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Structured LinkedIn people-search filters (Discovery v2, basket 1).

Every facet field carries LinkedIn IDs (not free text), resolved client-side via the typeahead endpoint (GET /api/v1/leads/discover/search-parameters), which proxies Unipile's /linkedin/search/parameters. Sending the wrong shape (free text where an ID is expected) is exactly what made classic search return nothing before, so the model only carries IDs and the adapter drops anything it can't map.

Form-supplied filters take priority over the ICP (the ICP only fills a facet the form left blank — see lead_finder._assemble_structured_filters).

This model is search-time facets only. Free-text "work keywords" + AND/OR and the company-size buckets are post-fetch SOFT signals and live as separate DiscoverRequest fields, not here (ТЗ v2 §B6/§B4).

network_distance is deliberately absent: discovery is pinned to 2nd + 3rd degree (1st-degree is excluded — those are usually already in conversation — while 3rd-degree strangers are the target of cold outreach). to_filter_dict injects [2, 3] unconditionally so the rule is enforced server-side regardless of the client. Safe even if LinkedIn rejects degree 3 on a free seat: classic search then degrades to keywords-only (see unipile.search_profiles). Confirm free-seat acceptance with backend/scripts/discovery_v2_spike.py (§E.2).

None = keep the campaign's value; a list (even empty) replaces it.

mode: titles (a role in a market), companies (those roles at the target_companies listed), lookalike (companies like seed_companies, then the roles at the companies found).

None = keep the campaign's value; a list (even empty) replaces it.

mode: titles (a role in a market), companies (those roles at the target_companies listed), lookalike (companies like seed_companies, then the roles at the companies found).