<summary>Query your canonical companies (`company_profiles`) — one deduped row per real-world company
in your account. Rows accrue from your contacts' employers, company searches, and domain
lookups, so a company may have no linked people yet. Use this to look a company up ("find the
company row for stripe.com"), list the companies you're tracking, or answer any question about
the company entity itself. This is the canonical company entity, NOT the LinkedIn post-monitoring
list — for companies whose posts an agent watches, use query_monitored_companies.
Columns: id, display_name, domain (normalized bare host), linkedin_company_id, owner_email,
data (JSONB), created_at, updated_at. Sliq's CRM is deals and tasks: to see whether a company
has a deal or a task, use query_deals (status='all') / query_crm_tasks with company_id.
JSONB queries: `data->>'some_key' ILIKE '%...%'`.
Firmographic columns (captured from company enrichment; blank/NULL until enriched): linkedin_url
(bare slug), industry, description, location (HQ), logo_url, employee_count, follower_count,
founded_year, company_type, annual_revenue, total_funding, latest_funding_stage.
To list the people you know at a company, take an `id` from here and call query_people with
`where_clause="company_profile_id = <id>"`.
For how many companies are in each industry or location, or which companies are in one of
those groups, call list_companies: it reads the Companies table the way the user sees it, over
every company without paging for the counts.</summary>
<returns>
<description>A dict with count, truncated, and items array (each row {id, display_name, domain,
linkedin_company_id, owner_email, linkedin_url, industry, description, location,
logo_url, employee_count, follower_count, founded_year, company_type, annual_revenue,
total_funding, latest_funding_stage, data, created_at, updated_at}).</description>
</returns>