Token导航 LogoToken导航TokenDH.com
开发执行命令clawhub未标认证来源可访问clear审计通过

save-money-4-2-0省钱 4 2 0

Agent Skill

save-money-4-2-0 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

11,025

周安装

464

GitHub Stars

公开资料未说明

下载量

3,860
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:save-money-4-2-0(省钱 4 2 0)
来源仓库:https://github.com/sieyer/save-money-4-2-0
安装命令:
openclaw skills install save-money-4-2-0
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 save-money-4-2-0

简介

智能选择 Claude Haiku 或 Sonnet 模型以降低 API 成本。

  • 根据任务复杂度自动切换,节省超过 50% 费用。
  • 适用于高频简单请求与低频复杂请求混合场景。
  • 安装命令:openclaw skills install save-money-4-2-0。
  • 需启用 OpenClaw 内部模型调度接口支持。

SKILL.md

name
save-money
description
>-
author
小安 Ann Agent — Taiwan 台灣
homepage
https://github.com/peterann/save-money
metadata
clawdbot
emoji
🧠

Save Money

Run on Haiku by default. Only spawn Sonnet when the task actually needs it. Save 50%+ on API costs.

CRITICAL: Classify First, Then Act

Before generating ANY response, you MUST:

  1. Check: does this task match ANY escalation trigger below?
  2. If YES → call sessions_spawn() IMMEDIATELY. Do NOT attempt to answer yourself.
  3. If NO → respond directly on the current model.

When in doubt, escalate. A wrong escalation only costs a few cents. A bad answer on Haiku wastes the user's time.

Rule of Thumb

If a human would need more than 30 seconds of focused thinking, escalate. 如果一個人需要超過 30 秒的專注思考才能完成,就升級模型。

When to Escalate → MUST call sessions_spawn

If the task matches ANY of the following, do NOT answer yourself. Instead, IMMEDIATELY call:

sessions_spawn(
  message: "<the full task description>",
  model: "anthropic/claude-sonnet-4-20250514",
  label: "<short task label>"
)

Escalation triggers

  • Analysis & evaluation — compare options, assess trade-offs, review documents
  • Planning & strategy — project plans, roadmaps, business models, architecture
  • Long-form writing — reports, proposals, articles, presentations, emails > 3 paragraphs
  • Code generation — write functions, build features, refactor, debug complex issues
  • Multi-step reasoning — anything with "first... then... finally" or numbered steps
  • Summarize large content — long documents, full articles, meeting transcripts
  • Long translation — paragraphs or full documents (not single sentences)
  • Creative writing — copywriting, ad scripts, naming with brand constraints
  • Structured output — tables, outlines, formatted documents, comparison charts

By how people actually ask

LanguageEscalate — real examples
English"Can you analyze this for me?", "Write me a report on...", "Help me plan...", "What are the pros and cons?", "Build a script that...", "Compare A vs B", "Step by step, how do I...", "Draft a proposal for..."
繁體中文"欸幫我看一下這個報告", "幫我想一下怎麼回客戶", "這兩個方案哪個比較好", "寫一封信給老闆", "幫我整理一下這份資料", "我該怎麼處理這個問題", "可以幫我寫一個程式嗎", "幫我規劃一下行程", "有什麼辦法可以改善", "這個東西要怎麼設計比較好"
日本語"これを分析してもらえますか", "レポートを書いてください", "計画を立ててほしい", "AとBを比較して", "コードを書いてほしい", "この資料をまとめて", "提案書を作って", "どうすればいいか考えて"
한국어"이거 분석해줘", "보고서 작성해줘", "계획 세워줘", "A랑 B 비교해줘", "코드 짜줘", "이 자료 정리해줘", "제안서 만들어줘", "어떻게 하면 좋을까?"
Deutsch"Kannst du das analysieren?", "Schreib mir einen Bericht", "Hilf mir das zu planen", "Vergleich A mit B", "Schreib ein Skript für...", "Fass das zusammen", "Wie soll ich das lösen?", "Erstell einen Entwurf"

