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Agent Skill · 开发

groove-work-compound(凹槽工作化合物)

groove-work-compound 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。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。

groove-work-compound 是开发类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为只读;许可证信息还不明确,第三方扫描已通过,按安装量在开发类的 21,746 个 Skill 里排第 6,340。

总安装 4,823周安装 203GitHub Stars 4下载 1,689核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

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:groove-work-compound(凹槽工作化合物)
来源仓库:https://github.com/andreadellacorte/groove
仓库路径:skills/groove-work-compound
安装命令:
npx skills add https://github.com/andreadellacorte/groove --skill groove-work-compound
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 npx skills 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。

skills.shnpx skills
npx skills add https://github.com/andreadellacorte/groove --skill groove-work-compound

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

groove-work-compound 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息。适合在 Codex、Claude、Cursor、Gemini CLI 中围绕仓库状态、代码变更或协作事项进行整理。通过 npx skills add 命令从指定 GitHub 仓库安装并使用。

安装前需确认权限范围和维护状态,注意可能触发联网或文件读写操作。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

来源仓库内路径:skills/groove-work-compound

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/andreadellacorte/groove --skill groove-work-co…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

groove-work-compound 怎么安装?

在终端执行 npx skills add https://github.com/andreadellacorte/groove --skill groove-work-compound。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

groove-work-compound 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

groove-work-compound 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

groove-work-compound 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

groove-work-compound 用的人多吗?

公开数据是累计安装 4,823 次,近一周安装 203 次,下载 1,689 次,GitHub 4 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

groove-work-compound 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。
  • 标注为只读权限,试用阶段不容易误改本地文件。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理开发类任务、又不想每次都手写提示词的人。
  • 只想先试试效果、不希望它改动本地文件的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
groove-work-compound

凹槽工作化合物 · 本页

4,8234只读未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

groove-work-compound

Scope

"This conversation" means the full chat thread (all messages in the same chat where the user invoked compound). Lessons and compound actions come from work done or decided anywhere in that thread.

In scope:

  • Work done earlier in the same chat: other skill runs (e.g. /ppp-weekly-report, /groove-work-plan), file or bean edits, decisions, review or planning discussion.
  • Any bean or work item the user or the thread refers to as part of the workflow (e.g. the epic or task this compound stage belongs to). Use those to ground lessons and actions.

Not in scope unless the user asks: Daily memory, weekly summaries, or other docs (e.g. "compound on the whole day").

If no other work is visible in the context when compound runs (e.g. the turn only shows the compound request): ask which session or work to compound on (e.g. "I only see the compound request. Which session should I compound on — e.g. the PPP run above, or something else?") instead of concluding "no work discussed."

Outcome

Lessons, root causes, and fixes are documented. Relevant project files are updated (rules, templates, docs, task bodies). A checklist of compound actions with done/pending status is produced.

Acceptance Criteria

  • Lessons are documented with root cause analysis (not just what went wrong, but why)
  • Relevant project files are updated: rules files, templates, docs, task bodies
  • Checklist is produced with each action marked done or pending
  • If user frustration patterns were detected, they are specifically captured
  • "No new lessons" is an explicit acceptable outcome — capture it rather than skipping

Constraints

  • Read tasks.backend from .groove/index.md; memory path is always .groove/memory/
  • Before producing the compound actions checklist, check for open mistake incidents via /groove-utilities-memory-mistakes --list:

- If open incidents exist: process each using the log → fix → audit → resolve cycle from /groove-utilities-memory-mistakes before moving on - Add to compound checklist: "mistakes: N incident(s) resolved → learned/" (done/pending) - If no open incidents: skip silently

  • Output goes into existing project files — do not create new files unless necessary
  • Always run even if it seems like "nothing to capture" — capture that explicitly
  • Compound actions checklist must include why each action matters, not just what it is
  • If user showed repeated fixes, confusion, or rework: capture the pattern and its trigger
  • Create stage task in backend if tasks.backend!= none via /groove-utilities-task-create with a descriptive title so multiple compounds per day are distinct: YYYY-MM-DD, Compound — <brief topic> (topic from the work just closed, e.g. release, feature, or session summary). Do not number stages in task titles.
  • After producing the compound actions checklist, identify any lesson that is about AI workflow, agent behaviour, tool usage, or engineering process — not specific to the codebase or product
  • If any such lesson is found:

- Propose: "Workflow learning detected — add to.groove/memory/learned/.md?" - Suggest a topic name based on the content (e.g. patterns, tools, anti-patterns, hooks) - Wait for user to confirm, pick a different topic, or skip - If confirmed: append the lesson as a bullet under a ## <YYYY-MM-DD> heading in the file; create the file with a # <Topic> heading if it does not exist; create the dated heading if absent - Add to compound checklist: "workflow learning →.groove/memory/learned/.md" (done/pending)

  • If no workflow lessons, skip this step entirely — no prompt, no noise
  • If a workflow learning was captured locally AND groovebook: is set in .groove/index.md: add a one-line suggestion after the checklist: "Learning captured → .groove/memory/learned/<topic>.md. Publish to groovebook? Run /groove-groovebook-publish." If groovebook: is absent: skip silently.
  • After a workflow learning is captured, offer graduation: "Is this lesson stable enough to apply to every future session? Run /groove-utilities-memory-graduate <topic> to promote it to AGENTS.md permanently." — only suggest if the lesson was just confirmed, not every compound run.
  • After the workflow learning step, scan the conversation for deferred items — phrases like "we'll come back to", "do this later", "next time", "TODO", "skip for now", "won't fix today". If any are found: list them and ask "Capture any of these as promises? (numbers, or enter to skip)" — for each confirmed item, run /groove-utilities-memory-promises <text>. If none found: skip silently.
  • After the workflow learning step, prompt for an optional session rating:

- Ask: "Rate this session (1–5): how well did the compound loop serve you? (enter to skip)" - If the user provides a rating: append to .groove/memory/learned/signals.md under a table; create the file with a header and table header row if it does not exist - Format: | YYYY-MM-DD | <rating>/5 | <one-line context from the session topic> | - If the user skips: do not mention it again

平台分布

Codex

36.23%
按下载量换算612

Claude

28%
按下载量换算473

Cursor

19.1%
按下载量换算323

Gemini CLI

8.18%
按下载量换算138

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

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。目前只有一个公开来源,建议同时核对源仓库。

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