warm-intro-finderlisted

# Warm-intro and referral path finder Cold is not the only way in. Given a target account, find the warm path hiding in the network. Given the whole network, find which accounts are already reachable. ## Before anything else Ask for the LinkedIn export if it is not already provided: Settings → Data privacy → Get a copy of your data → Connections. The file arrives as `Connections.csv` with a 3-line privacy notice above the real header. `scripts/match.py` handles that automatically. ## Workflow ### 1. Profile the network first, always ```bash python3 scripts/match.py <path-to-Connections.csv> --profile ``` Read the output before doing anything else, and tell the user what it means for them. Two numbers decide how much the rest is worth: - **`with_email`**: usually near zero. LinkedIn only exports an email when that person opted in. If it is low, say so, because it removes the strongest available relationship signal. - **`connections_by_year`**: if the last 12 months dominate the file, most of the network is inbound from content, not relationships. Warn the user plainly rather than scoring inbound follows as warm ties. `likely_own_employers` is inferred from dense, long-lived clusters. Read it back to the user for confirmation, since it is a guess and it drives exclusions in reverse mode. ### 2. Run the mode that matches the question **Target mode** when they named an account: ```bash python3 scripts/match.py <csv> --target "Acme" ``` **Reverse mode** when t