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Agent Skill · 研究检索

connections-optimizer(连接优化器)

connections-optimizer 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。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。

connections-optimizer 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为操作浏览器;许可证信息还不明确,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 4,247。

总安装 34,272周安装 1,423GitHub Stars 170,278下载 11,088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:connections-optimizer(连接优化器)
来源仓库:https://github.com/affaan-m/everything-claude-code
仓库路径:skills/connections-optimizer
安装命令:
npx skills add https://github.com/affaan-m/everything-claude-code --skill connections-optimizer
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/affaan-m/everything-claude-code --skill connections-optimizer

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于优化社交网络关系,包括清理关注列表、分析推荐连接与生成沟通草稿。支持 X(原 Twitter)、LinkedIn、Apple Mail 等平台的消息模板生成。适用于希望重构人脉网络或提升冷启动效率的用户。需明确操作边界,避免对非活跃联系人造成骚扰。

connections-optimizer 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/connections-optimizer

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/affaan-m/everything-claude-code --skill connec…;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

    它需要操作浏览器,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

connections-optimizer 怎么安装?

在终端执行 npx skills add https://github.com/affaan-m/everything-claude-code --skill connections-opti…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

connections-optimizer 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。

connections-optimizer 需要什么权限?

权限级别是操作浏览器。该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

connections-optimizer 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。

connections-optimizer 用的人多吗?

公开数据是累计安装 34,272 次,近一周安装 1,423 次,下载 11,088 次,GitHub 170,278 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。

connections-optimizer 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

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。
  • 来源仓库有 170,278 星,维护活跃度相对可查。

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。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 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。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

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。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
connections-optimizer

连接优化器 · 本页

34,272170,278操作浏览器未明确有提醒

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

Connections Optimizer

Reorganize the user's network instead of treating outbound as a one-way prospecting list.

This skill handles:

  • X following cleanup and expansion
  • LinkedIn follow and connection analysis
  • review-first prune queues
  • add and follow recommendations
  • warm-path identification
  • Apple Mail, X DM, and LinkedIn draft generation in the user's real voice

When to Activate

  • the user wants to prune their X following
  • the user wants to rebalance who they follow or stay connected to
  • the user says "clean up my network", "who should I unfollow", "who should I follow", "who should I reconnect with"
  • outreach quality depends on network structure, not just cold list generation

Required Inputs

Collect or infer:

  • current priorities and active work
  • target roles, industries, geos, or ecosystems
  • platform selection: X, LinkedIn, or both
  • do-not-touch list
  • mode: light-pass, default, or aggressive

If the user does not specify a mode, use default.

Tool Requirements

Preferred

  • x-api for X graph inspection and recent activity
  • lead-intelligence for target discovery and warm-path ranking
  • social-graph-ranker when the user wants bridge value scored independently of the broader lead workflow
  • Exa / deep research for person and company enrichment
  • brand-voice before drafting outbound

Fallbacks

  • browser control for LinkedIn analysis and drafting
  • browser control for X if API coverage is constrained
  • Apple Mail or Mail.app drafting via desktop automation when email is the right channel

Safety Defaults

  • default is review-first, never blind auto-pruning
  • X: prune only accounts the user follows, never followers
  • LinkedIn: treat 1st-degree connection removal as manual-review-first
  • do not auto-send DMs, invites, or emails
  • emit a ranked action plan and drafts before any apply step

Platform Rules

X

  • mutuals are stickier than one-way follows
  • non-follow-backs can be pruned more aggressively
  • heavily inactive or disappeared accounts should surface quickly
  • engagement, signal quality, and bridge value matter more than raw follower count

LinkedIn

  • API-first if the user actually has LinkedIn API access
  • browser workflow must work when API access is missing
  • distinguish outbound follows from accepted 1st-degree connections
  • outbound follows can be pruned more freely
  • accepted 1st-degree connections should default to review, not auto-remove

Modes

light-pass

  • prune only high-confidence low-value one-way follows
  • surface the rest for review
  • generate a small add/follow list

default

  • balanced prune queue
  • balanced keep list
  • ranked add/follow queue
  • draft warm intros or direct outreach where useful

aggressive

  • larger prune queue
  • lower tolerance for stale non-follow-backs
  • still review-gated before apply

Scoring Model

Use these positive signals:

  • reciprocity
  • recent activity
  • alignment to current priorities
  • network bridge value
  • role relevance
  • real engagement history
  • recent presence and responsiveness

Use these negative signals:

  • disappeared or abandoned account
  • stale one-way follow
  • off-priority topic cluster
  • low-value noise
  • repeated non-response
  • no follow-back when many better replacements exist

Mutuals and real warm-path bridges should be penalized less aggressively than one-way follows.

Workflow

  1. Capture priorities, do-not-touch constraints, and selected platforms.
  2. Pull the current following / connection inventory.
  3. Score prune candidates with explicit reasons.
  4. Score keep candidates with explicit reasons.
  5. Use lead-intelligence plus research surfaces to rank expansion candidates.
  6. Match the right channel:

- X DM for warm, fast social touch points - LinkedIn message for professional graph adjacency - Apple Mail draft for higher-context intros or outreach

  1. Run brand-voice before drafting messages.
  2. Return a review pack before any apply step.

Review Pack Format

CONNECTIONS OPTIMIZER REPORT
============================

Mode:
Platforms:
Priority Set:

Prune Queue
- handle / profile
  reason:
  confidence:
  action:

Review Queue
- handle / profile
  reason:
  risk:

Keep / Protect
- handle / profile
  bridge value:

Add / Follow Targets
- person
  why now:
  warm path:
  preferred channel:

Drafts
- X DM:
- LinkedIn:
- Apple Mail:

Outbound Rules

  • Default email path is Apple Mail / Mail.app draft creation.
  • Do not send automatically.
  • Choose the channel based on warmth, relevance, and context depth.
  • Do not force a DM when an email or no outreach is the right move.
  • Drafts should sound like the user, not like automated sales copy.

Related Skills

  • brand-voice for the reusable voice profile
  • social-graph-ranker for the standalone bridge-scoring and warm-path math
  • lead-intelligence for weighted target and warm-path discovery
  • x-api for X graph access, drafting, and optional apply flows
  • content-engine when the user also wants public launch content around network moves

平台分布

Codex

35.84%
按下载量换算3,974

Claude

29.9%
按下载量换算3,315

Cursor

18.36%
按下载量换算2,036

Gemini CLI

10.42%
按下载量换算1,155

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

操作浏览器

该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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