Schema Consistency Analysis - December 25, 2025

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Schema Consistency Check - December 25, 2025

Overview

This analysis reversed the typical validation approach by inferring what the schema SHOULD be from actual workflow usage (124 production workflows), then comparing to the declared schema. This "reality-first" perspective revealed dead schema fields, undocumented patterns, and structural inconsistencies invisible to traditional top-down validation.

Key Statistics:

• Workflows Analyzed: 124
• Unique Fields Found: 528 (including nested paths)
• Top-Level Fields: 29 actively used
• Schema Fields: 39 defined
• Critical Findings: 5
• Moderate Findings: 8

Full Report

Critical Issues

1. Fourteen Dead Schema Fields (0% Adoption)

The following fields are defined in main_workflow_schema.json but have zero usage across all 124 production workflows:

Field	Status	Notes
command	Dead	Never used
container	Dead	Top-level unused (but nested mcp-servers.*.container IS used)
environment	Dead	Never used
github-token	Dead	Never used
githubActionsStep	Dead	Known dead code (documented in previous analyses)
labels	Dead	Top-level unused
metadata	Dead	Never used
run-name	Dead	Never used
runtimes	Dead	Known low adoption from previous analyses
safe-inputs	Near-dead	Only 3 occurrences
secret-masking	Near-dead	Only 1 occurrence
services	Near-dead	Only 1 occurrence
timeout_minutes	Deprecated	Replaced by timeout-minutes, never used

Impact: Schema bloat, maintenance burden, false advertised capabilities

Recommendation: Deprecate unused fields or document why they exist (future use, backwards compatibility)

2. Schema Validates 'on: daily' Despite Being Invalid GitHub Event

Finding: 6 workflows successfully use on: daily as a string value:

• agent-performance-analyzer.md
• campaign-manager.md
• daily-issues-report.md

Schema Allows This: Confirmed in schema oneOf string pattern:

{
  "type": "string",
  "description": "... schedule shorthand (e.g., 'daily', 'weekly') ...",
  "examples": ["daily", "/my-bot"]
}

Status: ✅ Not a bug - 'daily' is a documented shorthand that expands during parsing

However: This is a non-standard extension to GitHub Actions syntax that should be prominently documented as gh-aw-specific

3. MCP-Servers Structural Ambiguity

Issue: mcp-servers defined at schema top level but never used as top-level field

Reality: Used as nested property under tools configuration:

tools:
  github:
    mcp-servers:
      - id: github
        command: ["npx", "`@modelcontextprotocol/server-github`"]

Schema Status: Field exists at top level in schema (verified)

Impact: Schema structure doesn't reflect actual usage patterns. IDE autocomplete might suggest top-level usage that doesn't work.

Recommendation: Either move definition to tools context or document top-level vs nested usage

4. Jobs + Steps Co-Existence Unclear

Finding: 3 workflows use BOTH jobs AND steps:

• hourly-ci-cleaner.md:37
• release.md:37
• super-linter.md:37

Schema: Both fields defined, no apparent mutual exclusion constraints

Question: Are these mutually exclusive in practice? If so, schema validation is missing.

Recommendation: Clarify relationship and add validation if needed

5. Engine Empty Value Pattern (16% of Workflows)

Finding: 19 workflows (16%) have empty engine values

Breakdown:

• copilot: 71 workflows (57%)
• claude: 27 workflows (22%)
• Empty/unset: 19 workflows (15%)
• codex: 8 workflows (6%)

Question: Is empty engine valid? What's the default behavior?

Recommendation: Document default engine behavior in schema description

Moderate Issues

6. Tools + Safe-Outputs Strong Correlation (95%)

Data:

• Workflows with tools: 119
• Workflows with safe-outputs: 118
• Workflows with BOTH: 113 (95% correlation)

Insight: These fields almost always appear together but schema doesn't indicate relationship

Recommendation: Add schema guidance or make relationship explicit

7. Timeout Range: 5 to 480 Minutes (No Schema Constraints)

Actual Usage:

• Min: 5 minutes (18 workflows)
• Max: 480 minutes / 8 hours (org-wide-rollout.md)
• Common: 10-30 minutes

Schema: No minimum or maximum constraints defined (verified: both null)

Risk: Extremely long timeouts accepted without warning

Recommendation: Add reasonable maximum (e.g., 720 minutes) or document unbounded by design

8. Description Length: No MaxLength Despite 271-Char Usage

Actual Usage:

• Min: 53 characters
• Max: 271 characters
• Avg: 148 characters

Schema: No maxLength constraint (verified: null)

