connections-optimizer
by affaan-mconnections-optimizer is a workflow skill for reviewing and reshaping X and LinkedIn networks with prune queues, follow recommendations, warm-path ranking, and channel-specific outreach. Install it when you need review-first network cleanup, reconnection planning, or connections-optimizer for Lead Research.
This skill scores 74/100, which means it is listable and likely useful for agents, but directory users should expect a document-driven workflow rather than a strongly tooled or fully reproducible implementation. The repository gives clear activation cues, required inputs, and channel-specific outcomes for X and LinkedIn network cleanup plus warm outreach drafting, so an agent can usually trigger it with less guesswork than a generic prompt.
- Strong triggerability: the skill explicitly names when to activate it and includes example user intents like pruning follows, rebalancing networks, and reconnecting.
- Good operational framing: it defines required inputs, default mode behavior, supported platforms, and review-first pruning/add-follow recommendations.
- Useful agent leverage: it goes beyond generic outreach by combining network analysis, warm-path identification, and channel-specific draft generation in the user's voice.
- Execution depends on external tools named as preferred requirements, but the repo provides no bundled scripts, references, or installation guidance for those dependencies.
- Practical adoption detail is limited: despite a long SKILL.md, there are no support files, repo references, or concrete quick-start examples showing end-to-end use.
Overview of connections-optimizer skill
connections-optimizer is a workflow skill for cleaning up and reshaping professional social graphs on X and LinkedIn. It is best for users who want more than a generic “who should I follow” list: they need review-first pruning, better follow decisions, and warm outreach that matches real priorities. If you are optimizing a network around a new role, a campaign, a niche, or a relationship strategy, this skill helps turn scattered contacts into a higher-signal system.
What this skill does best
The connections-optimizer skill focuses on three jobs: decide who to keep, identify who to add or reconnect with, and draft outreach that fits the channel. It is especially useful when network quality matters more than raw volume, such as lead research, ecosystem building, or founder-style relationship management.
Who should install it
Install connections-optimizer if you already have a live network and want to improve it, not just build one from scratch. It fits operators, founders, recruiters, sales people, and researchers who use X or LinkedIn to stay close to a target market. It is less useful if you only need a one-off prospect list with no pruning or relationship context.
Key decision factors
The biggest differentiator is the review-first approach: it prioritizes thoughtful pruning and ranking before outreach. The skill also supports channel-specific output, so X DM and LinkedIn drafts can differ instead of forcing one tone across both. For users evaluating connections-optimizer for Lead Research, that matters because the best next action is often a warm path, not a cold scrape.
How to Use connections-optimizer skill
Install and entry point
Use the skill in the repo path skills/connections-optimizer. A typical install command is:
npx skills add affaan-m/everything-claude-code --skill connections-optimizer
After install, open SKILL.md first, then check any linked support docs if they exist in your local copy. In this repo, there are no extra scripts or reference folders, so the main behavior comes from the skill file itself.
What to provide up front
The quality of connections-optimizer usage depends on a few concrete inputs: current priorities, target roles or industries, target geography or ecosystem, platform choice, a do-not-touch list, and the mode (light-pass, default, or aggressive). If you skip mode, default is the safest starting point. For Lead Research, be explicit about the ideal customer profile or relationship goal so the skill ranks connections against a real target.
How to prompt it well
Turn a vague ask into an actionable brief. Good: “Use connections-optimizer to review my LinkedIn network for current product leaders in fintech, keep investors and hiring contacts, avoid pruning people from my last two clients, and draft warm reconnect messages for the top 15 matches.” Weak: “Optimize my network.” The first prompt gives the skill enough structure to make pruning, ranking, and messaging decisions that feel deliberate.
Best workflow for output quality
Start with one platform, one objective, and one mode. Review the prune queue before asking for outreach so you do not draft messages for accounts you would remove anyway. If the first pass is too aggressive or too conservative, adjust the mode and your do-not-touch list rather than rewriting the whole brief. When using connections-optimizer for Lead Research, add a short note on what counts as a warm path, such as mutual employers, shared communities, or adjacent buyers.
connections-optimizer skill FAQ
Is connections-optimizer only for pruning?
No. pruning is part of it, but the skill also supports follow recommendations, reconnection ideas, and warm outreach drafting. If your real problem is network quality rather than list hygiene, this is a stronger fit than a plain prompt.
Does it work better for X or LinkedIn?
It is designed for both, but the best platform depends on your goal. X is usually better for visibility, signal scanning, and fast relationship mapping; LinkedIn is better for professional connection review and outreach context. Use one or both, but name the platform so the skill does not guess.
Is it beginner-friendly?
Yes, if you can describe your goal clearly. You do not need a complex workflow, but you do need basic constraints: what to keep, what to protect, and what success looks like. Beginners get the best results by starting with default mode and a small review set.
When should I not use it?
Do not use connections-optimizer if you only need a static lead list, if you have no access to the actual network data, or if your goal is purely cold outbound copy. It is also a poor fit when you have no pruning tolerance, no target segment, or no willingness to review recommendations before acting.
How to Improve connections-optimizer skill
Give it sharper decision rules
The skill improves when you define what “high signal” means in your context. For example, say “keep anyone from current customers, active collaborators, and target investors; prune inactive peers outside fintech; prioritize people who post about AI ops, not generic productivity.” This is better than asking for “better connections” because it gives the model a stable ranking frame.
Share constraints before the first pass
The most common failure mode is over-pruning or recommending the wrong kind of relationship. Prevent that by adding a do-not-touch list, excluded industries, and any reputation-sensitive contacts. If you are using connections-optimizer for Lead Research, include the buyer persona and the relationship type you want the skill to preserve or create.
Iterate on the output, not the whole task
After the first pass, improve results by narrowing the next pass: ask for a smaller prune queue, more conservative outreach, or stricter warm-path criteria. If the draft voice feels off, provide a sample message that sounds right and ask for channel-specific rewrites. The more you iterate on one failure at a time, the more useful the connections-optimizer skill becomes.