diff --git a/headroom/proxy/handlers/openai.py b/headroom/proxy/handlers/openai.py
index cfacab82f..701a67261 100644
--- a/headroom/proxy/handlers/openai.py
+++ b/headroom/proxy/handlers/openai.py
@@ -3361,6 +3361,63 @@ class OpenAIHandlerMixin:
         # `max_completion_tokens`.
         _normalize_openai_max_tokens(body)
 
+        # Output shaping (opt-in via HEADROOM_OUTPUT_SHAPER): verbosity steering
+        # on the chat system message. Runs after every other body mutation so the
+        # turn classifier sees the final messages, and respects the same bypass
+        # as compression. OpenAI-compatible clients that route through
+        # /v1/chat/completions (GitHub Copilot CLI, opencode, older SDKs) never
+        # reached the shaper before, so they saw zero output savings (#2302).
+        # Mutating `body` in place is sufficient here — the outbound request
+        # serializes `body` fresh, so no body-mutation tracker is needed.
+        if not _bypass:
+            from headroom.proxy import runtime_env
+            from headroom.proxy.output_savings import (
+                assign_arm,
+                conversation_key_from_body,
+                stratum_key,
+                stratum_label,
+            )
+            from headroom.proxy.output_shaper import (
+                OutputShaperSettings,
+                classify_turn,
+                resolve_verbosity_level,
+                shape_openai_chat_request,
+            )
+
+            _shaper_settings = OutputShaperSettings.from_env()
+            if _shaper_settings.enabled:
+                # Conversation-stable holdout: a whole conversation is treatment
+                # or control, which keeps the A/B comparison clean and the
+                # provider prefix cache stable (the steering block never flips
+                # mid-conversation).
+                _holdout = 0.0
+                try:
+                    _holdout = float(runtime_env.getenv("HEADROOM_OUTPUT_HOLDOUT", "0") or "0")
+                except ValueError:
+                    _holdout = 0.0
+                _arm = assign_arm(conversation_key_from_body(body), _holdout)
+                _turn_kind = classify_turn(body.get("messages", [])).value
+                _stratum = stratum_key(
+                    turn_kind=_turn_kind,
+                    input_tokens=original_tokens,
+                    model=model,
+                    has_tools=bool(body.get("tools")),
+                )
+                # Carry (arm, stratum) on the transforms channel so the outcome
+                # funnel feeds the output-savings ledger from the chat path too.
+                transforms_applied.append(stratum_label(_arm, _stratum))
+                if _arm == "treatment":
+                    _level, _src = resolve_verbosity_level(_shaper_settings)
+                    _shape_result = shape_openai_chat_request(
+                        body, _shaper_settings, level_override=_level
+                    )
+                    if _shape_result.changed:
+                        transforms_applied.extend(_shape_result.labels or [])
+                        logger.info(
+                            f"[{request_id}] OutputShaper(chat, L{_level}/{_src}): "
+                            f"{_shape_result.labels}"
+                        )
+
         # Route through LiteLLM/any-llm backend if configured
         if self.anthropic_backend is not None:
             try:
diff --git a/headroom/proxy/output_shaper.py b/headroom/proxy/output_shaper.py
index 1be86e1cc..daa84f256 100644
--- a/headroom/proxy/output_shaper.py
+++ b/headroom/proxy/output_shaper.py
@@ -58,6 +58,7 @@ from headroom.proxy.output_effort_policy import (
     lower_text_verbosity_value,
 )
 from headroom.proxy.output_steering import (
+    apply_openai_chat_verbosity_steering,
     apply_openai_responses_verbosity_steering,
     apply_verbosity_steering,
     replace_or_append_steering_block,
@@ -76,6 +77,7 @@ __all__ = [
     "OutputShaperSettings",
     "ShapeResult",
     "TurnKind",
+    "apply_openai_chat_verbosity_steering",
     "apply_openai_responses_verbosity_steering",
     "apply_verbosity_steering",
     "classify_openai_responses_input",
@@ -84,6 +86,7 @@ __all__ = [
     "route_effort",
     "route_openai_reasoning_effort",
     "route_openai_text_verbosity",
+    "shape_openai_chat_request",
     "shape_openai_responses_request",
     "shape_request",
     "steering_text",
@@ -352,6 +355,36 @@ def shape_request(
     return result
 
 
+def shape_openai_chat_request(
+    body: dict[str, Any],
+    settings: OutputShaperSettings | None = None,
+    level_override: int | None = None,
+) -> ShapeResult:
+    """Apply output-shaping levers to an OpenAI chat/completions body in place.
