RepoDocs AI Product Specification
AI-Prompt-Powered Docs-as-Code Documentation System for SaaS APIs
Version: 1.0
Product Type: Documentation Template System + AI Prompt Framework
Primary Environment: GitHub repositories using Markdown documentation
1. Product Vision
RepoDocs AI is a structured documentation system designed for SaaS teams building API-driven products.
The system enables engineering teams to:
- Generate high-quality API documentation rapidly
- Standardize documentation across repositories
- Integrate documentation with development workflows
- Use AI tools safely with structured prompts and guardrails
- Maintain documentation quality through automated review workflows
RepoDocs AI is built for Docs-as-Code environments.
Primary documentation format: Markdown
2. Target Market
Primary Buyer (ICP)
- Startup CTO
- Head of Engineering
- Developer Relations Lead
- Technical Writer working in SaaS organizations
Company Profile
- SaaS startup or scale-up
- API-first platform
- 5-200 engineers
- Documentation maintained in Git repositories
Primary Pain Points
Teams struggle with:
- inconsistent documentation structure
- slow documentation creation
- lack of review standards
- poor API documentation quality
- documentation drift from code
3. Product Goals
RepoDocs AI must:
- Reduce time required to create API documentation
- Provide reusable documentation structure
- Enable AI-assisted documentation generation
- Support Git-based documentation workflows
- Enforce documentation quality standards
4. Supported Technology Stack
Documentation Format
Markdown
Repository Platforms
GitHub (primary)
Future support:
- GitLab
- Bitbucket
Static Documentation Generators
- Docusaurus
- MkDocs
- GitBook
- Next.js documentation sites
5. System Architecture
RepoDocs AI is composed of five major subsystems:
- Documentation Template Library
- Metadata Schema
- AI Prompt Framework
- Diagram Templates
- Documentation Validation System
6. Repository Structure
repodocs-ai/
├── docs/
├── templates/
│ ├── api/
│ ├── product/
│ ├── features/
│ └── governance/
├── prompts/
│ ├── api-generation/
│ ├── product-docs/
│ ├── feature-docs/
│ └── review/
├── diagrams/
│ ├── architecture/
│ ├── sequence/
│ └── data-flow/
├── validation/
│ ├── review-checklists/
│ └── hallucination-guards/
├── schema/
└── examples/
├── api-docs/
├── product-docs/
├── feature-docs/
└── complete-system/
7. Metadata Schema
All documentation files must contain metadata using Markdown frontmatter.
Standard Metadata Fields
- title
- description
- service
- component
- owner
- api_version
- status
- dependencies
- last_reviewed
- security_impact
Field Definitions
| Field | Description |
|---|---|
| title | Document title |
| description | Short description |
| service | Microservice or module |
| component | System component |
| owner | Responsible team |
| api_version | Version of API |
| status | draft / beta / stable / deprecated |
| dependencies | Related services |
| last_reviewed | Last documentation review date |
| security_impact | low / medium / high |
8. Template Library
8.1 Product Documentation Templates
Product Overview
Sections:
- Purpose
- Target Users
- Business Problem
- Core Capabilities
- Product Positioning
- Dependencies
Feature Documentation
Sections:
- Feature name
- Description
- Business value
- Configuration
- Workflow
- Examples
- Known limitations
User Guide
Sections:
- Prerequisites
- Setup
- Step-by-step usage
- Screenshots or visual placeholders
- Expected results
Administrator Guide
Sections:
- Installation
- Configuration
- Permissions
- Security
- Backup
- Monitoring
8.2 API Documentation Templates
API Overview Template
Sections:
- Purpose
- Authentication
- Base URL
- Versioning Strategy
- Rate Limits
- Error Handling
- SDK Support
- Example Use Case
Endpoint Documentation Template
Sections:
- Endpoint name
- HTTP method
- URL
- Purpose
- Authentication
- Parameters
- Request example
- Response example
- Error codes
- Performance considerations
8.3 Governance Templates
Documentation Review Checklist
Focus areas:
- Accuracy
- Completeness
- Security
- Examples
- Version compatibility
9. AI Prompt Framework
RepoDocs AI includes structured prompts for AI-assisted documentation.
Prompts must include:
- role definition
- input format
- expected output
- validation guidance
10. Diagram Templates
RepoDocs AI includes Mermaid diagram templates for:
- architecture diagrams
- sequence diagrams
- workflow diagrams
- data flow diagrams
11. Documentation Workflow
- Engineer defines source material such as OpenAPI specs or product notes.
- AI generates draft documentation using the structured prompts.
- Content is placed into Markdown templates.
- Documentation is committed to the repository.
- Pull request review is performed.
- SMEs validate technical accuracy using review checklists.
- Documentation is published to the target site or system.
12. Validation System
RepoDocs AI includes validation guidance for:
- parameter accuracy
- endpoint correctness
- example validity
- version compatibility
- hallucination prevention
13. Example Documentation System
Examples should include:
- complete example API documentation
- example SaaS product documentation
- example feature documentation
14. Packaging
The final product bundle includes:
- template library
- AI prompt library
- diagram templates
- metadata schema
- review workflows
- example documentation systems
15. Pricing Strategy
- Individual license: $49
- Team license: $149
Includes lifetime updates for v1.
16. Future Roadmap
Future versions may include:
- AI documentation agents
- automated OpenAPI documentation generation
- documentation linting tools
- knowledge graph indexing
- documentation analytics
17. Key Differentiators
RepoDocs AI differentiates from typical documentation templates by providing:
- AI-prompt-powered prompt integration
- metadata-driven documentation architecture
- documentation governance workflows
- diagram templates for developer documentation
- repo-native documentation workflows