Azure Data Studio Tool

The tool generates a formal, machine-readable specification package for a developer-facing Azure Data Studio tooling asset. It targets tool builders, data engineers, technical writers, and AI agents that require consistent documentation and SEO-ready content. It is used when a new tool concept is defined or an existing tool needs a standards-compliant spec, including inputs, outputs, and localization details.
Core structure enforces a fixed schema with sections for Purpose, Core Logic & Features, Inputs & Outputs, Algorithms, Error Handling, Localization, and Assumptions. Required elements include a defined identity, category, type, complete input/output schemas, sample values, and a meta-description. Optional elements add FAQs, multi-language copies, SEO fields, and an exported image descriptor.
Inputs and outputs are defined with precise names, types, units, sample values, and validation rules. Outputs specify types, units, and formatting conventions. The tool validates field lengths, ensures non-duplication, and enforces consistency across sections to support automation and auditing.
Algorithms and calculations assemble content from template blocks, apply length constraints (spec_text: 220–320 words; meta_description: 140–160 chars; 3–7 steps in how_to_use; 3–7 faq items), and derive SEO fields from inputs. Slug normalization, keyword deduplication, and case handling are applied to ensure reliability.
Industry localization and exclusions: en-us is the default language with US conventions; additional locales can be added by extending the language map. Units and terminology align with IT and data tooling standards. The meta description emphasizes “Free online tool.”
Assumptions include a developer audience and Azure Data Studio focus. Exclusions cover UI specifics, runtime integration details, and marketing language.