Claude Code Plugins

Community-maintained marketplace

Feedback

architecture-validation

@d-o-hub/rust-self-learning-memory
1
0

Generic architecture validation that validates implementations against any plan files in the plans/ folder

Install Skill

1Download skill
2Enable skills in Claude

Open claude.ai/settings/capabilities and find the "Skills" section

3Upload to Claude

Click "Upload skill" and select the downloaded ZIP file

Note: Please verify skill by going through its instructions before using it.

SKILL.md

name architecture-validation
description Generic architecture validation that validates implementations against any plan files in the plans/ folder
version 2.0.0

Architecture Validation Skill

Dynamically validate that the implemented codebase matches the architectural decisions, design patterns, and system constraints documented in ANY plan files found in the plans/ directory.

Purpose

This skill provides a generic, adaptive framework for architecture validation that:

  • Discovers all plan files in plans/ directory
  • Extracts architectural requirements, decisions, and constraints dynamically
  • Validates implementation compliance without hardcoded assumptions
  • Reports gaps, drift, and violations with actionable recommendations

Key Principle: Be architecture-agnostic. Work with ANY project structure and ANY set of plans.

When to Use This Skill

Use this skill when:

  • Validating that implementation matches planning documents
  • Checking for architecture drift after development
  • Ensuring design decisions are being followed
  • Identifying missing or incomplete implementations
  • Auditing compliance with documented constraints
  • Preparing for architecture reviews
  • Verifying refactoring didn't break architectural boundaries

Validation Dimensions

The skill validates across multiple dimensions, dynamically discovered from plan files:

1. Component/Module Structure

  • Planned crates, packages, modules exist
  • Directory organization matches plans
  • Component boundaries are maintained

2. Dependency Architecture

  • Dependency rules are followed
  • No circular dependencies
  • Proper abstraction layers
  • No unwanted dependencies

3. Data Models

  • Structs, enums, types match plans
  • Required fields present
  • Schemas implemented correctly

4. APIs and Interfaces

  • Public APIs match planned signatures
  • Required functions exist
  • Traits/interfaces implemented

5. Performance Architecture

  • Benchmarks exist for targets
  • Performance requirements documented
  • Resource limits implemented

6. Security Architecture

  • Security measures implemented
  • Attack surfaces addressed
  • Input validation present
  • No hardcoded secrets

7. Testing Strategy

  • Test types match plan
  • Coverage requirements met
  • Test infrastructure present

8. Integration Patterns

  • External integrations match design
  • Communication patterns correct
  • Protocol implementations compliant

Validation Workflow

Phase 1: Plan Discovery

# Find all plan files
ls -1 plans/*.md

# Read plan index
cat plans/README.md

Output: List of all plan files to analyze

Phase 2: Architecture Extraction

# Extract components/crates
grep -rh "crate\|component\|module" plans/ | sort -u

# Extract dependencies
grep -rh "depend\|flow\|import" plans/ | sort -u

# Extract performance targets
grep -rh "target\|metric\|<.*ms\|P[0-9]" plans/ | sort -u

# Extract security requirements
grep -rh "security\|threat\|attack" plans/ -i | sort -u

# Extract data models
grep -rh "struct\|enum\|type\|schema" plans/ | sort -u

Output: Structured list of architectural elements

Phase 3: Codebase Analysis

# Analyze project structure
find . -name "Cargo.toml" -not -path "*/target/*"
tree -L 2 -I target

# Analyze dependencies
cargo tree --depth 1
cargo tree --duplicates

# Analyze code
rg "pub (async )?fn|pub struct|pub enum" --type rust

Output: Actual implementation state

Phase 4: Compliance Validation

For each discovered architectural element:

  1. Check if it exists in codebase
  2. Validate it matches specification
  3. Assess compliance level
  4. Document findings

Output: Compliance matrix

Phase 5: Gap Analysis

Identify:

  • Missing: Planned but not implemented
  • Drift: Implemented differently than planned
  • Extra: Implemented but not documented

