gpt-image-2 multi-image + fix: tools need reasoning_effort none on gpt-5.6 (ggg mute bug)

DECISIONS.md

@@ -35,7 +35,9 @@ Decisions inside the set architecture. D-NNN, never renumbered.
 - **D-009** — `translate()` still keys off `fix-model` although the
   repair path is gone; the whole translate-before-draw step dies in
   FDB-009 (gpt-image-2 is multilingual). Not worth a config rename
-  for one phase.
+  for one phase. *(Closed 2026-07-13: FDB-009 deleted translate();
+  the fix-model config key is now fully dead and can be dropped from
+  live configs.)*
 - **D-010** — Persistence uses stdlib `sqlite3` via
   `asyncio.to_thread`, not aiosqlite: no new dependency, and a
   connection-per-operation with WAL is plenty at this message volume.

config.toml

@@ -50,3 +50,8 @@ enable-game-info = true
 # split-threshold = 1200              # long answers split at paragraphs
 # split-max-parts = 3
 # quiet-hours = "21:00-09:00"         # no bot-initiated posts in this window
+
+# Image generation (SPEC-004)
+# image-model = "gpt-image-2"    # default; dall-e-3 gets clamped to n=1
+# image-size = "1024x1024"
+# image-quality = "medium"        # passed through only when set

fjerkroa_bot/ai_responder.py

@@ -123,6 +123,7 @@ class AIResponse(AIMessageBase):
         self.channel = channel
         self.staff = staff
         self.picture = picture
+        self.picture_count = 1
         self.picture_edit = picture_edit
         self.hack = hack
         self.vars = ["answer", "answer_needed", "channel", "staff", "picture", "hack"]
@@ -188,15 +189,15 @@ class AIResponder(AIResponderBase):
             messages.append({"role": "user", "content": content})
         return messages
 
-    async def draw(self, description: str) -> BytesIO:
+    async def draw(self, description: str, count: int = 1) -> List[BytesIO]:
         if self.config.get("leonardo-token") is not None:
-            return await self.draw_leonardo(description)
+            return [await self.draw_leonardo(description)]  # single image only, behind config
-        return await self.draw_openai(description)
+        return await self.draw_openai(description, count)
 
     async def draw_leonardo(self, description: str) -> BytesIO:
         raise NotImplementedError()
 
-    async def draw_openai(self, description: str) -> BytesIO:
+    async def draw_openai(self, description: str, count: int = 1) -> List[BytesIO]:
         raise NotImplementedError()
 
     async def post_process(self, message: AIMessage, response: Dict[str, Any]) -> AIResponse:
@@ -221,6 +222,10 @@ class AIResponder(AIResponderBase):
             bool(response.get("picture_edit", False)),
             bool(response.get("hack", False)),
         )
+        try:
+            response_message.picture_count = max(1, min(int(response.get("picture_count") or 1), 4))  # IMG-02
+        except (TypeError, ValueError):
+            response_message.picture_count = 1
         if response_message.staff is not None and response_message.answer is not None:
             response_message.answer_needed = True
         if response_message.channel is None:
@@ -250,9 +255,6 @@ class AIResponder(AIResponderBase):
         """Cheap reply/factual/emoji pre-pass (BEH-01); None = fail open."""
         raise NotImplementedError()
 
-    async def translate(self, text: str, language: str = "english") -> str:
-        raise NotImplementedError()
-
     @staticmethod
     def _entry_channel(item: Dict[str, Any]) -> Optional[str]:
         try:
@@ -299,11 +301,10 @@ class AIResponder(AIResponderBase):
             await asyncio.to_thread(self.store.save_history, self.channel, list(self.history))
 
     async def handle_picture(self, response: Dict) -> bool:
+        # Prompt goes to the image API verbatim — no translate step (IMG-05)
         if not isinstance(response.get("picture"), (type(None), str)):
             logging.warning(f"picture key is wrong in response: {pp(response)}")
             return False
-        if response.get("picture") is not None:
-            response["picture"] = await self.translate(response["picture"])
         return True
 
     def _parse_answer(self, answer: Dict[str, Any]) -> Optional[Dict[str, Any]]:

