← DevelopersThe ilml LinkedIn plugin

Your LinkedIn —
mirrored, and yours.

Not just auto-apply. ilml-plugin-linkedin keeps a local copy of your LinkedIn — inbox, contacts and jobs — on your machine, and runs AI-assisted workflows from the terminal: reply, classify, connect, and apply.

Not a bot that clicks blindly

A copy of your LinkedIn, on your machine.

sync pulls your inbox and contacts into a local database you own. Analysis after that — planning your day, drafting replies, classifying people, choosing who to reach — runs against your own copy, no browser needed. And when something does touch LinkedIn itself — a sync, an apply, a connect — the plugin drives the browser for you; you never sit in the tab.

What it does

One plugin, the whole workflow.

A local copy you own

sync pulls your LinkedIn inbox and contacts into a local database on your machine. Analysis runs offline against your own history — your data stays yours.

A daily plan — no browser

today reads the synced data and tells you who to reply to and what to do next, prioritized. report prints inbox stats. No LinkedIn tab open.

Reply with your AI

Your assistant hands over a JSON of drafts (messages --draft-batch); you approve them (--review-drafts); it sends (--push-drafts). enrich classifies every thread — recruiter, HM, founder, coach…

Find & reach the right people

warm-scan finds your 1st-degree connections at target companies; funnel builds a quota-tracked connection-request queue for recruiters / founders / investors.

Show up & get seen

visit walks a queue of profiles so you appear in their “who viewed your profile”; viewers pulls that list back so you can act on it.

Jobs — scored, then applied

scout scores jobs from your search URLs; apply and apply-queue auto-apply to the Easy Apply roles at the top — filling each form with Lifebot AI.

Your own profile, audited

enrich-profile <you> --full pulls your full Experience, Skills, Recommendations and Certifications; profile-history tracks how a contact’s profile changed over time.

It lands in your graph

Applications, session reports and post snapshots flow into iLiveMyLife nodes — read-post --save-to-graph captures a post into your graph, ready to automate on.

In your terminal

Every command, real.

The plugin installs into your ilml CLI and runs as ilml linkedin <command>. Run ilml linkedin help any time for the full list.

ilml linkedin — command reference
# Set up & update
$ ilml plugin install linkedin# add the plugin from npm
$ ilml linkedin login# open a browser, log in once, save cookies
$ ilml plugin config linkedin# your name, search URLs & graph nodes
$ ilml plugin update linkedin# update to the latest version
# Every day
$ ilml linkedin sync# pull new threads (--full · --dry-run)
$ ilml linkedin today# prioritized action plan — no browser
$ ilml linkedin report# inbox stats & last-session summary
# Reply with your AI
$ ilml linkedin messages --draft-batch @replies.json# AI hands over a JSON of drafts
$ ilml linkedin messages --review-drafts# approve / edit / reject them
$ ilml linkedin messages --push-drafts# send — with a pre-send freshness re-check
$ ilml linkedin enrich# re-classify every contact (offline)
# People & outreach
$ ilml linkedin warm-scan --companies "…"# 1st-degree connections at target companies
$ ilml linkedin funnel# connection-request queue (quota-tracked)
$ ilml linkedin visit# appear in their “who viewed your profile”
$ ilml linkedin viewers# pull who viewed you
# Profiles & posts
$ ilml linkedin enrich-profile <you> --full# deep-audit your own profile
$ ilml linkedin profile-history# how a contact’s profile changed over time
$ ilml linkedin read-post <url> --save-to-graph <node># AI reads a post → into your graph
# Jobs & the full run
$ ilml linkedin scout# score jobs from your search URLs
$ ilml linkedin apply# auto-apply to Easy Apply roles
$ ilml linkedin apply-queue# apply to the top-scored queue
$ ilml linkedin daily# the whole pipeline, one command
Safe

Built to respect LinkedIn. Every command has a cap and a stated ban-risk; connection requests are weekly-quota-tracked; replies pass a salutation guard and a pre-send freshness re-check. And the offline commands — today, enrich, warm-scan, report — never open a browser at all.

Driven by your AI

Your assistant does the writing.

The messages flow is built for AI: your assistant drafts the replies, you review them, the plugin sends them. Because the plugin runs on the same ilml CLI, your AI can reach it — and your graph — over MCP.

Pro

Give it its own account. Automations are cleaner on a dedicated login. Run ilml login --local inside the plugin’s folder to sign that project into a separate account — your personal graph stays untouched while the bot works. One CLI, many accounts. More on accounts →

Get started

Three commands to first sync.

Node 18+. You’ll need the ilml CLI (a one-line install) and a LinkedIn account.

install, log in, first sync
npm install -g @ilivemylife/graph-sdk   # the ilml CLI
ilml plugin install linkedin             # add the plugin
ilml linkedin login                      # log in once, cookies saved
ilml linkedin sync                       # pull your inbox locally
ilml linkedin today                      # your action plan for today

Own your network.

A local mirror, your AI, and one CLI — LinkedIn on your terms.

Get the plugin →