Output: Gap report with priorities

Phase 6: Report Generation

Generate comprehensive report with:

  • Executive summary
  • Detailed findings per dimension
  • Specific recommendations
  • Action items with priorities

Extraction Patterns

Components/Crates

Look for:

  • "crate", "component", "module", "package"
  • Directory tree structures in code blocks
  • Architecture diagrams
  • Component lists

Dependencies

Look for:

  • "depends on", "imports", "requires"
  • "must not depend", "should not import"
  • "flow:", "→", "-->", "⇒"
  • Dependency rules and constraints

Performance

Look for:

  • "target:", "metric:", "goal:"
  • "<Xms", "P95", "P99", "latency", "throughput"
  • Performance requirements tables
  • Benchmark specifications

Security

Look for:

  • "security", "threat", "attack", "vulnerability"
  • "sanitize", "validate", "authenticate"
  • Security requirement lists
  • Attack surface descriptions

Data Models

Look for:

  • "struct", "enum", "type", "interface"
  • "table", "schema", "field", "column"
  • Data model diagrams
  • Type definitions

APIs

Look for:

  • "pub fn", "public function", "API"
  • "endpoint", "method", "operation"
  • Function signatures
  • Interface definitions

Compliance Levels

✅ Compliant

  • Architectural element fully implemented as planned
  • No deviations
  • All requirements met

⚠️ Partial

  • Element exists but incomplete
  • Some requirements met, others missing
  • Functional but not fully compliant

❌ Non-Compliant

  • Element missing entirely
  • Significant violations
  • Major architectural drift

Report Format

# Architecture Validation Report
**Date**: [Date]
**Project**: [Name]
**Plans**: [List of plan files]

## Executive Summary
- Overall Compliance: X%
- Critical Issues: N
- Warnings: M
- Info: K

## Plans Analyzed
1. plans/00-overview.md - Project overview
2. plans/01-understand.md - Requirements
...

## Architectural Elements Discovered
[Dynamic list based on plan extraction]

### Components
- Component A: ✅ Implemented
- Component B: ⚠️ Partial
- Component C: ❌ Missing

### Dependencies
- Rule 1: ✅ Compliant
- Rule 2: ❌ Violated

### Performance
- Target 1 (<100ms): ⚠️ Untested
- Target 2 (>1000 ops/s): ✅ Met

### Security
- Requirement 1: ✅ Implemented
- Requirement 2: ⚠️ Partial

## Detailed Findings

### ✅ Fully Compliant
[List compliant aspects]

### ⚠️ Partial Compliance
[List partial implementations with details]

### ❌ Non-Compliant
[List violations with:
- Plan reference (file:line)
- Expected vs Actual
- Impact assessment
- Priority
- Recommended action]

## Architecture Drift
[List intentional or unintentional deviations]

## Recommendations
### High Priority
[Critical items]

### Medium Priority
[Important items]

### Low Priority
[Nice to have items]

## Next Steps
[Actionable next steps]

Example Usage

Scenario 1: Initial Validation

# After reading all plan files
# Extract 50+ architectural elements
# Validate against codebase
# Generate report: 75% compliance, 5 critical issues

Scenario 2: Post-Refactoring

# Re-validate after major changes
# Check for new violations
# Verify planned improvements implemented
# Generate diff report

Scenario 3: Architecture Review Prep

# Comprehensive validation
# Document all drift
# Prepare justifications
# Generate presentation-ready report

Integration with Agent

This skill is used by the architecture-validator agent to:

  1. Provide validation patterns and utilities
  2. Define report formats
  3. Establish compliance criteria
  4. Guide systematic validation process

Validation Commands

Discovery

# Find all plans
ls -1 plans/*.md | wc -l

# Check plan structure
head -20 plans/README.md

Extraction

# Extract all architectural keywords
for file in plans/*.md; do
  echo "=== $file ==="
  grep -i "decision:\|requirement:\|target:\|constraint:" "$file"
done