fjerkroa_bot/discord_bot.py

@@ -462,7 +462,8 @@ class FjerkroaBot(commands.Bot):
         """Send the answer paced, split and with images on the last part (BEH-04/05/06)"""
         files = None
         if response.picture is not None:
-            files = [discord.File(fp=await airesponder.draw(response.picture), filename="image.png")]
+            buffers = await airesponder.draw(response.picture, getattr(response, "picture_count", 1))
+            files = [discord.File(fp=buffer, filename=f"image-{index}.png") for index, buffer in enumerate(buffers)]
         parts = split_answer(response.answer, int(self.config.get("split-threshold", 1200)), int(self.config.get("split-max-parts", 3)))
         pace = float(self.config.get("typing-chars-per-second", 0) or 0)
         max_delay = float(self.config.get("typing-max-seconds", 8))

fjerkroa_bot/openai_responder.py

@@ -1,14 +1,14 @@
 import asyncio
+import base64
 import hashlib
 import json
 import logging
 from io import BytesIO
 from typing import Any, Dict, List, Optional, Tuple
 
-import aiohttp
 import openai
 
-from .ai_responder import AIResponder, exponential_backoff, pp, sanitize_external_text
+from .ai_responder import AIResponder, exponential_backoff, sanitize_external_text
 from .igdblib import IGDBQuery
 from .leonardo_draw import LeonardoAIDrawMixIn
 from .quota import QuotaLedger
@@ -24,10 +24,11 @@ ENVELOPE_SCHEMA = {
         "channel": {"type": ["string", "null"], "description": "Target channel name, or null for the origin channel."},
         "staff": {"type": ["string", "null"], "description": "Alert text for the staff channel, or null."},
         "picture": {"type": ["string", "null"], "description": "Image generation prompt, or null."},
+        "picture_count": {"type": "integer", "description": "How many images to generate (1-4), 1 unless more were asked for."},
         "picture_edit": {"type": "boolean", "description": "Whether the picture refers to an earlier image."},
         "hack": {"type": "boolean", "description": "Whether the user tried to manipulate the assistant."},
     },
-    "required": ["answer", "answer_needed", "channel", "staff", "picture", "picture_edit", "hack"],
+    "required": ["answer", "answer_needed", "channel", "staff", "picture", "picture_count", "picture_edit", "hack"],
     "additionalProperties": False,
 }
 ENVELOPE_RESPONSE_FORMAT = {"type": "json_schema", "json_schema": {"name": "envelope", "strict": True, "schema": ENVELOPE_SCHEMA}}
@@ -92,10 +93,7 @@ async def openai_chat(client, *args, **kwargs):
 
 
 async def openai_image(client, *args, **kwargs):
-    response = await client.images.generate(*args, **kwargs)
+    return await client.images.generate(*args, **kwargs)
-    async with aiohttp.ClientSession() as session:
-        async with session.get(response.data[0].url) as image:
-            return BytesIO(await image.read())
 
 
 class OpenAIResponder(AIResponder, LeonardoAIDrawMixIn):
@@ -126,15 +124,26 @@ class OpenAIResponder(AIResponder, LeonardoAIDrawMixIn):
         else:
             logging.warning("❌ IGDB integration DISABLED - missing configuration or disabled in config")
 
-    async def draw_openai(self, description: str) -> BytesIO:
+    async def draw_openai(self, description: str, count: int = 1) -> List[BytesIO]:
         if not self.ledger.budget_ok():
             raise RuntimeError("daily budget exhausted - refusing image call")
+        model = self.config.get("image-model", "gpt-image-2")
+        kwargs: Dict[str, Any] = {"model": model, "prompt": description, "size": self.config.get("image-size", "1024x1024")}
+        if "image-quality" in self.config:
+            kwargs["quality"] = self.config["image-quality"]
+        if model.startswith("gpt-image"):
+            kwargs["n"] = max(1, min(int(count), 4))
+        else:
+            # legacy models: single image, base64 must be requested (IMG-04)
+            kwargs["n"] = 1
+            kwargs["response_format"] = "b64_json"
         for _ in range(3):
             try:
-                response = await openai_image(self.client, prompt=description, n=1, size="1024x1024", model="dall-e-3")
+                response = await openai_image(self.client, **kwargs)
-                self.ledger.add_images(1)
+                buffers = [BytesIO(base64.b64decode(item.b64_json)) for item in response.data]
-                logging.info(f"Drawed a picture with DALL-E on this description: {repr(description)}")
+                self.ledger.add_images(len(buffers))
-                return response
+                logging.info(f"generated {len(buffers)} image(s) on {model} for: {repr(description)}")
+                return buffers
             except Exception as err:
                 logging.warning(f"Failed to generate image {repr(description)}: {repr(err)}")
         raise RuntimeError(f"Failed to generate image {repr(description)} after multiple retries")
@@ -209,6 +218,8 @@ class OpenAIResponder(AIResponder, LeonardoAIDrawMixIn):
                     if igdb_functions and isinstance(igdb_functions, list):
                         chat_kwargs["tools"] = [{"type": "function", "function": func} for func in igdb_functions]
                         chat_kwargs["tool_choice"] = "auto"
+                        # gpt-5.6 rejects tools + reasoning on chat/completions (ENV-21)
+                        chat_kwargs["reasoning_effort"] = self.config.get("reasoning-effort", "none")
                         logging.info(f"🎮 IGDB functions available to AI: {[f['name'] for f in igdb_functions]}")
                         logging.debug(f"   Full chat_kwargs with tools: {list(chat_kwargs.keys())}")
                 except (TypeError, AttributeError) as e:
@@ -343,27 +354,6 @@ class OpenAIResponder(AIResponder, LeonardoAIDrawMixIn):
             logging.debug(f"Full traceback: {traceback.format_exc()}")
         return None, limit
 
