首页/销售与商务/connections-optimizer
C

connections-optimizer

by @affaan-mv
4.1(12)

优化X和LinkedIn社交网络,清理无效连接、识别高价值路径并批量管理关注和互动策略

salescrmsocial-medianetworkingGitHub
安装方式
npx skills add affaan-m/everything-claude-code --skill connections-optimizer
compare_arrows

Before / After 效果对比

1
使用前

手动浏览关注列表判断账号质量,逐个取消无效关注和添加新连接,难以识别网络中的高价值节点,网络优化需要数周持续操作

使用后

自动分析账号活跃度和互动价值,批量清理僵尸关注并推荐高价值连接,识别网络中的关键传播节点,1次操作完成网络优化

description SKILL.md

connections-optimizer

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

  • Capture priorities, do-not-touch constraints, and selected platforms.

  • Pull the current following / connection inventory.

  • Score prune candidates with explicit reasons.

  • Score keep candidates with explicit reasons.

  • Use lead-intelligence plus research surfaces to rank expansion candidates.

  • 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

  • Run brand-voice before drafting messages.

  • 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

Weekly Installs520Repositoryaffaan-m/everyt…ude-codeGitHub Stars152.8KFirst Seen11 days agoSecurity AuditsGen Agent Trust HubPassSocketPassSnykWarnInstalled oncodex483opencode460gemini-cli455cursor455antigravity455kimi-cli454

forum用户评价 (0)

发表评价

效果
易用性
文档
兼容性

暂无评价

统计数据

安装量289
评分4.1 / 5.0
版本
更新日期2026年4月27日
对比案例1 组

用户评分

4.1(12)
5
42%
4
33%
3
17%
2
8%
1
0%

为此 Skill 评分

0.0

兼容平台

🔧Claude Code

时间线

创建2026年4月14日
最后更新2026年4月27日
🎁 Agent 知识卡片