Analysis

# Compare planned vs actual
echo "Planned crates:" && grep -rh "crate" plans/ | wc -l
echo "Actual crates:" && find . -name "Cargo.toml" | wc -l

Validation

# Check specific requirement
grep -r "requirement X" plans/
rg "implementation of X" --type rust

Best Practices

  1. Start with README: Read plans/README.md first to understand structure
  2. Read all plans: Don't skip any plan files
  3. Extract systematically: Use consistent patterns across all files
  4. Be specific: Always reference exact file and line numbers
  5. Assess impact: Explain why violations matter
  6. Provide solutions: Give clear remediation steps
  7. Track evolution: Compare current vs previous validations

Edge Cases

  • No plans folder: Report that validation cannot proceed
  • Empty plans: Report insufficient documentation
  • Conflicting plans: Flag conflicts for resolution
  • Outdated plans: Note discrepancies and suggest updates
  • Ambiguous plans: Request clarification
  • Multiple architectures: Validate each separately

Metrics

Track validation quality:

  • Plan Coverage: % of plan files analyzed
  • Element Coverage: % of architectural elements checked
  • Validation Depth: How thoroughly each element validated
  • Finding Quality: Specificity and actionability of findings
  • Report Completeness: All sections filled out

Self-Learning Framework

This skill enables self-learning and continuous improvement by learning from validation results.

Learning Cycle

Validate → Identify Issues → Analyze Root Cause → Update Documentation → Re-validate
    ↑                                                                            ↓
    └────────────────────────── Feedback Loop ──────────────────────────────────┘

Learning Triggers

Trigger 1: Repeated Violations

  • Same violation appears 3+ times
  • May indicate plan is outdated or unrealistic
  • Action: Review and potentially update plan

Trigger 2: False Positives

  • Validator reports violations for correct code
  • Indicates validation logic needs refinement
  • Action: Update agent/skill validation patterns

Trigger 3: New Patterns Emerge

  • Implementation uses patterns not documented
  • Patterns appear beneficial
  • Action: Document new patterns in plans

Trigger 4: Plan-Reality Mismatch

  • Consistent drift between plan and implementation
  • Implementation is actually better
  • Action: Update plan to reflect reality

Self-Update Protocol

Phase 1: Detect Learning Opportunity

# After validation, analyze:
# - Number of violations by type
# - Pattern frequency
# - False positive rate
# - User feedback on findings

# If thresholds exceeded, trigger learning

Phase 2: Root Cause Analysis

# Determine root cause:
# - Is the plan outdated? → Update plan
# - Is validation incomplete? → Update agent/skill
# - Is implementation wrong? → Report to user
# - Is this a new valid pattern? → Document pattern

Phase 3: Update Documentation

# Update appropriate files:

# Option A: Update Plans
# - plans/00-overview.md: If project scope changed
# - plans/01-understand.md: If requirements changed
# - plans/02-plan.md: If architecture evolved
# - plans/03-execute.md: If implementation patterns changed
# - plans/04-review.md: If quality criteria changed
# - plans/05-secure.md: If security model changed
# - plans/06-feedback-loop.md: Document the learning

# Option B: Update Agent/Skill
# - .claude/agents/architecture-validator.md: Update validation logic
# - .claude/skills/architecture-validation/SKILL.md: Update patterns

# Option C: Update Other Claude Files
# - .claude/CLAUDE.md: If workflow changes
# - Related skill files: If validation changes affect them

Phase 4: Verification

# After updates:
# 1. Re-run validation
# 2. Confirm issue resolved
# 3. Check for new issues
# 4. Document learning

Learning Examples

Example 1: Outdated Dependency Rule

Violation: "Core depends on storage implementation"
Frequency: 10 occurrences
Analysis: Dependency is intentional and beneficial
Learning: Rule too strict for current architecture
Action:
  1. Edit plans/02-plan.md: Update dependency rules
  2. Document rationale: "Direct dependency acceptable for X reason"
  3. Edit architecture-validator.md: Remove overly strict check
  4. Document in plans/06-feedback-loop.md

