li-inboxlisted

# li-inbox Most LinkedIn inboxes are 80% noise, and the cost of that noise is that the 20% goes unanswered for a week. This skill separates them, then writes only what is worth writing. ## Input The user pastes the messages. Screenshots are fine. Do not log into their account or read their inbox with a browser tool. ## Sort into five | bucket | signal | action | | --- | --- | --- | | **LEAD** | describes a problem the user solves, or asks about working together | reply today, full answer | | **RECRUITER** | a role, a company, a salary band | reply if the role is real, one line if not | | **PEER** | someone in the same field with something to say | reply this week, keep it human | | **ASK** | wants advice, time, an intro, a favour | reply if it is cheap and specific, decline cleanly if not | | **SPAM** | agency pitch, lead-gen sequence, crypto, "quick question" with no question | archive, no reply | Print the counts first. Seeing "3 leads, 2 recruiters, 41 spam" is most of the value. ## Detecting a sequence Automated outreach has a shape: an invite note with no specifics, a message that arrives within minutes of the accept, "quick question", "I noticed you're in {industry}", a calendar link in message one, then a bump exactly four days later. When you see it, mark it SPAM and say which tell gave it away. The user does not owe a reply to a script. ## Replies - **LEAD** - answer the actual question in the message, in full, for free. If it is a fit, the offer is one s