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Query the user's HubSpot contacts — the people synced from the HubSpot portals they've connected. Use this for any question about their CRM contacts: engagement filters ('show me people with more than 10 page views'), lifecycle and pipeline ('how many customers do I have?', 'leads with an open deal'), firmographics ('contacts at Google', 'people in Boston'), attribution ('which source brought the most contacts?'), email activity, deal amounts, lead scores, or form conversions. Answered by generating a read-only SQL query over the synced contact table, so it returns columns and rows rather than prose — summarize the rows for the user, and say how many there were. If it reports no contacts synced, tell them to import at /hubspot/import. Keep the question under 500 characters.

Query the user's HubSpot companies — the companies synced from the HubSpot portals they've connected. Use this for any question about their CRM companies: firmographics ('software companies with more than 100 employees'), lifecycle and pipeline ('companies with an open deal', 'how many customer accounts?'), location ('companies in Boston'), funding and size ('which companies raised money?', 'biggest companies by revenue'), or attribution. Answered by generating a read-only SQL query over the synced company table, so it returns columns and rows rather than prose — summarize the rows for the user, and say how many there were. If it reports no companies synced, tell them to run a company sync for their portal. Keep the question under 500 characters.

Ask a free-form question about the user's LinkedIn connections that the other tools can't express: aggregates and rankings ('which companies do I know the most people at?'), date ranges ('who did I connect with in 2023?'), location filters ('my connections in Boston'), or several conditions at once ('founders in New York I connected with this year'). Answered by generating a read-only SQL query, so it returns columns and rows rather than prose. Prefer search_connections for a simple name/company/title lookup — it is faster. Keep the question under 500 characters.

107 questions this archive can answer, each with the SQL that answers it. Every one is executed against the database on every build, so none of them is a claim. Start from the nearest one and edit it rather than writing a query from scratch.

Any question the other tools do not cover, as one read-only SQL statement over the archive database. SELECT or WITH only; a LIMIT is imposed if you omit one. Call `read_first` before computing anything and `list_datasets` to find table names. A query estimated to read more than 250,000 rows is refused — narrow it with a WHERE, or ask for one table at a time.

Run a database query on one of your servers — passwordless. It executes the engine's own client on the host over Termalin's keyless tunnel, using the database's local trust (Postgres peer auth via `sudo -u postgres`, MySQL/MariaDB unix-socket via `sudo mysql`, redis-cli, mongosh, sqlite3) — so no database password is needed or stored anywhere. Read-only by default: only SELECT/SHOW-style statements run unless allowWrites is set (full-access keys only). SQL engines return CSV/TSV with a header. For MongoDB pass a shell expression, e.g. db.products.find({}).limit(20).toArray().