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prompt-token-saver提示令牌保存程序

Agent Skill

用于辅助提示词、系统指令、Agent 行为约束和工作流模板的整理。它适合让 Agent 规范任务边界、统一输出格式、拆分操作步骤或优化提示词可复用性。使用时需要保留真实业务约束,不要把示例当硬规则;涉及自动执行、外部工具或高风险操作时,应在提示词中明确确认步骤、权限边界和失败处理方式。

总安装

7,543

周安装

324

GitHub Stars

公开资料未说明

下载量

2,644
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:prompt-token-saver(提示令牌保存程序)
来源仓库:https://github.com/ckpxgfnksd-max/prompt-token-saver
安装命令:
openclaw skills install prompt-token-saver
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 prompt-token-saver

简介

通过压缩响应、内存日志等方式节省 20%-40% LLM token。

  • 引导代理编写紧凑输出并采用预压缩摘要策略。prompt-token-saver 属于开发类 Skill,可作为该场景下的辅助能力补充。
  • 适用于高并发或成本敏感型 AI 应用场景。
  • 需在工作区 SO 文件中定义压缩规则与策略模板。
  • 过度压缩可能影响输出质量,应平衡效率与信息完整性。

SKILL.md

name
prompt-compressor
description
Saves 20-40% of LLM tokens by teaching the agent to write compressed responses, compressed memory logs, and compressed pre-compaction summaries. Works via SOUL.md instructions — no hooks, no extra process, no dependencies. Also provides explicit compression when the user asks to compress a prompt. Use when the user asks about reducing token costs, optimizing API spend, compressing prompts, or making the agent more efficient.
version
1.0.0
metadata
{"openclaw":{"emoji":"🗜️","homepage":"https://github.com/ckpxgfnksd-max/prompt-compressor-openclaw"}}

Prompt Compressor

Saves tokens on turns 2+ by making all agent output compressed from the start.

How it works

This is NOT a hook (hooks require newer OpenClaw versions). Instead, it works by adding instructions to SOUL.md that make the agent:

  1. Write compressed responses — no filler, no hedging, lead with answers
  2. Write compressed MEMORY.md — one fact per line, no narrative
  3. Write compressed daily logs — decisions only, not discussions
  4. Compress pre-compaction flushes — facts not paragraphs

The savings compound: compressed responses → compressed history → compressed compaction summaries → fewer tokens on every subsequent turn.

Install

Append the contents of soul-snippet.md to the user's SOUL.md:

cat {baseDir}/soul-snippet.md >> ~/.openclaw/SOUL.md

Or if using a workspace SOUL.md:

cat {baseDir}/soul-snippet.md >> <workspace>/SOUL.md

Then start a new session (/new) so the updated SOUL.md loads.

When user asks to compress a specific prompt

Apply these rules manually to their text:

Remove

  • Greetings: "Hello", "Hi", "Hey", "Good morning"
  • Sign-offs: "Thanks", "Best regards", "Cheers"
  • Hedging: "Could you please", "I was wondering if", "Would you be able to"
  • Filler: "just", "really", "very", "basically", "actually", "literally", "honestly"
  • Padding: "I think that", "In my opinion", "It is worth mentioning"

Shorten

  • "due to the fact that" → "because"
  • "in order to" → "to"
  • "with regard to" → "about"
  • "take into consideration" → "consider"
  • "come up with" → "create"
  • "figure out" → "determine"
  • "a large number of" → "many"
  • "at this point in time" → "now"
  • "for the purpose of" → "to"
  • "it is important to note that" → "note:"
  • "it would be a good idea to" → remove entirely

Normalize

  • "yeah", "yep", "yup" → "yes"
  • "nah", "nope" → "no"

Never touch

  • Code blocks, inline code, URLs, quoted strings, numbers, file paths, ALL_CAPS

Rules

  • When installing, ALWAYS append to SOUL.md, never overwrite it
  • Tell the user to run /new after installation so the new SOUL.md loads
  • Show a before/after example so the user sees the difference

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

98.93%
按下载量换算2,616

安全审计

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通过

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权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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。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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