Table of Contents

• Quick Start
• When to Use
• Core Hub Responsibilities
• Module Selection Strategy
• Context Classification
• Integration Points
• Resources

Context Optimization Hub

Quick Start

Basic Usage

# Analyze current context usage
python -m conserve.context_analyzer

When To Use

• Threshold Alert: When context usage approaches 50% of the window.
• Complex Tasks: For operations requiring multi-file analysis or long tool chains.

When NOT To Use

• Simple single-step tasks with low context usage
• Already using mcp-code-execution for tool chains

Core Hub Responsibilities

1. Assess context pressure and MECW compliance.
2. Route to appropriate specialized modules.
3. Coordinate subagent-based workflows.
4. Manage token budget allocation across modules.
5. Synthesize results from modular execution.

Module Selection Strategy

def select_optimal_modules(context_situation, task_complexity):
    if context_situation == "CRITICAL":
        return ['mecw-assessment', 'subagent-coordination']
    elif task_complexity == 'high':
        return ['mecw-principles', 'subagent-coordination']
    else:
        return ['mecw-assessment']

Context Classification

Utilization	Status	Action
< 30%	LOW	Continue normally
30-50%	MODERATE	Monitor, apply principles
> 50%	CRITICAL	Immediate optimization required

Large Output Handling (Claude Code 2.1.2+)

Behavior Change: Large bash command and tool outputs are saved to disk instead of being truncated; file references are provided for access.

Impact on Context Optimization

Scenario	Before 2.1.2	After 2.1.2
Large test output	Truncated, partial data	Full output via file reference
Verbose build logs	Lost after 30K chars	Complete, accessible on-demand
Context pressure	Less from truncation	Same - only loaded when read

Best Practices

• Avoid pre-emptive reads: Large outputs are referenced, not automatically loaded into context.
• Read selectively: Use head, tail, or grep on file references.
• Leverage full data: Quality gates can access complete test results via files.
• Monitor growth: File references are small, but reading the full files adds to context.

Integration Points

• Token Conservation: Receives usage strategies, returns MECW-compliant optimizations.
• CPU/GPU Performance: Aligns context optimization with resource constraints.
• MCP Code Execution: Delegates complex patterns to specialized MCP modules.

Resources

• MECW Theory: See modules/mecw-principles.md for core concepts and the 50% rule.
• MECW Theory (Extended): See modules/mecw-theory.md for pressure levels, compliance checking, and monitoring patterns.
• Context Analysis: See modules/mecw-assessment.md for risk identification.
• Workflow Delegation: See modules/subagent-coordination.md for decomposition patterns.
• Context Waiting: See modules/context-waiting.md for deferred loading strategies.

Troubleshooting

Common Issues

If context usage remains high after optimization, check for large files that were read entirely rather than selectively. If MECW assessments fail, ensure that your environment provides accurate token count metadata. For permission errors when writing output logs to /tmp, verify that the project's temporary directory is writable.