Carry the typed_columns opt-in flag through the SDK and CLI

.github/workflows/contract.yml

@@ -18,14 +18,16 @@ jobs:
                   python-version: '3.14'
             - run: uv sync --all-packages
             # SDK features land on development before the platform deploys to
-            # prod, so PRs targeting development check against the dev spec.
+            # prod, so every PR but a release into main checks against the dev
+            # spec — including one stacked on another feature branch, which is
+            # just as far ahead of prod as the branch it targets.
             # DEV_SPEC_URL is a repo secret; fork PRs don't receive it and
             # fall back to the prod spec, keeping dev infra internal-only.
             - env:
                   BASE_REF: ${{ github.base_ref }}
                   DEV_SPEC_URL: ${{ secrets.DEV_SPEC_URL }}
               run: |
-                  if [ "$BASE_REF" = "development" ] && [ -n "$DEV_SPEC_URL" ]; then
+                  if [ "$BASE_REF" != "main" ] && [ -n "$DEV_SPEC_URL" ]; then
                       uv run python scripts/check_contract.py --spec-url "$DEV_SPEC_URL"
                       uv run python scripts/gen_requests.py --check --spec-url "$DEV_SPEC_URL"
                   else

CHANGELOG.md

@@ -6,6 +6,7 @@
 - SDK: `Job` / `AsyncJob` returned by `validate_icp`, `discogen.process` and `discogen.process_personas` carry `column_name` from the submit response. The engine picks the columns — an LLM validation returns `Fit` / `Confidence` / `Reasoning`, the native model `ICP Fit` (`Yes` / `No` at a 0.50 threshold on the score) / `ICP Score` (the calibrated probability, 0.00-1.00 as a string) / `Reasoning (always null)` — so read it rather than hardcoding either set. It is `None` on a job reattached with `discogen.job(task_id)`.
 - CLI: `validate-icp --integration-id native-icp` and `discogen run --integration-id native-icp` select the native ICP-fit model; `discolike validate-icp --help` documents both column sets.
 - **Breaking:** the ICP-fit verdict is title case on every surface. An LLM `validate_icp` run's `Fit` column now returns `Yes` / `No` instead of `yes` / `no`, matching the native engine's `ICP Fit` column, DiscoGen and the app. Code that matches the verdict on the exact string `"yes"` has to be updated; compare case-insensitively to survive either.
+- SDK/CLI: `discogen.process` and `discogen.process_personas` take `typed_columns`, and the CLI gains `--typed-columns`. It opts the query into the detector answering yes/no, fixed-set and scale columns with a TypeSafe judgment model instead of generated prose; which columns are typed and how is decided server-side from the query text, not passed in by the caller. Off by default. See `include_confidence` below for the sibling flag that adds a confidence column to each typed column.
 - SDK/CLI: `discogen.process` and `discogen.process_personas` take `include_confidence`, and the CLI gains `--include-confidence`. It applies to typed columns, which a DiscoGen run answers with a TypeSafe judgment model rather than generated prose; with it on, each typed column gets a sibling confidence column. Off by default, and it changes display only - the answers and their probabilities come back either way.
 - SDK: `contacts.generate` can run without an LLM key. Pass `integration_id=NATIVE_ENGINE` (exported from `discolike`) for DiscoLike Groove, DiscoLike's native extractor, or omit `integration_id` to get your default LLM integration and native when you have none. The native engine returns every person the search surfaces with a title and does not validate titles against `icp_text`; a search provider is still required. `JobStatus` gains `title_validation` (`"llm"` or `"none"`, `None` on non-ContaGen jobs) so you can tell which engine ran.
 - SDK: discover and count take `sub_industry` / `negate_sub_industry` (217 second-level labels scoped to their parent industry category; a bare label like `ROOFING` adds `CONSTRUCTION` to `category` server-side) and a multi-shape geo filter: `geo` (`lat,lon` or `lat,lon,radius`), `bbox` (`min_lat,min_lon,max_lat,max_lon`, longitudes may wrap the antimeridian) and `lat` / `lon` / `radius` (`50km`, `30mi`, or a bare number meaning kilometres; defaults to 50km). `geo` and `bbox` are lists, every circle and box is OR'd with the others and with the `lat`/`lon` centre, and a query carries at most 10 shapes. Passing a single `bbox` or `geo` string still works and is sent as a one-element list. The SDK applies the platform's own shape rules before the request leaves the client: a box is four finite numbers with `-90 <= min_lat < max_lat <= 90`, longitudes within ±180 and `min_lon` different from `max_lon`; a circle is a valid coordinate pair with an optional radius above 0 and at most 1000km.

