SKILL_AUTOMATIC_REMEDIATION

Automatic Remediation Skill - Phase 2 Stage 4

Version: 1.0.0 Status: Production Ready ✅ Date: December 22, 2025 Phase: 2 Stage 4 - Automatic Remediation Tests: 10/10 Passing

---

Overview

Intelligent automatic detection and remediation of proof system issues using cache statistics from the navigation cache (Stage 3). Maintains system health while respecting LHoTT resource constraints through four targeted remediation strategies.

Quick Stats:

• 300+ lines of core code (2 modules)
• 400+ lines of tests (10 tests, 10/10 PASS ✅)
• <1ms per operation (well under performance targets)
• Zero external dependencies
• Full Julia language implementation
• Integrated with Phase 2 Stages 1-3 modules

---

Problem Statement

Current Challenges:

• Low cache hit rates indicate weak proof organization
• High resource costs suggest inefficient proof paths
• Low success rates indicate unreliable proofs
• Resource exhaustion prevents further navigation
• Manual intervention required for system recovery

With Automatic Remediation:

• Automatic issue detection using cache statistics
• Intelligent plan generation ranking strategies by effectiveness
• Safe remediation execution with constraint verification
• Health-aware rollback on failures
• Continuous system optimization without human intervention

---

Capabilities

Core Data Structures

RemediationIssue - Detected proof system problem:

mutable struct RemediationIssue
    issue_id::String                      # Unique ID
    issue_type::Symbol                    # :low_hit_rate, :high_cost, :low_success
    theorem_id::Int                       # Affected theorem
    severity::Float64                     # 0.0-1.0 severity score
    current_value::Float64                # Current metric value
    target_value::Float64                 # Desired metric value
    recommended_strategies::Vector{Symbol} # Applicable strategies
    timestamp::Float64                    # Detection time
end