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Agent skill

Connections Optimizer

by affaan-m in affaan-m/ECC

Reorganize the user's X and LinkedIn network with review-first pruning, add/follow recommendations, and channel-specific warm outreach drafted in the user's real voice.

MITAuto-check passed

Install Connections Optimizer

skills CLI
$ npx skills add affaan-m/ECC --skill connections-optimizer -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install affaan-m/ECC connections-optimizer --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/affaan-m/ECC.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/connections-optimizer .claude/skills/connections-optimizer && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
connections-optimizer
GitHub stars
277k
Used in
2 other repos
Token cost
~1.4k tokens
SKILL.md length
630 words
Files
1
Skills in repo
683
Repo updated
First seen
Licence
MIT

At a glance

Reorganize the user's X and LinkedIn network with review-first pruning, add/follow recommendations, and channel-specific warm outreach drafted in the user's real voice.

  • Works in 8 steps: Capture priorities, do-not-touch… → Pull the current following / connection… → Score prune candidates with explicit… → …
  • The user wants to clean up following lists
  • SKILL.md covers When to Activate, Required Inputs, Tool Requirements and Safety Defaults, plus 7 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Connections Optimizer is an agent skill from affaan-m/ECC. Reorganize the user's X and LinkedIn network with review-first pruning, add/follow recommendations, and channel-specific warm outreach drafted in the user's real voice. Use when the user wants to clean up following lists, grow toward current priorities, or rebalance a social graph around higher-signal relationships.

Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It works with LinkedIn. The repository describes itself as: The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond. The licence is MIT.

When your agent uses it

  • The user wants to clean up following lists
  • Grow toward current priorities
  • Rebalance a social graph around higher-signal relationships

Example prompts

  • “/connections-optimizer”

Workflow steps

8 steps, taken from the first numbered list in SKILL.md.

  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
  7. Run brand-voice before drafting messages.
  8. Return a review pack before any apply step.

What it can do on your machine

Read from SKILL.md and the folder at commit 2d515e4. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Connections Optimizer loads about 1.4k tokens when it runs. Until then it costs about 85 tokens; SKILL.md has 630 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~85
When it runs · the whole SKILL.md, loaded when a task matches
~1.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from affaan-m/ECC at commit 2d515e4, republished under its MIT licence (© affaan-m). 630 words, ~1,370 tokens.

Download SKILL.mdSave it as .claude/skills/connections-optimizer/SKILL.md (or your agent's skills folder).
name
connections-optimizer
description
Reorganize the user's X and LinkedIn network with review-first pruning, add/follow recommendations, and channel-specific warm outreach drafted in the user's real voice. Use when the user wants to clean up following lists, grow toward current priorities, or rebalance a social graph around higher-signal relationships.
metadata.origin
ECC

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
Show full SKILL.md (257 more words)Show less
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
  7. Run brand-voice before drafting messages.
  8. Return a review pack before any apply step.

Review Pack Format

text
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.
  • 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

© affaan-m, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/connections-optimizer of affaan-m/ECC.

Open the folder on GitHubat commit 2d515e4

Used in 2 other repositories

We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in affaan-m/ECC, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Connections Optimizer next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Connections Optimizer compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Connections Optimizer this skillaffaan-m/ECC277k2 repos~1.4kAutomated safety check: PassMIT
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Banner Design Systemnextlevelbuilder/ui-ux-pro-max-skill135k1 repos~1.8kAutomated safety check: PassMIT
Agent ReachPanniantong/Agent-Reach95k—~1.4kAutomated safety check: PassMIT
Ad CreativeLeoYeAI/openclaw-marketing-skills1k8 repos~3.4kAutomated safety check: PassCustom licence
Social Contentfreekmurze/dotfiles1k23 repos~2.1kAutomated safety check: PassNone

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Works with

Questions about Connections Optimizer

What does Connections Optimizer do?

Reorganize the user's X and LinkedIn network with review-first pruning, add/follow recommendations, and channel-specific warm outreach drafted in the user's real voice. Connections Optimizer is an agent skill from affaan-m/ECC. Reorganize the user's X and LinkedIn network with review-first pruning, add/follow recommendations, and channel-specific warm outreach drafted in the user's real voice.

When should I use Connections Optimizer?

Connections Optimizer fits situations like: the user wants to clean up following lists; grow toward current priorities; rebalance a social graph around higher-signal relationships.

How do I install Connections Optimizer in Claude Code?

Run `npx skills add affaan-m/ECC --skill connections-optimizer -a claude-code`. Or copy the skill folder (skills/connections-optimizer in affaan-m/ECC) into .claude/skills/connections-optimizer in your project. Claude Code loads it when a task matches its description.

How do I install Connections Optimizer in Codex?

Run `npx skills add affaan-m/ECC --skill connections-optimizer -a codex`. Or copy the skill folder (skills/connections-optimizer in affaan-m/ECC) into .agents/skills/connections-optimizer in your project. Codex loads it when a task matches its description.

Can I use Connections Optimizer in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add affaan-m/ECC --skill connections-optimizer -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/connections-optimizer, .gemini/skills/connections-optimizer, .github/skills/connections-optimizer and .opencode/skills/connections-optimizer in your project.

What does Connections Optimizer need to run?

SKILL.md names no scripts, command-line tools or credentials: Connections Optimizer is instructions for the agent only.

Does Connections Optimizer access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Connections Optimizer safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Connections Optimizer use?

Connections Optimizer is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Connections Optimizer use?

About 1.4k tokens (SKILL.md is roughly 5.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Connections Optimizer?

Skills that share tags, products or a category with Connections Optimizer: Social (coreyhaines31/marketingskills, 54k stars), Banner Design System (nextlevelbuilder/ui-ux-pro-max-skill, 135k stars), Agent Reach (Panniantong/Agent-Reach, 95k stars) and Ad Creative (LeoYeAI/openclaw-marketing-skills, 1k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Connections Optimizer?

affaan-m (a GitHub user) maintains it in affaan-m/ECC, which has 276,673 GitHub stars. The repository holds 683 skills in this directory. The repository was last updated on October 11, 2026.

Source: affaan-m/ECC on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.