Example 2: Missing Validation Pattern

Issue: New async pattern not validated
Frequency: 5 instances found manually
Analysis: Validation extraction patterns incomplete
Learning: Need to check for async patterns
Action:
  1. Edit architecture-validator.md: Add async pattern checks
  2. Edit SKILL.md: Document async validation
  3. Re-run validation: Confirm new patterns detected

Example 3: New Architecture Pattern

Discovery: Code uses Circuit Breaker pattern
Status: Not documented in plans
Analysis: Pattern is beneficial, should be standard
Learning: Update plans to include pattern
Action:
  1. Edit plans/02-plan.md: Add Circuit Breaker section
  2. Edit plans/03-execute.md: Document implementation
  3. Edit architecture-validator.md: Validate circuit breakers
  4. Document in plans/06-feedback-loop.md

Files to Update

Plans (plans/):

  • Update when architecture evolves
  • Document new patterns
  • Revise constraints
  • Add learnings to 06-feedback-loop.md

Agent (.claude/agents/architecture-validator.md):

  • Update validation logic
  • Add new extraction patterns
  • Refine reporting
  • Document self-learning improvements

Skill (.claude/skills/architecture-validation/SKILL.md):

  • Update validation dimensions
  • Add new patterns
  • Refine workflows
  • Document examples

Other Claude Files (.claude/):

  • CLAUDE.md: Update if workflow changes
  • Related skills: Update if validation changes affect them
  • Agent coordination files: Update if dependencies change

Learning Metrics

Track learning effectiveness:

  • Learning Rate: Updates per week
  • False Positive Reduction: % decrease over time
  • Coverage Improvement: New patterns detected
  • Plan Accuracy: Plan-reality alignment
  • Validation Quality: User satisfaction with findings

Learning History Format

In plans/06-feedback-loop.md:

## Architecture Validator Learnings

### [Date]: Dependency Rule Refinement
**Issue**: Core-Storage dependency flagged incorrectly
**Analysis**: Rule too strict, dependency is intentional
**Action**: Updated plans/02-plan.md lines 45-50
**Result**: False positives reduced from 10 to 0
**Status**: ✅ Verified

### [Date]: New Pattern Recognition
**Issue**: Circuit Breaker pattern not validated
**Analysis**: Pattern is widely used, should validate
**Action**: Updated architecture-validator.md, added extraction
**Result**: Now detects 5 instances of pattern
**Status**: ✅ Verified

Continuous Improvement

Weekly Review:

  • Review validation results
  • Identify improvement opportunities
  • Update documentation
  • Refine validation logic

Monthly Retrospective:

  • Assess learning metrics
  • Major architecture changes
  • Plan substantial updates
  • Validate learning effectiveness

Quarterly Audit:

  • Comprehensive review of plans
  • Major agent/skill updates
  • Architecture evolution assessment
  • Long-term pattern analysis

Updates and Versioning

Version 2.0.0 Changes:

  • Made validation fully generic and plan-driven
  • Removed hardcoded architectural assumptions
  • Added dynamic element extraction
  • Enhanced pattern matching capabilities
  • Improved report generation
  • Added comprehensive edge case handling
  • Added self-learning and adaptation framework
  • Integrated feedback loop for continuous improvement
  • Enabled automatic plan and agent updates

Related Skills

  • plan-gap-analysis: Analyzes gaps between plans and implementation
  • rust-code-quality: Validates Rust-specific code quality
  • code-reviewer: Reviews code changes for quality
  • episode-complete: For recording validation learnings in memory system

Resources

  • Agent: .claude/agents/architecture-validator.md
  • Plans: plans/*.md
  • Project guidelines: AGENTS.md, CLAUDE.md
  • Learning history: plans/06-feedback-loop.md

Last Updated: 2025-11-12 Status: Active Maintenance: Self-updating based on validation learnings Learning Enabled: Yes