Fix local model tool-call loops

extensions/python/system_prompt/AGENTS.md

@@ -6,7 +6,7 @@
 
 ## Ownership
 
-- Ordered Python files own main, tools, MCP, secrets, skills, and project prompt sections.
+- Ordered Python files own main, small-local-model, tools, MCP, secrets, skills, and project prompt sections.
 - Active project instruction bodies are moved into prompt protocol; the system prompt keeps project metadata and stable project rules.
 
 ## Local Contracts

extensions/python/system_prompt/_10_small_local_model_prompt.py

@@ -0,0 +1,87 @@
+import re
+from typing import Any
+from urllib.parse import urlparse
+
+from helpers.extension import Extension, extensible
+from agent import Agent, LoopData
+
+
+LOCAL_PROVIDER_IDS = {"ollama", "lm_studio"}
+LOCAL_HOSTS = {"localhost", "127.0.0.1", "0.0.0.0", "::1", "host.docker.internal"}
+THINKING_MODEL_MARKERS = (
+    "qwen3",
+    "qwen-3",
+    "qwq",
+    "deepseek-r1",
+    "deepseek_r1",
+    "gpt-oss",
+    "gemma4",
+    "gemma-4",
+)
+SMALL_LOCAL_MAX_B = 14.0
+MODEL_SIZE_RE = re.compile(r"(?<!\d)(\d+(?:\.\d+)?)[-_ ]?b(?![a-z])", re.IGNORECASE)
+
+
+class SmallLocalModelPrompt(Extension):
+    async def execute(
+        self,
+        system_prompt: list[str] = [],
+        loop_data: LoopData = LoopData(),
+        **kwargs: Any,
+    ):
+        if not self.agent:
+            return
+        prompt = await build_prompt(self.agent)
+        if prompt:
+            system_prompt.append(prompt)
+
+
+@extensible
+async def build_prompt(agent: Agent) -> str:
+    try:
+        from plugins._model_config.helpers.model_config import get_chat_model_config
+
+        chat_cfg = get_chat_model_config(agent)
+    except Exception:
+        return ""
+
+    if should_include_small_local_prompt(chat_cfg):
+        return agent.read_prompt("agent.system.main.small_local_model.md")
+    return ""
+
+
+def should_include_small_local_prompt(chat_cfg: dict[str, Any] | None) -> bool:
+    if not isinstance(chat_cfg, dict):
+        return False
+
+    provider = str(chat_cfg.get("provider") or "").lower().strip()
+    name = str(chat_cfg.get("name") or "").lower().strip()
+    api_base = str(chat_cfg.get("api_base") or "").lower().strip()
+
+    is_local = provider in LOCAL_PROVIDER_IDS or _is_local_api_base(api_base)
+    if not is_local:
+        return False
+
+    if any(marker in name for marker in THINKING_MODEL_MARKERS):
+        return True
+
+    size_b = _model_size_billions(name)
+    return size_b is not None and size_b <= SMALL_LOCAL_MAX_B
+
+
+def _is_local_api_base(api_base: str) -> bool:
+    if not api_base:
+        return False
+    parsed = urlparse(api_base if "://" in api_base else f"http://{api_base}")
+    host = (parsed.hostname or "").lower()
+    return host in LOCAL_HOSTS
+
+
+def _model_size_billions(model_name: str) -> float | None:
+    match = MODEL_SIZE_RE.search(model_name)
+    if not match:
+        return None
+    try:
+        return float(match.group(1))
+    except ValueError:
+        return None