niche-signal-discovery

# Niche Signal Discovery ## Quick Start ```bash npm install -g deepline # Fallback for secure sandboxes: mkdir -p "$HOME/.local" && npm config set prefix "$HOME/.local" && export PATH="$HOME/.local/bin:$PATH" && npm install -g deepline --registry https://code.deepline.com/api/v2/npm/ deepline auth register --wait auto deepline auth wait --timeout 120 # completes Cowork/browser approval; no-op if already connected deepline auth status deepline -h ``` ## CLI resolution Run `deepline` when it is available. If the shell reports that command is missing, use `<workspace-root>/.deepline/runtime/bin/deepline` (or the npm-created `.cmd` shim on Windows). If neither exists, follow `https://code.deepline.com/SKILL.md` to set up Deepline. Discover differential signals between Closed Won and Closed Lost accounts by extracting multi-page website content and job listings, then computing Laplace-smoothed lift scores to identify what distinguishes buyers from non-buyers. ## Prerequisites - **Deepline CLI** — All enrichment runs through `deepline enrich`; route through prebuilt plays and customer-configured provider connections rather than hardcoding provider-specific prospecting tools. - **Python 3** stdlib only — no pip dependencies for any shipped script. - **Credits** - paid web extraction plus CrustData job search. Run a small sample or `deepline tools describe crustdata_v2_job_search --json` for current Deepline-facing pricing before scaling. Step 7 contact discovery is additional...