-    async def translate(self, text: str, language: str = "english") -> str:
-        if "fix-model" not in self.config:
-            return text
-        message = [
-            {
-                "role": "system",
-                "content": f"You are an professional translator to {language} language,"
-                f" you translate everything you get directly to {language}"
-                f" if it is not already in {language}, otherwise you just copy it.",
-            },
-            {"role": "user", "content": text},
-        ]
-        try:
-            result = await openai_chat(self.client, model=self.config["fix-model"], messages=message)
-            response = result.choices[0].message.content
-            logging.info(f"got this translated message:\n{pp(response)}")
-            return response
-        except Exception as err:
-            logging.warning(f"failed to translate the text: {repr(err)}")
-        return text
-
     async def classify(self, message: Any, history_tail: List[Dict[str, Any]]) -> Optional[Dict[str, Any]]:
         """~100-token reply/factual/emoji verdict on classifier-model (BEH-01/03)."""
         if "classifier-model" not in self.config or not self.ledger.budget_ok():

manual-verification.md

@@ -8,7 +8,7 @@ with date + result.
 | --- | --- | --- |
 | DEP-01 | 2026-07-13 | Verified with the v3.0.0 ggg deploy: tag-only refusal + untracked config/state survived. fjerkroa redeploy after the service window (tree already identical to 3d22894). |
 | DEP-02 | 2026-07-13 | Service map exercised: luma restart via script (v3.0.0); kroa mapping code-reviewed, exercised on its next deploy. |
-| DEP-03 | 2026-07-13 | ggg had no pre-existing bot.db (pickle era) — nothing to back up; backup branch code-reviewed, exercised on the next deploy of either host. |
+| DEP-03 | 2026-07-13 | Exercised with the v3.1.0 ggg deploy: bot.db.pre-v3.1.0 confirmed on the host. (v3.0.0 note: no pre-existing db in the pickle era.) |
 | DEP-04 | 2026-07-13 | Smoke gate exercised on ggg: RUNNING + fresh login line. |
 | DEP-05 | 2026-07-13 | Live-verified: kroa deploy attempt ~15h Oslo refused without DEPLOY_FORCE=1. |
 | DEP-06 | 2026-07-13 | Rollback documented (older tag + db backup restore); live drill pending — next release. |

specs/SPEC-001-responder-envelope.md

@@ -75,6 +75,14 @@ in a context suffix, not inline — see ENV-20; legacy `{date}`,
 `{time}`, `{news}`, `{memory}` placeholders in operator templates are
 stripped.
 
+### ENV-21 — Tool calls disable reasoning effort (coverage: test)
+
+When function tools are attached to a chat call, the call carries
+`reasoning_effort` (config `reasoning-effort`, default `"none"`) —
+gpt-5.6 models reject tools + reasoning on chat/completions with a
+400 otherwise (found live on ggg 2026-07-13: IGDB tools made Luma
+mute after the Luna cutover). Tool-less calls stay untouched.
+
 ### ENV-20 — Persona prefix is byte-stable (coverage: test)
 
 `message()` renders the system message as: static persona text
@@ -140,6 +148,7 @@ ENV-06.
 
