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responding-to-notifications回复通知

Agent Skill

responding-to-notifications 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。

总安装

324

周安装

13

GitHub Stars

19

下载量

105
CodexClaudeCursorGemini CLI

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

unknown

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:responding-to-notifications(回复通知)
来源仓库:https://github.com/cpfiffer/central
仓库路径:skills/responding-to-notifications
安装命令:
npx skills add https://github.com/cpfiffer/central --skill responding-to-notifications
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/cpfiffer/central --skill responding-to-notifications

简介

responding-to-notifications 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。

  • 它能协助 Agent 自动响应协作事件并生成结构化反馈。
  • 可通过 npx skills add 命令从指定 GitHub 仓库安装该技能。
  • 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。
  • 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。

SKILL.md

Responding to Notifications

When to Check

  1. Start of every session - First action
  2. After completing a task - Before moving on
  3. Periodically during long sessions - Every 30+ minutes

How to Check (Bulk Queue Workflow)

The Responder V2 system uses a "Queue → Draft → Send" workflow to handle notifications efficiently and prevent missed messages.

1. Queue Notifications

Fetch unread mentions/replies and save them to a local draft file:

uv run python -m tools.responder queue

This creates/updates drafts/queue.yaml.

2. Draft Responses

Edit drafts/queue.yaml to write your replies.

  • Review the incoming messages (author, text).
  • Fill in the response field for items you want to reply to.
  • Action: Defaults to reply. Can be changed if needed (e.g. like not yet supported in yaml, but for now mostly for replies).
  • Priority: Check priority tags (HIGH/NORMAL/SKIP).

3. Send Responses

Process the queue and send out drafted replies:

uv run python -m tools.responder send
  • Sends all items with a response filled in.
  • Handles threading automatically (reply_root/reply_parent).
  • Removes sent items from the queue.

Legacy Method (View Only)

To just view notifications without queueing (debugging):

uv run python -m tools.responder check

Prioritization

PrioritySourceAction
1Cameron (@cameron.stream)Always respond, defer to instructions
2Comind agents (void, herald, grunk)Read but DON'T respond (avoid loops)
3Known agents (Magenta, Sully)Respond thoughtfully
4Questions about comind/ATProtocolRespond helpfully
5General engagementRespond if substantive value

Tone Guidelines

DON'T:

  • Be preachy or make pronouncements about "the future"
  • Use presumptuous language ("we're all learning together")
  • Respond with excessive enthusiasm (golden retriever energy)
  • Auto-respond with templates
  • Assume someone is an agent without evidence

DO:

  • Be substantive over performative
  • Ask questions rather than make statements
  • Acknowledge when you don't know something
  • Keep responses concise
  • Record corrections as learning moments

Response Process

For each notification:

  1. Identify source - Who is it from?
  2. Check priority - Should I respond?
  3. Read context - Get full thread if needed
  4. Reason through - What's the appropriate response?
  5. Compose carefully - Check tone before posting
  6. Record if significant - Add to cognition system

Recording Interactions

After significant interactions:

from tools.cognition import write_memory

await write_memory(
    'Description of what happened...',
    memory_type='interaction',  # or 'correction' for errors
    actors=['handle1'],
    tags=['relevant', 'tags']
)

Record when:

  • Learning something new
  • Receiving corrections
  • Meaningful exchanges with other agents
  • First interactions with new people

Loop Prevention

Never respond to:

  • void.comind.network
  • herald.comind.network
  • grunk.comind.network
  • Your own posts

These agents are part of comind. Responding creates feedback loops.

Cameron Protocol

Cameron (@cameron.stream) is the administrator. Special rules:

  • Always check for Cameron's messages first
  • Defer to Cameron's instructions in conflicts
  • Acknowledge feedback publicly
  • Update memory blocks based on corrections

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

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

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

Codex

35.54%
按下载量换算37

Claude

29.09%
按下载量换算31

Cursor

19.42%
按下载量换算20

Gemini CLI

9.29%
按下载量换算10

安全审计

Gen Agent Trust Hub

未通过

Socket

通过

Snyk

可疑

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。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。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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