business-to-technical-spec

name	business-to-technical-spec
description	Business to Technical Specification enables systematic translation of Use when this capability is needed.
metadata	{"author":"amnadtaowsoam"}

Business To Technical Spec

Skill Profile

(Select at least one profile to enable specific modules)

• DevOps
• Backend
• Frontend
• AI-RAG
• Security Critical

Overview

Business to Technical Specification enables systematic translation of business requirements into detailed technical specifications that guide product development. This capability is essential for ensuring alignment between business objectives and technical implementation, reducing miscommunication and development rework.

Why This Matters

Strategic Necessity:

• Alignment: Ensure technical solutions match business needs
• Clarity: Provide clear, actionable specifications
• Efficiency: Reduce development rework and delays
• Quality: Improve product quality through clear requirements
• Communication: Bridge gap between business and engineering

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Core Concepts & Rules

1. Core Principles

• Follow established patterns and conventions
• Maintain consistency across codebase
• Document decisions and trade-offs

2. Implementation Guidelines

• Start with the simplest viable solution
• Iterate based on feedback and requirements
• Test thoroughly before deployment

Inputs / Outputs / Contracts

• Inputs:
  • <e.g., env vars, request payload, file paths, schema>
• Entry Conditions:
  • <Pre-requisites: e.g., Repo initialized, DB running, specific branch checked out>
• Outputs:
  • <e.g., artifacts (PR diff, docs, tests, dashboard JSON)>
• Artifacts Required (Deliverables):
  • <e.g., Code Diff, Unit Tests, Migration Script, API Docs>
• Acceptance Evidence:
  • <e.g., Test Report (screenshot/log), Benchmark Result, Security Scan Report>
• Success Criteria:
  • <e.g., p95 < 300ms, coverage ≥ 80%>

Skill Composition

• Depends on: None
• Compatible with: None
• Conflicts with: None
• Related Skills: None

Quick Start / Implementation Example

1. Review requirements and constraints
2. Set up development environment
3. Implement core functionality following patterns
4. Write tests for critical paths
5. Run tests and fix issues
6. Document any deviations or decisions

# Example implementation following best practices
def example_function():
    # Your implementation here
    pass

Assumptions

• Stakeholders are available for consultation
• Business requirements are documented or can be gathered
• Technical team has capacity to implement specifications
• Templates and standards are established
• Review process is defined and followed

Compatibility & Prerequisites

• Supported Versions:
  • Python 3.8+
  • Node.js 16+
  • Modern browsers (Chrome, Firefox, Safari, Edge)
• Required AI Tools:
  • Code editor (VS Code recommended)
  • Testing framework appropriate for language
  • Version control (Git)
• Dependencies:
  • Language-specific package manager
  • Build tools
  • Testing libraries
• Environment Setup:
  • .env.example keys: API_KEY, DATABASE_URL (no values)

Test Scenario Matrix

Scenario	Description	Expected Outcome
Requirement Gathering	Gather requirements from multiple sources	Complete requirements list with metadata
Requirement Analysis	Analyze requirements for quality	Analysis report with scores and issues
Requirement Validation	Validate requirements against thresholds	Pass/fail result with issues
PRD Generation	Generate Product Requirements Document	Complete PRD with all sections
FRD Generation	Generate Functional Requirements Document	Complete FRD with functional requirements
TRD Generation	Generate Technical Requirements Document	Complete TRD with technical requirements
API Spec Generation	Generate API specification	Valid OpenAPI 3.0 specification
Review Process	Initiate review and approval	Approved specifications with feedback

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Technical Guardrails & Security Threat Model

1. Security & Privacy (Threat Model)

• Top Threats: Injection attacks, authentication bypass, data exposure

• Data Handling: Sanitize all user inputs to prevent Injection attacks. Never log raw PII
• Secrets Management: No hardcoded API keys. Use Env Vars/Secrets Manager
• Authorization: Validate user permissions before state changes

2. Performance & Resources

• Execution Efficiency: Consider time complexity for algorithms
• Memory Management: Use streams/pagination for large data
• Resource Cleanup: Close DB connections/file handlers in finally blocks

3. Architecture & Scalability

• Design Pattern: Follow SOLID principles, use Dependency Injection
• Modularity: Decouple logic from UI/Frameworks

4. Observability & Reliability

• Logging Standards: Structured JSON, include trace IDs request_id
• Metrics: Track error_rate, latency, queue_depth
• Error Handling: Standardized error codes, no bare except
• Observability Artifacts:
  • Log Fields: timestamp, level, message, request_id
  • Metrics: request_count, error_count, response_time
  • Dashboards/Alerts: High Error Rate > 5%

Agent Directives

1. Gathering Phase: Always gather requirements from multiple sources
2. Analysis Phase: Always analyze requirements for quality and completeness
3. Validation Phase: Always validate requirements against thresholds
4. Generation Phase: Always use standard templates for specifications
5. Review Phase: Always require review and approval before publishing

Definition of Done (DoD) Checklist

• Tests passed + coverage met
• Lint/Typecheck passed
• Logging/Metrics/Trace implemented
• Security checks passed
• Documentation/Changelog updated
• Accessibility/Performance requirements met (if frontend)

Anti-patterns / Pitfalls

• ⛔ Don't: Log PII, catch-all exception, N+1 queries
• ⚠️ Watch out for: Common symptoms and quick fixes
• 💡 Instead: Use proper error handling, pagination, and logging

Reference Links & Examples

• Internal documentation and examples
• Official documentation and best practices
• Community resources and discussions

Versioning & Changelog

• Version: 1.0.0
• Changelog:
  • 2026-02-22: Initial version with complete template structure

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