Risk: Unbounded descriptions could cause display issues

Recommendation: Add maxLength constraint (e.g., 500) based on actual usage

9. Permissions Polymorphism: 99% Object, 1% String

Schema Design: Allows string OR object via oneOf

Actual Usage:

• String (read-all): 1 workflow (<1%)
• Object (nested permissions): 122 workflows (99%)

Status: ✅ Schema correctly supports both, but string usage is rare

10. Roles Field: Array-Only in Practice

Schema Design: Allows string OR array

Actual Usage:

• String: 0 workflows
• Array: 5 workflows (100% of roles users)

Status: ✅ Schema supports both, but only array used in practice

11. Field Adoption Tiers

Tier 1 - Core Fields (94-105% adoption):

• tools (130 uses - 105%)
• safe-outputs (124 - 100%)
• on (124 - 100%)
• permissions (123 - 99%)
• timeout-minutes (121 - 98%)
• description (120 - 97%)
• engine (117 - 94%)

Tier 2 - Common (48-78%):

• strict (78 - 63%)
• imports (72 - 58%)
• network (59 - 48%)

Tier 3 - Moderate (15-51%):

• name (63)
• steps (37)
• tracker-id (29)
• mcp-servers (20 nested)
• sandbox (17)

Tier 4 - Rare (<9%):

• 14 fields with <10 uses each
• 10 fields with <3 uses each (including dead fields)

12. Schedule Event Dominance (54%)

On Event Distribution:

• schedule: 67 workflows (54%)
• workflow_dispatch: 29 (23%)
• slash_command: 11 (9%)
• GitHub events (push, PR, issues): 8 (6%)
• Other: 9 (8%)

Insight: This is an automation-first workflow system, not a typical CI/CD system

13. Workflow Comments Indicate Schema Issues

Several workflows contain comments about schema problems:

1. changeset.md: "Note about entrypointArgs schema validation issue"
2. mcp-inspector.md: "azure.md excluded due to schema validation issue"

Recommendation: Investigate these specific validation failures

Positive Findings

✅ Boolean Consistency (YAML 1.1 Ambiguity Avoided)

• true: 212 occurrences
• false: 45 occurrences
• yes/no: 0 occurrences

Excellent: Workflows consistently avoid YAML 1.1 boolean keywords, preventing parser ambiguity

✅ 'on: daily' Documented Shorthand

Schema explicitly supports schedule shorthands - not a bug, but a feature

✅ Polymorphic Fields Work Correctly

permissions and roles oneOf patterns validated against real usage

Recommendations

Immediate Actions

1. Document Dead Fields: Create schema changelog explaining why 14 fields exist but are unused
2. Clarify MCP-Servers Nesting: Update schema description to explain top-level vs nested usage
3. Validate Jobs + Steps: Clarify if mutually exclusive and add validation
4. Investigate Validation Failures: Check changeset.md and azure.md schema issues

Short-Term Improvements

5. Add Timeout Constraints: Set reasonable maximum (720 min?) or document unbounded design
6. Add Description MaxLength: Use 500 chars based on 271-char max observed
7. Document Engine Defaults: Explain behavior when engine is empty/unset
8. Formalize Tools + Safe-Outputs Relationship: Add schema guidance about correlation

Long-Term Considerations

9. Deprecation Strategy: Plan removal path for dead fields
10. Adoption Metrics: Track Tier 4 fields - improve docs or consider deprecation
11. Schema Validation in CI: Add workflow validation tests to catch schema violations early

Strategy Performance

Strategy ID: 027
Name: Schema Inference from Real Workflows (Reverse Engineering)
Approach: Infer schema from 124 workflows, compare to declared schema
Findings: 13 categories (5 critical, 8 moderate)
Novel Insights: Yes - revealed dead fields, adoption tiers, structural mismatches
Effectiveness: VERY HIGH

Unique Value: Only strategy that measures schema accuracy against reality rather than validating reality against schema

Recommendation: Use every 6-8 analyses to ensure schema evolves with actual usage patterns

Next Steps

• Review and triage 14 dead schema fields
• Document 'on: daily' shorthand syntax prominently
• Clarify mcp-servers top-level vs nested usage
• Investigate jobs + steps relationship
• Add timeout-minutes and description length constraints
• Research changeset.md and azure.md validation issues
• Update strategy cache with results

Summary Statistics

Category	Count
Dead Schema Fields	14
Near-Dead Fields (<3 uses)	3
High-Adoption Fields (>90%)	7
Schema Fields Never Used	14 (36%)
Workflows with Potential Issues	3 (jobs+steps)
Empty Engine Values	19 (15%)

References:

• schema-consistency-checker.md
• main_workflow_schema.json

AI generated by Schema Consistency Checker