+
+    The chat counterpart of :func:`shape_request`. Chat carries the system
+    prompt as a ``role: "system"`` message, so verbosity steering uses the
+    chat-specific injector. Effort routing is intentionally not applied here:
+    the ``route_effort`` levers write Anthropic-shaped config and there is no
+    portable chat/completions equivalent, so only the verbosity steering lever
+    (the one that reduces output tokens) runs on this path.
+    """
+    if settings is None:
+        settings = OutputShaperSettings.from_env()
+    result = ShapeResult()
+    if not settings.enabled:
+        return result
+
+    assert result.labels is not None  # __post_init__ guarantees this
+
+    level = settings.verbosity_level if level_override is None else level_override
+    if level > 0 and apply_openai_chat_verbosity_steering(body, level):
+        result.changed = True
+        result.labels.append(f"output_shaper:verbosity:L{level}")
+
+    return result
+
+
 # ---------------------------------------------------------------------------
 # OpenAI Responses format (Codex, /v1/responses HTTP + WebSocket)
 # ---------------------------------------------------------------------------
diff --git a/headroom/proxy/output_steering.py b/headroom/proxy/output_steering.py
index 6eb31b64e..2d86a86bc 100644
--- a/headroom/proxy/output_steering.py
+++ b/headroom/proxy/output_steering.py
@@ -46,6 +46,68 @@ def apply_verbosity_steering(body: dict[str, Any], level: int) -> bool:
     return False
 
 
+def apply_openai_chat_verbosity_steering(
+    body: dict[str, Any],
+    level: int,
+) -> bool:
+    """Append or replace the steering block in an OpenAI chat/completions body.
+
+    OpenAI ``/v1/chat/completions`` carries the system prompt as a
+    ``role: "system"`` (or ``"developer"``) message inside ``messages`` rather
+    than a top-level field, so it needs its own injector (the Anthropic
+    ``system`` and Responses ``instructions`` variants do not reach it — the
+    root cause of GitHub Copilot CLI seeing zero output savings, #2302).
+
+    The block is appended to the tail of the last system/developer message so a
+    treatment conversation's steering stays byte-stable across turns (and
+    re-applies idempotently via the sentinel). When the request carries no
+    system message at all, one is inserted at the front. Returns True only when
+    the body actually changed.
+    """
+    text = steering_text(level)
+    if text is None:
+        return False
+
+    messages = body.get("messages")
+    if not isinstance(messages, list):
+        return False
+
+    target: dict[str, Any] | None = None
+    for message in messages:
+        if isinstance(message, dict) and message.get("role") in ("system", "developer"):
+            target = message
+    if target is None:
+        # No system prompt to append to — insert one carrying just the block.
+        messages.insert(0, {"role": "system", "content": text})
+        return True
+
+    content = target.get("content")
+    if content is None:
+        target["content"] = text
+        return True
+    if isinstance(content, str):
+        updated, changed = replace_or_append_steering_block(content, text)
+        if changed:
+            target["content"] = updated
+        return changed
+    if isinstance(content, list):
+        # OpenAI also accepts a content-part list ([{"type": "text", ...}]).
+        for part in content:
+            if (
+                isinstance(part, dict)
+                and part.get("type") == "text"
+                and isinstance(part.get("text"), str)
+                and part["text"].startswith(_STEERING_SENTINEL)
+            ):
+                if part["text"] == text:
+                    return False
+                part["text"] = text
+                return True
+        content.append({"type": "text", "text": text})
+        return True
+    return False
+
+
 def apply_openai_responses_verbosity_steering(
     body: dict[str, Any],
     level: int,
diff --git a/tests/test_output_shaper.py b/tests/test_output_shaper.py
index 516478942..00e274e3d 100644
--- a/tests/test_output_shaper.py
+++ b/tests/test_output_shaper.py
@@ -20,6 +20,7 @@ from headroom.proxy.output_shaper import (
     route_effort,
     route_openai_reasoning_effort,
     route_openai_text_verbosity,
+    shape_openai_chat_request,
     shape_openai_responses_request,
     shape_request,
     steering_text,
@@ -402,3 +403,40 @@ class TestOpenAIResponsesTextVerbosity:
         assert steering_text(2) in body["instructions"]
         assert body["reasoning"]["effort"] == "low"
         assert body["text"]["verbosity"] == "low"
+
+
+class TestShapeOpenAIChatRequest:
+    def test_disabled_is_noop(self):
+        body = {"messages": [{"role": "system", "content": "Sys."}]}
+        snapshot = copy.deepcopy(body)
+        result = shape_openai_chat_request(body, OutputShaperSettings(enabled=False))
+        assert result.changed is False
+        assert body == snapshot
+
+    def test_enabled_applies_verbosity_steering(self):
+        body = {
+            "messages": [
+                {"role": "system", "content": "Sys."},
+                {"role": "user", "content": "hi"},
+            ]
+        }
+        result = shape_openai_chat_request(body, ENABLED)
+        assert result.changed is True
+        assert result.labels == ["output_shaper:verbosity:L2"]
+        assert steering_text(2) in body["messages"][0]["content"]
+        # User turn is untouched.