 Every chat call carries `response_format` = strict JSON schema named
 `envelope` with exactly the fields `answer`, `answer_needed`,
-`channel`, `staff`, `picture`, `picture_edit`, `hack` — all required,
+`channel`, `staff`, `picture`, `picture_count` (since FDB-009,
+IMG-02), `picture_edit`, `hack` — all required,
 `additionalProperties: false`, nullable where the protocol allows
 null. Tool-followup calls carry the same format.

specs/SPEC-004-images.md

@@ -0,0 +1,39 @@
+# SPEC-004 — Image generation
+
+Generation on `image-model` (default `gpt-image-2`), base64 end to
+end — no URL downloads, no expiring CDN links in the generation path.
+Optional knobs: `image-size` (default 1024x1024), `image-quality`
+(passed through only when set). The Leonardo path stays behind
+`leonardo-token` until parity is confirmed, then dies. The input
+pipeline (attachment cache, vision, edit/remix) is FDB-010 / IMG-10+.
+
+### IMG-01 — Images arrive as base64 buffers (coverage: test)
+
+`draw_openai(description, count)` requests `count` images and returns
+a list of decoded image buffers straight from the API response; every
+generated image is metered in the ledger (SAF-05).
+
+### IMG-02 — The envelope carries picture_count (coverage: test)
+
+The envelope gains `picture_count` (integer). `post_process` clamps
+it to 1..4 and defaults to 1 when absent (legacy history entries,
+old-model output). ENV-19's field list is revised accordingly.
+
+### IMG-03 — Multiple images, one message (coverage: test)
+
+`picture_count` images are attached as multiple files to a single
+Discord send (the last part when the answer is split, per BEH-06).
+
+### IMG-04 — Legacy image models degrade safely (coverage: test)
+
+When `image-model` is not a `gpt-image-*` model (e.g. `dall-e-3`),
+the count is clamped to 1 and `response_format="b64_json"` is
+requested explicitly (gpt-image models return base64 natively and
+reject the parameter).
+
+### IMG-05 — Picture prompts go to the API untouched (coverage: test)
+
+The translate-before-draw step is deleted: the model's picture prompt
+reaches the image API verbatim (current image models handle
+Norwegian/German natively). The `translate()` method and its
+`fix-model` dependency are gone (closes D-009).

tests/test_ai.py

@@ -102,33 +102,6 @@ You always try to say something positive about the current day and the Fjærkroa
         # Skip this test due to Mock iteration issues - functionality works in practice
         self.skipTest("Mock iteration issue - test works in real usage")
 
-    async def test_translate1(self) -> None:
-        self.bot.airesponder.config["fix-model"] = "gpt-4o-mini"
-
-        # Mock translation responses
-        def translation_side_effect(*args, **kwargs):
-            mock_resp = Mock()
-            mock_resp.choices = [Mock()]
-            mock_resp.choices[0].message = Mock()
-
-            # Check the input text to return appropriate translation
-            user_content = kwargs["messages"][1]["content"]
-            if user_content == "Das ist ein komischer Text.":
-                mock_resp.choices[0].message.content = "This is a strange text."
-            elif user_content == "This is a strange text.":
-                mock_resp.choices[0].message.content = "Dies ist ein seltsamer Text."
-            else:
-                mock_resp.choices[0].message.content = user_content
-
-            return mock_resp
-
-        self.mock_openai_chat.side_effect = translation_side_effect
-
-        response = await self.bot.airesponder.translate("Das ist ein komischer Text.")
-        self.assertEqual(response, "This is a strange text.")
-        response = await self.bot.airesponder.translate("This is a strange text.", language="german")
-        self.assertEqual(response, "Dies ist ein seltsamer Text.")
-
     async def test_fix1(self) -> None:
         # Skip this test due to Mock iteration issues - functionality works in practice
         self.skipTest("Mock iteration issue - test works in real usage")

tests/test_bdd_envelope.py

@@ -49,9 +49,6 @@ class FakeModelResponder(AIResponder):
     async def classify(self, message, history_tail):
         return getattr(self, "scripted_classification", None)
 
-    async def translate(self, text: str, language: str = "english") -> str:
-        return text
-
 
 @given(parsers.parse("a responder with history limit {limit:d}"), target_fixture="responder")
 def responder(limit):

tests/test_openai_responder_simple.py

@@ -30,16 +30,6 @@ class TestOpenAIResponderSimple(unittest.IsolatedAsyncioTestCase):
         """ENV-18: the repair path is gone — no fix() on the responder."""
         self.assertFalse(hasattr(self.responder, "fix"))
 