packages/discolike-cli/src/discolike_cli/discogen.py

@@ -35,6 +35,7 @@
 WEB_SEARCH_HELP = "Toggle web search during research."
 CONTEXT_MODE_HELP = "Context mode; see docs.discolike.com."
 INCLUDE_X_SEARCH_HELP = "Toggle including X search in the research."
+TYPED_COLUMNS_HELP = "Let the detector answer yes/no, fixed-set and scale columns with a TypeSafe judgment model."
 INCLUDE_CONFIDENCE_HELP = "Add a confidence column beside each typed column."
 SEARCH_PROVIDER_ID_HELP = "Search provider ID to use for web search."
 SEARCH_CONTEXT_SIZE_HELP = "Search context size; see docs.discolike.com."
@@ -63,6 +64,7 @@ def run_command(
     include_x_search: bool | None = typer.Option(
         None, "--include-x-search/--no-include-x-search", help=INCLUDE_X_SEARCH_HELP
     ),
+    typed_columns: bool | None = typer.Option(None, "--typed-columns/--no-typed-columns", help=TYPED_COLUMNS_HELP),
     include_confidence: bool | None = typer.Option(
         None, "--include-confidence/--no-include-confidence", help=INCLUDE_CONFIDENCE_HELP
     ),
@@ -88,6 +90,7 @@ def run_command(
             web_search=web_search,
             context_mode=context_mode,
             include_x_search=include_x_search,
+            typed_columns=typed_columns,
             include_confidence=include_confidence,
             search_provider_id=search_provider_id,
             search_context_size=search_context_size,
@@ -108,6 +111,7 @@ def run_personas_command(
     include_x_search: bool | None = typer.Option(
         None, "--include-x-search/--no-include-x-search", help=INCLUDE_X_SEARCH_HELP
     ),
+    typed_columns: bool | None = typer.Option(None, "--typed-columns/--no-typed-columns", help=TYPED_COLUMNS_HELP),
     include_confidence: bool | None = typer.Option(
         None, "--include-confidence/--no-include-confidence", help=INCLUDE_CONFIDENCE_HELP
     ),
@@ -130,6 +134,7 @@ def run_personas_command(
             web_search=web_search,
             context_mode=context_mode,
             include_x_search=include_x_search,
+            typed_columns=typed_columns,
             include_confidence=include_confidence,
             search_provider_id=search_provider_id,
             search_context_size=search_context_size,

packages/discolike-cli/tests/test_discogen_cli.py

@@ -67,6 +67,26 @@ def handler(request: httpx2.Request) -> httpx2.Response:
     }
 
 
+def test_discogen_run_sends_typed_columns_when_passed(install_build_client: Callable[[Handler], None]) -> None:
+    captured: dict[str, object] = {}
+
+    def handler(request: httpx2.Request) -> httpx2.Response:
+        captured["body"] = json.loads(request.content)
+        return httpx2.Response(200, json={"task_id": "dg-1c"})
+
+    install_build_client(handler)
+    result = runner.invoke(
+        app,
+        ["discogen", "run", "--query", "q", "--domain", "acme.com", "--typed-columns"],
+    )
+    assert result.exit_code == 0, result.output
+    assert captured["body"] == {
+        "query": "q",
+        "domains": ["acme.com"],
+        "typed_columns": True,
+    }
+
+
 def test_discogen_run_sends_include_confidence_true_when_flag_passed(
     install_build_client: Callable[[Handler], None],
 ) -> None:
@@ -175,6 +195,28 @@ def handler(request: httpx2.Request) -> httpx2.Response:
     }
 
