将回复压缩为极简风格,同时保留技术准确性
复制安装指令,让 AI 自动完成配置 · 推荐新手
请帮我安装 askskill 上的 "caveman" 技能: 1. 下载 https://raw.githubusercontent.com/microsoft/hve-core/main/.github/skills/experimental/caveman/SKILL.md 2. 保存为 ~/.claude/skills/caveman/SKILL.md 3. 装好后重载技能,告诉我可以用了
请开启 caveman full 模式,后续回答尽量压缩。
进入压缩回复风格,去掉虚词与寒暄,但保留技术内容。
/caveman ultra 解释一下这段报错的原因。
给出更短、更电报式的解释,必要时只保留关键信息。
停止 caveman,恢复正常详细回答。
恢复默认更完整的表达风格。
开发者或研究者在看代码、报错、命令行输出时,希望答案更短但仍保持准确。这个技能会压缩措辞,同时保留代码、标识符和错误信息原样。
当用户明确要求进入某种压缩模式时,它会依据聊天记录里的最新指令持续生效,直到用户切回正常模式。
用户可以选择 lite、full、ultra 或 wenyan,不同等级决定压缩力度与语言风格。
Caveman 是一种可选的回复风格,用更少的词输出,但尽量保持技术内容完整准确。文档说明了它如何通过聊天记录中的激活指令持续生效、何时关闭,以及 lite、full、ultra、wenyan 四种强度等级。它还强调:generic brevity 只影响当前回复,不等于进入持续模式。
Caveman is an opt-in response style that reduces output verbosity while keeping technical content fully intact. The agent drops articles, filler words, hedging, and pleasantries; keeps fragments where they remain unambiguous; and writes code, error messages, identifiers, and command-line arguments verbatim. Use it when the user explicitly requests a terser response.
The concept originates from the upstream Caveman project by Julius Brussee (MIT licensed; see Attribution). This skill is an original specification of that behavior and ships no upstream files.
Caveman has no out-of-band state store, daemon, or hook. Persistence relies entirely on the conversation transcript:
/caveman ultra, "use caveman", and similar) stays visible in chat history.caveman/SKILL.md the next time an active directive appears.State lives in chat, not in a file. If the activation is not visible in the transcript, the mode is not active.
Activate Caveman when the user asks for it directly:
/caveman or /caveman <level> where <level> is one of lite, full, ultra, wenyanDo not activate on generic brevity requests such as "be brief", "less tokens", "terser output", or "save tokens". Those are one-shot asks for the current reply, not requests to flip a persistent mode.
Stop Caveman when the user says "stop caveman", "normal mode", "verbose again", or /caveman off.
| Level | Behavior |
|---|---|
lite | Drop filler and hedging. Keep articles and full sentences. |
full (default) | Drop articles. Sentence fragments allowed. Short synonyms. |
ultra | Telegraphic. One-word answers when sufficient. Arrows for flow. |
wenyan | Classical Chinese (文言) register layered on full compression. |
If the user requests /caveman without a level, default to full. /caveman wenyan applies the wenyan register at full compression. Combine with another level for stronger compression, e.g. /caveman wenyan ultra.
Always drop:
Always keep, exact and unmodified:
Pattern: [thing] [action] [reason]. [next step].
Switch off Caveman automatically — without being asked — when any of the following apply, then resume after the section ends:
…
它把回复压缩得更短,同时尽量保留技术准确性。支持不同强度,并有自动清晰度规则,避免关键信息丢失。
可用“use caveman”“caveman mode”或`/caveman <level>`开启;用“stop caveman”“normal mode”“verbose again”或`/caveman off`关闭。
不会有额外状态存储;是否生效取决于聊天记录里是否还能看到最新激活指令。记录清空、对话结束或指令不可见时就会关闭。
为设计思维教练提供身份、流程与状态基线
帮助你写出更规范、可维护的 Python 代码
将设计思维成果整理为可交接的 RPI 输入与上下文
通过 Python CLI 自动读写 Mural 内容并管理小组件
用 YAML 驱动生成、更新和管理 PowerPoint 幻灯片
从多视角审查代码变更,输出结构化问题与风险。
压缩提示词、文档与智能体技能内容,在保留结构下节省令牌成本。
帮助用户在回答前选择简短、标准或详细版本,控制回复深度与 token 用量。
基于本地文档学习你的个人文风,安全改写文本且数据不离开设备。
帮助规范 Claude Code 输出风格、压缩上下文并监控偏移与工具噪声。
压缩大模型输入输出内容,减少冗词与结构开销以节省令牌成本。
在结果送入大模型前压缩日志、文件与检索内容,显著降低 token 成本。