+        assert body["messages"][1] == {"role": "user", "content": "hi"}
+
+    def test_level_override_supersedes_settings(self):
+        body = {"messages": [{"role": "system", "content": "Sys."}]}
+        result = shape_openai_chat_request(body, ENABLED, level_override=4)
+        assert result.labels == ["output_shaper:verbosity:L4"]
+        assert steering_text(4) in body["messages"][0]["content"]
+
+    def test_second_pass_is_stable(self):
+        body = {"messages": [{"role": "system", "content": "Sys."}]}
+        shape_openai_chat_request(body, ENABLED)
+        snapshot = copy.deepcopy(body)
+        second = shape_openai_chat_request(body, ENABLED)
+        assert second.changed is False
+        assert body == snapshot
diff --git a/tests/test_output_steering.py b/tests/test_output_steering.py
index 144c93b74..8b94f66c8 100644
--- a/tests/test_output_steering.py
+++ b/tests/test_output_steering.py
@@ -42,3 +42,66 @@ def test_openai_responses_steering_is_idempotent() -> None:
     snapshot = body.copy()
     assert apply_openai_responses_verbosity_steering(body, 2) is False
     assert body == snapshot
+
+
+def test_openai_chat_steering_appends_to_system_message() -> None:
+    from headroom.proxy.output_steering import apply_openai_chat_verbosity_steering
+
+    body = {
+        "messages": [
+            {"role": "system", "content": "You are helpful."},
+            {"role": "user", "content": "hi"},
+        ]
+    }
+    assert apply_openai_chat_verbosity_steering(body, 2) is True
+    sys_content = body["messages"][0]["content"]
+    assert "You are helpful." in sys_content
+    assert steering_text(2) in sys_content
+    # Other messages and ordering are untouched.
+    assert body["messages"][1] == {"role": "user", "content": "hi"}
+    assert [m["role"] for m in body["messages"]] == ["system", "user"]
+
+
+def test_openai_chat_steering_is_idempotent_and_swaps_level() -> None:
+    from headroom.proxy.output_steering import apply_openai_chat_verbosity_steering
+
+    body = {"messages": [{"role": "system", "content": "S."}]}
+    assert apply_openai_chat_verbosity_steering(body, 2) is True
+    first = body["messages"][0]["content"]
+    # Same level again: no change.
+    assert apply_openai_chat_verbosity_steering(body, 2) is False
+    assert body["messages"][0]["content"] == first
+    # Different level: replace, still exactly one block.
+    assert apply_openai_chat_verbosity_steering(body, 4) is True
+    swapped = body["messages"][0]["content"]
+    assert steering_text(4) in swapped
+    assert swapped.count("<headroom_output_shaping>") == 1
+
+
+def test_openai_chat_steering_inserts_system_when_absent() -> None:
+    from headroom.proxy.output_steering import apply_openai_chat_verbosity_steering
+
+    body = {"messages": [{"role": "user", "content": "hi"}]}
+    assert apply_openai_chat_verbosity_steering(body, 3) is True
+    assert body["messages"][0]["role"] == "system"
+    assert body["messages"][0]["content"] == steering_text(3)
+    assert body["messages"][1] == {"role": "user", "content": "hi"}
+
+
+def test_openai_chat_steering_handles_list_content() -> None:
+    from headroom.proxy.output_steering import apply_openai_chat_verbosity_steering
+
+    body = {"messages": [{"role": "system", "content": [{"type": "text", "text": "base"}]}]}
+    assert apply_openai_chat_verbosity_steering(body, 1) is True
+    parts = body["messages"][0]["content"]
+    assert parts[0] == {"type": "text", "text": "base"}
+    assert parts[1]["type"] == "text"
+    assert parts[1]["text"] == steering_text(1)
+
+
+def test_openai_chat_steering_level_zero_is_noop() -> None:
+    from headroom.proxy.output_steering import apply_openai_chat_verbosity_steering
+
+    body = {"messages": [{"role": "system", "content": "S."}]}
+    assert apply_openai_chat_verbosity_steering(body, 0) is False
+    assert body["messages"][0]["content"] == "S."