AgentSkillsCN

context-optimization

在开始复杂任务之前,请主动检查上下文使用情况。适用于上下文使用率接近窗口容量的50%、任务需要拆解、计划执行复杂多步骤操作、上下文压力较高时使用此技能。切勿在上下文使用率较低、仅需执行简单单步任务时使用此技能。切勿在已经使用mcp-code-execution来管理工具链时使用此技能。

SKILL.md
--- frontmatter
name: context-optimization
description: 'Use this skill BEFORE starting complex tasks. Check context levels proactively.
  Use when context usage approaches 50% of window, tasks need decomposition, complex
  multi-step operations planned, context pressure is high. Do not use when simple
  single-step tasks with low context usage. DO NOT use when: already using mcp-code-execution
  for tool chains.'
category: conservation
token_budget: 150
progressive_loading: true
hooks:
  PreToolUse:
  - matcher: Read
    command: 'echo "[skill:context-optimization] 📊 Context analysis started: $(date)"
      >> ${CLAUDE_CODE_TMPDIR:-/tmp}/skill-audit.log

      '
    once: true
  PostToolUse:
  - matcher: Bash
    command: "# Track context analysis tools\nif echo \"$CLAUDE_TOOL_INPUT\" | grep\
      \ -qE \"(wc|tokei|cloc|context)\"; then\n  echo \"[skill:context-optimization]\
      \ Context measurement executed: $(date)\" >> ${CLAUDE_CODE_TMPDIR:-/tmp}/skill-audit.log\n\
      fi\n"
  Stop:
  - command: 'echo "[skill:context-optimization] === Optimization completed at $(date)
      ===" >> ${CLAUDE_CODE_TMPDIR:-/tmp}/skill-audit.log

      # Could export: context pressure events over time

      '
version: 1.4.0

Table of Contents

Context Optimization Hub

Quick Start

Basic Usage

bash
# 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

python
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

UtilizationStatusAction
< 30%LOWContinue normally
30-50%MODERATEMonitor, apply principles
> 50%CRITICALImmediate 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

ScenarioBefore 2.1.2After 2.1.2
Large test outputTruncated, partial dataFull output via file reference
Verbose build logsLost after 30K charsComplete, accessible on-demand
Context pressureLess from truncationSame - 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.
  • 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.