Define Validation Manifest Schema for Structured Result Storage

[Copilot]

This PR introduces a comprehensive JSON schema for validation manifests that will replace the current file-based validation result storage with structured data suitable for Azure DevOps artifact management.

What Changed

Core Schema Definition

• Created validation-manifest-schema.json with JSON Schema Draft 07 specification
• Defines complete structure for validation results across all supported languages
• Includes required fields, data types, and validation constraints

Comprehensive Examples

• Added language-specific examples for C#, Python, and Java validation scenarios
• Examples demonstrate both success and failure cases with detailed error information
• Shows integration with existing build systems (dotnet, pip/Python, Maven)

Complete Documentation

• Detailed schema documentation with usage examples and integration guidance
• Coverage analysis proving all current validation data needs are met
• Migration path from current log-based system to structured JSON

Key Features

The schema captures all validation data currently stored in simple log files:

• Sample validation results (pass/fail status)
• Build step outcomes with detailed error information
• Validation step results and comprehensive timing data
• Pipeline context (run ID, build number, repository info)
• Resolved configuration used for each sample
• Historical data from previous runs for packaging logic decisions

Enhanced Capabilities

• Structured error details with file location information for better debugging
• Artifact tracking for build outputs and reports
• Environment context including tool versions for reproducibility
• Extensible design supporting future validation requirements
• Integration-ready format for Azure DevOps artifact publishing

Validation

All example files validate successfully against the schema:

ajv validate -s validation-manifest-schema.json -d examples/validation-manifest-*.json

The schema replaces the current approach:

# Current: Simple log files
echo "✅ sample-name" >> validation-success.log
echo "❌ sample-name" >> validation-errors.log

# New: Structured data with detailed context
{
  "validation": {
    "summary": { "total": 3, "passed": 2, "failed": 1 },
    "samples": [
      {
        "name": "sample-name",
        "status": "failed",
        "buildSteps": [/* detailed execution info */],
        "errorDetails": {/* structured error with location */}
      }
    ]
  }
}

This structured approach enables better debugging, trend analysis, and automated decision-making for the packaging pipeline while maintaining backward compatibility with existing validation workflows.

Fixes #33.

---

💡 You can make Copilot smarter by setting up custom instructions, customizing its development environment and configuring Model Context Protocol (MCP) servers. Learn more Copilot coding agent tips in the docs.