Agent skill

mecw-patterns

MECW theory and patterns for hallucination prevention via context management. Implements 50% rule. Triggers: MECW, context window, hallucination, 50% rule, context pressure Use when: implementing context-aware systems or monitoring context pressure

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Install this agent skill to your Project

npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/devops/mecw-patterns-athola-claude-night-market

SKILL.md

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

python
from leyline import calculate_context_pressure

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

Full Compliance Check

python
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']}")

Continuous Monitoring

python
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}")

Detailed Topics

For detailed implementation patterns:

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:

yaml
dependencies: [leyline:mecw-patterns]

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

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