-    async def test_translate_no_fix_model(self):
-        """Test translate when no fix-model is configured."""
-        config_no_fix = {"openai-key": "test", "model": "gpt-4"}
-        responder = OpenAIResponder(config_no_fix)
-
-        original_text = "Hello world"
-        result = await responder.translate(original_text)
-
-        self.assertEqual(result, original_text)
-
     async def test_consolidate_no_memory_model(self):
         """MEM-10: without memory-model, consolidation is a no-op returning None."""
         config_no_memory = {"openai-key": "test", "model": "gpt-4"}

tests/test_spec_beh.py

@@ -121,7 +121,7 @@ class TestSplitSends(OpsBase):
         self.bot.config["split-threshold"] = 50
         answer = "Første del.\n\nAndre del som også er ganske lang her."
         response = AIResponse(answer, True, "chat", None, "a cat", False, False)
-        self.bot.airesponder.draw = AsyncMock(return_value=__import__("io").BytesIO(b"png"))
+        self.bot.airesponder.draw = AsyncMock(return_value=[__import__("io").BytesIO(b"png")])
         channel = MagicMock(spec=TextChannel)
         channel.send = AsyncMock()
         await self.bot.send_answer_with_typing(response, channel, self.bot.airesponder, factual=True)

tests/test_spec_img.py

@@ -0,0 +1,87 @@
+"""Unit coverage for SPEC-004 image generation (IMG-01..05)."""
+
+import base64
+import unittest
+from unittest.mock import AsyncMock, MagicMock, Mock, patch
+
+from discord import TextChannel
+
+from fjerkroa_bot.ai_responder import AIMessage, AIResponder, AIResponse
+from fjerkroa_bot.openai_responder import OpenAIResponder
+
+from .test_bdd_envelope import FakeModelResponder, envelope
+from .test_spec_ops import OpsBase
+
+RESPONDER_CONFIG = {"openai-token": "t", "model": "m", "system": "s", "history-limit": 5}
+
+
+def image_api_result(count):
+    return Mock(data=[Mock(b64_json=base64.b64encode(f"png{i}".encode()).decode()) for i in range(count)])
+
+
+class TestBase64Generation(unittest.IsolatedAsyncioTestCase):
+    async def test_draw_returns_decoded_buffers_and_meters(self):
+        """IMG-01: count images decoded from b64_json, each metered in the ledger."""
+        responder = OpenAIResponder(RESPONDER_CONFIG, "chat")
+        with patch("fjerkroa_bot.openai_responder.openai_image", new_callable=AsyncMock) as image_mock:
+            image_mock.return_value = image_api_result(2)
+            buffers = await responder.draw_openai("en katt på brygga", 2)
+        self.assertEqual([buf.read() for buf in buffers], [b"png0", b"png1"])
+        self.assertEqual(responder.ledger.images_today(), 2)
+        self.assertEqual(image_mock.await_args.kwargs["n"], 2)
+        self.assertEqual(image_mock.await_args.kwargs["model"], "gpt-image-2")
+        self.assertNotIn("response_format", image_mock.await_args.kwargs)
+
+    async def test_legacy_model_clamped_single_b64(self):
+        """IMG-04: dall-e-3 -> n=1 and explicit response_format=b64_json."""
+        config = dict(RESPONDER_CONFIG, **{"image-model": "dall-e-3"})
+        responder = OpenAIResponder(config, "chat")
+        with patch("fjerkroa_bot.openai_responder.openai_image", new_callable=AsyncMock) as image_mock:
+            image_mock.return_value = image_api_result(1)
+            buffers = await responder.draw_openai("a cat", 3)
+        self.assertEqual(len(buffers), 1)
+        self.assertEqual(image_mock.await_args.kwargs["n"], 1)
+        self.assertEqual(image_mock.await_args.kwargs["response_format"], "b64_json")
+
+
+class TestPictureCountEnvelope(unittest.IsolatedAsyncioTestCase):
+    async def clamp(self, raw):
+        responder = FakeModelResponder({"system": "s", "history-limit": 5}, "chat")
+        payload = {"answer": "ok", "answer_needed": True, "channel": "chat", "picture": "katt"}
+        if raw is not None:
+            payload["picture_count"] = raw
+        return await responder.post_process(AIMessage("alice", "tegn", "chat"), payload)
+
+    async def test_clamped_and_defaulted(self):
+        """IMG-02: picture_count clamps to 1..4, defaults to 1 when absent."""
+        self.assertEqual((await self.clamp(3)).picture_count, 3)
+        self.assertEqual((await self.clamp(9)).picture_count, 4)
+        self.assertEqual((await self.clamp(0)).picture_count, 1)
+        self.assertEqual((await self.clamp(None)).picture_count, 1)
+
+
+class TestMultiImageSend(OpsBase):
+    async def test_files_attached_to_single_send(self):
+        """IMG-03: picture_count images ride as multiple files on one send."""
+        response = AIResponse("her er kattene", True, "chat", None, "to katter", False, False)
+        response.picture_count = 2
+        import io
+
+        self.bot.airesponder.draw = AsyncMock(return_value=[io.BytesIO(b"a"), io.BytesIO(b"b")])
+        channel = MagicMock(spec=TextChannel)
+        channel.send = AsyncMock()
+        await self.bot.send_answer_with_typing(response, channel, self.bot.airesponder, factual=True)
+        self.bot.airesponder.draw.assert_awaited_once_with("to katter", 2)
+        files = channel.send.await_args.kwargs["files"]
+        self.assertEqual(len(files), 2)
+
+
+class TestNoTranslateStep(unittest.IsolatedAsyncioTestCase):
+    async def test_translate_is_gone_prompt_untouched(self):
+        """IMG-05: no translate() anywhere; the picture prompt survives verbatim."""
+        responder = FakeModelResponder({"system": "s", "history-limit": 5}, "chat")
+        self.assertFalse(hasattr(responder, "translate"))
+        self.assertFalse(hasattr(AIResponder, "translate"))
+        responder.scripted.append(envelope(answer="ok", answer_needed=True, picture="en rød katt på brygga"))
+        result = await responder.send(AIMessage("alice", "tegn en katt", "chat"))
+        self.assertEqual(result.picture, "en rød katt på brygga")

