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save-usage节省使用量

Agent Skill

save-usage 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

20,168

周安装

808

GitHub Stars

公开资料未说明

下载量

6,529
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-usage(节省使用量)
来源仓库:https://github.com/jacks3tr/save-usage
安装命令:
openclaw skills install save-usage
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-usage

简介

按安全性和复杂性对任务进行分类,以将安全、可忽略的查询路由到 gpt-5.1-codex-mini,并将关键或可执行任务升级到 gpt-5.3-codex。

SKILL.md

name
save-usage
description
>-

Save usage

Run on gpt-5.1-codex-mini only for safe/negligible work. Use gpt-5.3-codex when the task actually needs it. Avoid external API keys unless absolutely necessary.

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 costs little. A wrong “mini” answer can waste time or cause damage.

Rule of Thumb

If anything will be executed, or the outcome matters, escalate.

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: "gpt-5.3-codex",
	label: "<short task label>"
)

Escalation triggers (always)

  • Executed output — any tool runs, code changes, patches, shell commands, infra steps
  • Security / auth / secrets — threat modeling, permissions, tokens, keys, access control
  • Architecture & migrations — multi-epic plans, brownfield refactors, infra+product coupling
  • Integration/contract work — schema mapping, ordering, idempotency, retries, consistency
  • Uncertainty remains — ambiguity after 1 pass, contradictions, missing constraints
  • High-impact decisions — hard to reverse, expensive/subtle failure modes, 2+ domains affected
  • Complex reasoning — long dependency chains, multi-step analysis, nontrivial trade-offs
  • Structured deliverables — tables, outlines, reports/proposals, long writing, specs

Reasoning escalation (within gpt-5.3-codex)

  • Default: LOW/MEDIUM
  • Escalate to HIGH/EXTRA HIGH if 2+ are true:

- decision is hard to reverse - affects 2+ domains (infra/data/security/ops/cost) - failure modes are subtle/expensive - requires long dependency-chain reasoning

NEVER do this on gpt-5.1-codex-mini

  • NEVER output steps that will be executed (tools, code, commands) — escalate
  • NEVER do security/auth/secrets — escalate
  • NEVER do architecture, migrations, brownfield refactors — escalate
  • NEVER do integration contracts or schema choreography — escalate
  • NEVER produce structured deliverables (tables/outlines/reports/specs) — escalate
  • NEVER make high-impact decisions or complex reasoning chains — escalate

If you catch yourself taking responsibility for correctness or safety, STOP and call sessions_spawn instead.

When to Stay on gpt-5.1-codex-mini

Only if safe/negligible and non-executable:

  • Intent routing / triage — classify, choose agent/model/reasoning
  • Summaries & extraction — key points, action items, fields, dedupe
  • Reformatting — convert to markdown/YAML/JSON templates (non-executable)
  • Prompt drafts — write a prompt for a stronger agent/model to run
  • Simple Q&A — definitions, short explanations, short translations, unit conversions
  • Casual chat — greetings, short acknowledgments

Keep mini replies concise.

Save even more: de-escalate

If a conversation was escalated to gpt-5.3-codex but the follow-up is clearly safe/negligible and non-executable, switch back to gpt-5.1-codex-mini.

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

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, reasoning levels, and usage tips that the model can reference if it reads the file.

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


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

94.05%
按下载量换算6,141

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-usage 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

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