deepline-analytics

# Deepline Analytics ## 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. Use this skill to answer customer analytics questions through Deepline's warehouse and semantic-layer tools. The goal is not just to run SQL; it is to preserve the customer's business definitions by starting from the semantic layer, validating the query path, and reporting exactly what metric definitions and filters were used. ## Before You Start Use `deepline-gtm` instead when the task is prospecting, enrichment, contact finding, outbound sequencing, personalization, or row-by-row lead/account research. Analytics questions ask about existing customer data: revenue, pipeline, funnel, conversion, retention, usage, calls, accounts, opportunities, or warehouse tables. If Snowflake credentials or a semantic layer are missing, stop and report the setup b...