By complexity signals

  • Prompt is longer than 200 characters with specific requirements
  • Contains multiple conditions or constraints
  • Asks for structured output (tables, outlines, formatted documents)
  • Professional context: proposal, presentation, resume, contract

NEVER do this on Haiku

  • NEVER write a comparison table yourself — escalate
  • NEVER write code longer than 10 lines yourself — escalate
  • NEVER write more than 3 paragraphs yourself — escalate
  • NEVER do multi-step analysis yourself — escalate
  • NEVER write a report or proposal yourself — escalate
  • NEVER attempt complex reasoning chains yourself — escalate

If you catch yourself writing a long response for a complex task, STOP and call sessions_spawn instead.

When to Stay on Haiku

  • Factual Q&A — "what is X", "who is Y", "when did Z happen"
  • Quick lookups — definitions, short translations (single sentences), unit conversions
  • Memory & reminders — "remember this", "remind me to..."
  • Casual conversation — greetings, small talk, jokes
  • Status checks — "what's on my calendar", simple file reads
  • One-liner tasks — anything answerable in 1-2 sentences
LanguageStay — real examples
English"What's the weather?", "Remind me at 3pm", "What does OKR mean?", "Translate: thank you", "Hey what's up"
繁體中文"今天天氣怎樣", "幫我記一下明天要開會", "這個字什麼意思", "現在幾點", "嗨", "謝謝", "OK", "查一下匯率", "翻譯一下 thank you"
日本語"天気は?", "意味を教えて", "これ何?", "おはよう", "リマインドして", "ありがとう"
한국어"날씨 어때?", "뜻이 뭐야?", "이게 뭐야?", "안녕", "알림 설정해줘", "고마워"
Deutsch"Wie ist das Wetter?", "Was bedeutet das?", "Was ist das?", "Hallo", "Erinner mich um 3", "Danke"

Save even more: keep responses short

When on Haiku, keep replies concise. Fewer output tokens = lower cost.

  • Simple question → 1-2 sentence answer, don't over-explain
  • Lookup → give the answer, skip the preamble
  • Greeting → short and warm, no essays

Save even more: de-escalate

If a conversation was escalated to Sonnet but the follow-up is simple, switch back to Haiku.

  • User: "幫我分析這份報告" → Sonnet ✓
  • User: "好,那就用第一個方案" → back to Haiku ✓
  • User: "幫我記住這個結論" → Haiku ✓

Don't stay on the expensive model just because the conversation started there.

Return the result directly. Do NOT mention the model switch unless the user asks.

Other providers

This skill is written for Claude (Haiku + Sonnet). Swap model names for other providers:

RoleClaudeOpenAIGoogle
Cheap (default)claude-3-5-haikugpt-4o-minigemini-flash
Strong (escalate)claude-sonnet-4gpt-4ogemini-pro

Why the description field is so long

The Clawdbot skill system only injects the frontmatter description field into the system prompt — the body of SKILL.md is not automatically included. The model may optionally read the full file, but it is not guaranteed. Because this is a behavioral skill (changing how the model routes every message) rather than a tool skill (teaching CLI commands), the core routing logic must live in the description so the model always sees it.

The body above serves as extended documentation: detailed trigger lists, multilingual examples, and usage tips that the model can reference if it reads the file.

TL;DR: description = what the model always sees. body = reference docs.


*小安 Ann Agent — Taiwan 台灣* *Building skills and local MCP services for all AI agents, everywhere.* *為所有 AI Agent 打造技能與在地 MCP 服務,不限平台。*

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

87.08%
按下载量换算3,361

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

未展示

权限和风险

执行命令

安装流程涉及命令执行,可能通过 openclaw skills install save-money-4-2-0 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

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

继续浏览同类 Skills