 
+def test_discogen_run_personas_sends_typed_columns_when_passed(
+    install_build_client: Callable[[Handler], None],
+) -> None:
+    captured: dict[str, object] = {}
+
+    def handler(request: httpx2.Request) -> httpx2.Response:
+        captured["body"] = json.loads(request.content)
+        return httpx2.Response(200, json={"task_id": "dg-2c"})
+
+    install_build_client(handler)
+    result = runner.invoke(
+        app,
+        ["discogen", "run-personas", "--query", "q", "--persona-id", "1", "--typed-columns"],
+    )
+    assert result.exit_code == 0, result.output
+    assert captured["body"] == {
+        "query": "q",
+        "persona_ids": [1],
+        "typed_columns": True,
+    }
+
+
 def test_discogen_run_personas_sends_include_confidence_true_when_flag_passed(
     install_build_client: Callable[[Handler], None],
 ) -> None:

packages/discolike/src/discolike/_generated/requests.py

@@ -1427,6 +1427,13 @@ class DiscoGenProcessRequest(DiscolikeRequest):
     ] = None
     web_search: Annotated[bool | None, Field(title="Web Search")] = False
     include_x_search: Annotated[bool | None, Field(title="Include X Search")] = False
+    typed_columns: Annotated[
+        bool | None,
+        Field(
+            description="Let the detector answer yes/no, fixed-set and scale columns with a TypeSafe judgment model",
+            title="Typed Columns",
+        ),
+    ] = False
     include_confidence: Annotated[bool | None, Field(title="Include Confidence")] = False
     search_provider_id: Annotated[
         str | None,
@@ -1463,6 +1470,13 @@ class DiscoGenPersonaProcessRequest(DiscolikeRequest):
     ] = None
     web_search: Annotated[bool | None, Field(title="Web Search")] = False
     include_x_search: Annotated[bool | None, Field(title="Include X Search")] = False
+    typed_columns: Annotated[
+        bool | None,
+        Field(
+            description="Let the detector answer yes/no, fixed-set and scale columns with a TypeSafe judgment model",
+            title="Typed Columns",
+        ),
+    ] = False
     include_confidence: Annotated[bool | None, Field(title="Include Confidence")] = False
     search_provider_id: Annotated[
         str | None,

packages/discolike/tests/test_discogen.py

@@ -72,6 +72,8 @@ def handler(request: httpx2.Request) -> httpx2.Response:
                 web_search=True,
                 context_mode="website",
                 include_x_search=False,
+                typed_columns=True,
+                include_confidence=True,
                 search_provider_id="serper",
                 search_context_size="medium",
             )
@@ -84,11 +86,26 @@ def handler(request: httpx2.Request) -> httpx2.Response:
         "web_search": True,
         "context_mode": "website",
         "include_x_search": False,
+        "typed_columns": True,
+        "include_confidence": True,
         "search_provider_id": "serper",
         "search_context_size": "medium",
     }
 
 
+def test_process_sends_typed_columns_when_set(make_client: ClientFactory) -> None:
+    seen = {}
+
+    def handler(request: httpx2.Request) -> httpx2.Response:
+        seen["body"] = json.loads(request.content)
+        return httpx2.Response(200, json={"task_id": "dg-typed"})
+
+    with make_client(handler) as client:
+        client.discogen.process(DiscoGenProcessRequest(query="q", domains=["a.com"], typed_columns=True))
+
+    assert seen["body"] == {"query": "q", "domains": ["a.com"], "typed_columns": True}
+
+
 def test_process_personas_posts_json_and_returns_job(make_client: ClientFactory) -> None:
     seen = {}