20
- Trust score
- 88 / 100 · community maintained
- Author / version / license
- @tomevault-io · no license declared
- Token usage
- Moderate
- Setup complexity
- Guided setup
- External API key
- Not required
- Operating systems
- Windows
- Runtime requirements
- Python
- Permissions
-
- Read-only
- Write / modify
- Shell exec
- Network behavior
- External requests
- Install commands
- 26 variants
Profile is derived at build time from SKILL.md and install vectors. Subject to drift from author intent.
Heads up: 未限定 allowed-tools,默认拥有全部工具权限。
---
name: azure-database-postgresql
description: Expert knowledge for Azure Database for PostgreSQL development including troubleshooting, best p…
category: devops
runtime: Python
---
# azure-database-postgresql output preview
## PART A: Task fit
- Use case: Expert knowledge for Azure Database for PostgreSQL development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when using pgvector, Azure AI/OpenAI, Entra auth/Private Link, sharding/replication, or CI/CD/Bicep deployments, and other Azure Database for PostgreSQL related development tasks. Not for Azure Database for MySQL (use azure-database-mysql), Azure Database for MariaDB (use azure-database-mariadb), Azure SQL Database (use azure-sql-database), Azure SQL Managed Instance (use azure-sql-managed-instance). Use when this capability is needed..
- Inputs: target material, constraints, expected output, and acceptance criteria.
- Evidence boundary: follow “How to Use This Skill / Category Index / Troubleshooting” and do not present inference as author intent.
## PART B: Execution result
- **01** The card summarizes the use case; runtime output centers on “Expert knowledge for Azure Database for PostgreSQL development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when using pgvector, Azure AI/OpenAI, Entra auth/Private Link, sharding/replication, or CI/CD/Bicep deployments, and other Azure Database for PostgreSQL related development tasks. Not for Azure Database for MySQL (use azure-database-mysql), Azure Database for MariaDB (use azure-database-mariadb), Azure SQL Database (use azure-sql-database), Azure SQL Managed Instance (use azure-sql-managed-instance). Use when this capability is needed.”.
- **02** When the source has headings, the agent prioritizes “How to Use This Skill / Category Index / Troubleshooting” so the result follows the author’s structure.
- **03** Typical output includes task judgment, concrete steps, required commands or file edits, validation, and follow-up options.
- **04** Risk context follows the fingerprint: read files, write/modify files, run shell commands; may access external network resources; usually needs no extra API key.
## Running Rules
- read files, write/modify files, run shell commands; may access external network resources; usually needs no extra API key.
- Validate with a small sample before expanding scope.
- Return the result, validation criteria, and next iteration options. The source does not require a stable slash command. After installation, invoke the skill by name and describe the task.
Name target files or source material, expected output, forbidden changes, and whether network or shell access is allowed. Permission fingerprint: read files, write/modify files, run shell commands.
Start with a small task and check whether the result follows “How to Use This Skill / Category Index / Troubleshooting”. Inspect diffs, logs, previews, or tests before expanding scope.
Confirm the final output includes a concrete result, evidence, and next action. If it stays generic, tighten inputs, boundaries, and acceptance criteria.
---
name: azure-database-postgresql
description: Expert knowledge for Azure Database for PostgreSQL development including troubleshooting, best p…
category: devops
source: tomevault-io/skills-registry
---
# azure-database-postgresql
## When to use
- Expert knowledge for Azure Database for PostgreSQL development including troubleshooting, best practices, decision mak…
- Use it when the task has clear inputs, repeatable steps, and validation criteria.
## What to provide
- Target material, scope, expected result, and forbidden changes.
- Whether network, commands, file writes, or external services are allowed.
## Execution rules
- Organize steps around “How to Use This Skill / Category Index / Troubleshooting” and keep inference separate from source facts.
- read files, write/modify files, run shell commands; may access external network resources; usually needs no extra API key.
- Validate with a small sample before expanding the task.
## Output requirements
- Return the deliverable, key evidence, validation method, and next action.
- Mark missing information as unknown; do not invent commands, platforms, or dependencies. The author source anchors workflow facts; repository files anchor sources and commands; Fluxly only adds fit, limitations, and quality judgment.
skill "azure-database-postgresql" {
input -> user goal + target files + boundaries + acceptance criteria
context -> How to Use This Skill / Category Index / Troubleshooting
rules -> SKILL.md triggers / order / output contract
runtime -> Python | read files, write/modify files, run shell commands | may access external network resources
guardrails -> usually needs no extra API key + small-sample validation + diff/log review
output -> copyable result + checklist + next iteration
} Azure Database Postgresql Skill
This skill provides expert guidance for Azure Database Postgresql. Covers troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. It combines local quick-reference content with remote documentation fetching capabilities.
How to Use This Skill
IMPORTANT for Agent: This file may be large. Use the Category Index below to locate relevant sections, then use
read_filewith specific line ranges (e.g.,L136-L144) to read the sections needed for the user's question This skill requires network access to fetch documentation content. Usemcp_microsoftdocs:microsoft_docs_fetchto retrieve full articles.
- Fallback: Use the built-in
WebFetchtool if the Microsoft Learn MCP server is not available.
Category Index
| Category | Lines | Description |
|---|---|---|
| Troubleshooting | L31-L51 | Diagnosing and fixing Azure PostgreSQL issues: connectivity/TLS, HA and replicas, CPU/memory/IOPS, slow queries, autovacuum, extensions/CLI/storage, capacity, and migration validation errors. |
| Best Practices | L53-L69 | Performance, security, migration, and tooling best practices for Azure PostgreSQL: tuning queries, extensions, pooling, bulk load, stats, partitioning, pgvector, Oracle migration, and backups. |
| Decision Making | L71-L84 | Guidance for planning and sizing Azure PostgreSQL: choosing hosting and compute tiers, versions, geo-replication/DR, reserved capacity, and validating/sizing targets for migrations and upgrades. |
| Architecture & Design Patterns | L86-L95 | Patterns for using Azure PostgreSQL (often with OpenAI) to build recommendation/semantic search apps, microservices, multitenancy, real-time dashboards, and sharded/elastic data architectures. |
| Limits & Quotas | L97-L115 | Backup/restore and geo-restore behavior, storage types/limits/tuning, quotas and capacity limits, replication/slots, and known migration/conversion limitations for Azure PostgreSQL. |
| Security | L117-L146 | Securing Azure Database for PostgreSQL: auth (Entra, SCRAM, TLS/SSL), firewall/VNet/Private Link, managed identities, encryption, auditing, roles, policies, and Defender for Cloud. |
| Configuration | L148-L234 | Configuring Azure Database for PostgreSQL: server parameters, extensions, HA, maintenance, logging/monitoring, performance tuning, networking, migration settings, and WAL/replication options. |
| Integrations & Coding Patterns | L236-L264 | Using Azure PostgreSQL with AI/ML (Azure AI, OpenAI, LangChain, Foundry), app SDKs (C#, Java, Python, Go, PHP), VS Code/Copilot, Storage, Data Factory, and migration tools (Ora2Pg, pg_dump). |
| Deployment | L266-L276 | CI/CD deployment to Azure PostgreSQL, major upgrades, Bicep-based provisioning, app deployments (Django/AKS, Web Apps + VNet), maintenance rollout behavior, and point-in-time restore. |
Troubleshooting
Best Practices
Decision Making
Architecture & Design Patterns
Limits & Quotas
Security
Configuration
Integrations & Coding Patterns
Deployment
Source: atc-net/atc-agentic-toolkit — distributed by TomeVault.
Decide Fit First
Design Intent
How To Use It
Boundaries And Review