tests/test_spec_structured.py

@@ -43,7 +43,7 @@ class TestEnvelopeSchema(unittest.IsolatedAsyncioTestCase):
         """ENV-19: strict envelope schema — exact fields, all required, closed object."""
         json_schema = ENVELOPE_RESPONSE_FORMAT["json_schema"]
         schema = json_schema["schema"]
-        expected = {"answer", "answer_needed", "channel", "staff", "picture", "picture_edit", "hack"}
+        expected = {"answer", "answer_needed", "channel", "staff", "picture", "picture_count", "picture_edit", "hack"}
         self.assertEqual(set(schema["properties"]), expected)
         self.assertEqual(set(schema["required"]), expected)
         self.assertFalse(schema["additionalProperties"])

tests/test_spec_tools.py

@@ -0,0 +1,38 @@
+"""Unit coverage for ENV-21 (tools + reasoning_effort, found live on ggg)."""
+
+import unittest
+from unittest.mock import AsyncMock, Mock, patch
+
+from fjerkroa_bot.openai_responder import OpenAIResponder
+
+from .test_bdd_envelope import envelope
+
+
+def ok_result():
+    message = Mock(content=envelope(answer="x", answer_needed=True), role="assistant", tool_calls=None, refusal=None)
+    return Mock(choices=[Mock(message=message)], usage="usage")
+
+
+class TestToolsReasoningEffort(unittest.IsolatedAsyncioTestCase):
+    async def chat_kwargs(self, with_tools):
+        config = {"openai-token": "t", "model": "gpt-5.6-luna", "system": "s", "history-limit": 5, "enable-game-info": with_tools}
+        responder = OpenAIResponder(config, "chat")
+        if with_tools:
+            responder.igdb = Mock()
+            responder.igdb.get_openai_functions = Mock(return_value=[{"name": "search_games", "parameters": {}}])
+        with patch("fjerkroa_bot.openai_responder.openai_chat", new_callable=AsyncMock) as chat_mock:
+            chat_mock.return_value = ok_result()
+            await responder.chat([{"role": "user", "content": "hi"}], 10)
+        return chat_mock.await_args.kwargs
+
+    async def test_tools_carry_reasoning_effort_none(self):
+        """ENV-21: tools attached -> reasoning_effort 'none' rides along."""
+        kwargs = await self.chat_kwargs(with_tools=True)
+        self.assertIn("tools", kwargs)
+        self.assertEqual(kwargs["reasoning_effort"], "none")
+
+    async def test_toolless_calls_untouched(self):
+        """ENV-21: without tools no reasoning_effort is sent."""
+        kwargs = await self.chat_kwargs(with_tools=False)
+        self.assertNotIn("tools", kwargs)
+        self.assertNotIn("reasoning_effort", kwargs)