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nm-conserve-context-optimizationNM conserve context optimization 开发

Agent Skill

nm-conserve-context-optimization 用于补充开发相关能力,适合在 OpenClaw 中需要让 Agent 承接开发相关任务时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

2,851

周安装

120

GitHub Stars

公开资料未说明

下载量

998
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:nm-conserve-context-optimization(NM conserve context optimization 开发)
来源仓库:https://github.com/athola/nm-conserve-context-optimization
安装命令:
openclaw skills install nm-conserve-context-optimization
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install nm-conserve-context-optimization

简介

运用 MECW 原则分层管理内存与路由会话路径。

  • 适合在 OpenClaw 中处理超长对话历史时使用。
  • 核心能力是多维度优化上下文空间利用率。
  • 使用 clawhub 安装,需启用高级内存管理选项。
  • 注意检查是否兼容现有子代理调度机制。nm-conserve-context-optimization 属于开发类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

name
context-optimization
description
|
version
1.8.2
metadata
{"openclaw": {"homepage": "https://github.com/athola/claude-night-market/tree/master/plugins/conserve", "emoji": "\�\�"}}
source
claude-night-market
source_plugin
conserve
Night Market Skill — ported from claude-night-market/conserve. For the full experience with agents, hooks, and commands, install the Claude Code plugin.

Table of Contents

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

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.
  • 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.

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

81.95%
按下载量换算818

安全审计

VirusTotal

通过

ClawScan

可疑

Static analysis

通过

权限和风险

external-service

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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