Table of Contents

• Overview
• When to Use
• Core Principle: The 50% Rule
• Pressure Levels
• Quick Start
• Basic Pressure Check
• Full Compliance Check
• Continuous Monitoring
• Detailed Topics
• Best Practices
• Integration with Other Skills
• Exit Criteria

MECW Patterns

Overview

Maximum Effective Context Window (MECW) patterns provide the theoretical foundations and practical utilities for managing context window usage to prevent hallucinations. The core principle: Never use more than 50% of total context window for input content.

When to Use

• Need to prevent hallucinations in long-running sessions
• Managing context-heavy workflows
• Building systems that process large amounts of data
• Want proactive context pressure monitoring
• Require safe token budget calculation

Core Principle: The 50% Rule

Context pressure increases non-linearly as usage approaches limits. Exceeding 50% of context window significantly increases hallucination risk.

Pressure Levels

Level	Usage	Effect	Action
LOW	<30%	Optimal performance, high accuracy	Continue normally
MODERATE	30-50%	Good performance, within MECW	Monitor closely
HIGH	50-70%	Degraded performance, risk zone	Optimize immediately
CRITICAL	>70%	Severe degradation, high hallucination	Reset context

Quick Start

Basic Pressure Check

from leyline import calculate_context_pressure

pressure = calculate_context_pressure(
    current_tokens=80000,
    max_tokens=200000
)
print(pressure)  # "MODERATE"

Verification: Run the command with --help flag to verify availability.

Full Compliance Check

from leyline import check_mecw_compliance

result = check_mecw_compliance(
    current_tokens=120000,
    max_tokens=200000
)

if not result['compliant']:
    print(f"Overage: {result['overage']:,} tokens")
    print(f"Action: {result['action']}")

Verification: Run the command with --help flag to verify availability.

Continuous Monitoring

from leyline import MECWMonitor

monitor = MECWMonitor(max_context=200000)

# Track usage throughout session
monitor.track_usage(80000)
status = monitor.get_status()

if status.warnings:
    for warning in status.warnings:
        print(f"[WARN] {warning}")

if status.recommendations:
    print("\nRecommended actions:")
    for rec in status.recommendations:
        print(f"  • {rec}")

Verification: Run the command with --help flag to verify availability.

Detailed Topics

For detailed implementation patterns:

• MECW Theory - Theoretical foundations, research basis, thresholds
• Monitoring Patterns - Integration patterns, quota management, token estimation
• Prevention Strategies - Early detection, compression, delegation, progressive disclosure

Best Practices

1. Plan for 40%: Design workflows to use ~40% of context, leaving buffer
2. Buffer for Response: Leave 50% for model reasoning + response generation
3. Monitor Continuously: Check context at each major step
4. Fail Fast: Abort and restructure when approaching limits
5. Document Aggressively: Keep summaries for context recovery after reset

Integration with Other Skills

This skill provides foundational utilities referenced by:

• conserve:context-optimization - Uses MECW for optimization decisions
• conjure:delegation-core - Uses MECW for delegation triggers
• Plugin authors building context-aware systems

Reference in your skill's frontmatter:

dependencies: [leyline:mecw-patterns]

Verification: Run the command with --help flag to verify availability.

Exit Criteria

• Context pressure monitored before major operations
• MECW compliance checked when loading large content
• Safe budget calculated before batch operations
• Recommendations followed when warnings issued
• Context reset triggered before CRITICAL threshold

Troubleshooting

Common Issues

Command not found Ensure all dependencies are installed and in PATH

Permission errors Check file permissions and run with appropriate privileges

Unexpected behavior Enable verbose logging with --verbose flag