Schema Consistency: Conditional Logic Analysis - Dec 19, 2025

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Summary

Analysis of conditional logic, feature interactions, and cross-component dependencies confirms continued high quality with 2 minor documentation enhancement opportunities identified.

Key Results:

• ✅ 5 positive confirmations of excellent implementation
• 📝 2 moderate documentation gaps (HTTP transport engine compatibility, safe-outputs schema)
• 🎯 Strategy showing diminishing returns - approaching maturity on current codebase
• 📊 Effectiveness trend: Very-High → High (still valuable for regression checks)

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Moderate Findings

1. HTTP MCP Transport Engine Compatibility Not in Schema

Priority: Medium (Documentation Enhancement)

Current State:

• Implementation validates HTTP transport support per engine in agent_validation.go
• Copilot engine supports HTTP transport, others may only support stdio
• Schema $defs.http_mcp_tool lacks description mentioning engine compatibility

Error Message (Excellent Quality):

tool '%s' uses HTTP transport which is not supported by engine '%s'.
Only stdio transport is supported. Use a different engine (e.g., copilot)
or change the tool to use stdio transport.

Impact: Users discover limitation at compile time (good), but IDE autocomplete and schema docs don't surface this constraint proactively.

Recommendation:

Add to $defs.http_mcp_tool in pkg/parser/schemas/main_workflow_schema.json:

{
  "description": "HTTP-based MCP server configuration using URL endpoints. Note: HTTP transport is engine-specific - supported by copilot engine, but other engines may only support stdio transport. Check engine documentation for compatibility.",
  "type": "object",
  "properties": { ... }
}

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2. Safe-Outputs Target Field Schema Requirement

Priority: Low (Schema Consistency)

Current State:

• Compiler requires configuration but schema required array is empty
• Appears to be intentional: schema defines structure, compiler validates semantics

Recommendation: Either accept as designed (Option A) or add $comment to clarify intent (Option B). No functional impact.

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Positive Findings ✅

1. Pull Request Event Type Documentation is Exemplary

Files: main_workflow_schema.json:284-285

{
  "description": "Pull request event types to trigger on. Note: 'converted_to_draft' and 'ready_for_review' represent state transitions (events) rather than states. While technically valid to listen for both, consider if you need to handle both transitions or just one.",
  "$comment": "converted_to_draft and ready_for_review are logically opposite state transitions. Using both may indicate unclear intent."
}

Why Excellent:

• User-facing description explains semantic meaning
• Developer $comment notes logical consideration without over-restricting
• Educates without constraining valid use cases

This is a model example for documenting conditional logic in JSON Schema.

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2. Strict Mode: Perfect Schema + Implementation Alignment

Schema describes all 5 enforcements clearly:

1. Write Permissions - refuses write permissions, requires safe-outputs
2. Network Configuration - requires explicit network config
3. Action Pinning - enforces commit SHA pins
4. MCP Network - requires network config for containers
5. Deprecated Fields - refuses deprecated fields

Error messages provide concrete remediation with examples and docs links.

---

3. Multiple Engine Validation: Clear Cross-File Enforcement

Implementation correctly validates engine uniqueness across main + included files:

if len(allEngines) > 1 {
    return "", fmt.Errorf("multiple engine fields found (%d engine specifications detected).
    Only one engine field is allowed across the main workflow and all included files.
    Remove duplicate engine specifications to keep only one. Example: engine: copilot",
    len(allEngines))
}

Why Correct: JSON Schema cannot express cross-file constraints. Runtime validation is appropriate.

---

4. Filter Validation: Mutual Exclusivity Properly Enforced

Implementation in compiler_filters_validation.go validates GitHub Actions requirements:

• branches/branches-ignore are mutually exclusive
• paths/paths-ignore are mutually exclusive
• Clear error messages with GitHub docs links

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5. MCP Type-Container Validation: Clear Logic

HTTP MCP cannot use container field - validated with clear explanation:

HTTP MCP uses URL endpoints, not containers.

Provides corrected example in error message.

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Key Insights

Schema Design Patterns Validated

1. $comment Usage Appropriate - Developer notes in $comment, user guidance in description
2. Runtime Validation Complements Schema - Complex conditional logic validated at compile time (correct approach)
3. Error Message Quality High - All errors include examples, remediation steps, docs links
4. Security Features Well-Documented - Strict mode enforcements clearly enumerated

Strategy Performance

Run History: 9 runs (strategy-005)

Findings Trend:

• Runs 1-3: 5-8 findings (discovery phase)
• Runs 4-6: 3-5 findings (refinement phase)
• Runs 7-9: 1-2 findings (maturity phase)

Diminishing Returns Observed: Strategy has systematically validated conditional logic. Most gaps resolved. Recent runs find primarily positive confirmations.

Effectiveness: Very-High → High (still valuable for regression checks, but lower discovery rate)

Recommendation: Reduce frequency from every 3-4 to every 5-6 analyses. Pair with strategies 7 (Example Validation) or 17 (Runtime Type Behavior) for fresh perspectives.

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Recommendations

Immediate Actions (Optional, Low Priority)

1. Add HTTP Transport Compatibility to Schema (Medium Priority)

   • Location: $defs.http_mcp_tool.description in main_workflow_schema.json
   • Impact: Improves IDE autocomplete and schema-driven tooling

2. Optional: Document Cross-File Engine Uniqueness (Low Priority)

   • Add note to engine descriptions about single-engine requirement
   • Impact: Sets user expectations upfront

No Action Required

• Safe-outputs schema gap (working as designed)
• Pull request event documentation (already exemplary)
• All other positive findings confirmed

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Conclusion

This analysis confirms continued high quality in conditional logic handling. The 2 findings are documentation enhancements, not functional gaps.

Strengths:

• ✅ Exemplary $comment vs description usage
• ✅ Comprehensive strict mode enforcement
• ✅ High-quality error messages
• ✅ Appropriate runtime validation
• ✅ Proper JSON Schema limitation handling

Strategy Status: Mature - Recommend reduced frequency for regression checks while exploring other strategies for new discovery.

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Analysis Date: 2025-12-19
Strategy: Conditional Logic & Feature Flag Analysis (Strategy-005, Run #9)
Files Analyzed: Schema files, compiler validation, error messages, documentation
Methodology: Conditional logic pattern analysis, cross-file validation checks, error message quality assessment

AI generated by Schema Consistency Checker

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