Bootstrap rein-openweights: minimal agentic loop over OpenRouter (REIN-OW-WP-0001)

Implements T01-T04:
- tools.py: green-commit-only-equivalent tool surface (read/write/edit/
  glob/grep + git status/diff/log/add+commit), path-traversal guarded.
- openrouter_client.py: own minimal chat-completions client — llm-connect's
  OpenRouterAdapter takes a single prompt string and never surfaces
  tool_calls, so it can't drive a multi-turn tool-calling loop without a
  breaking change to its frozen Core ABC. llm-connect stays an optional
  dependency (pyproject.toml), not load-bearing.
- loop.py: plan -> tool call -> observe -> repeat, budget- and
  turn-bounded, tool errors reported back to the model instead of
  crashing the loop.
- credentials.py: own OpenBao AppRole/ambient-token acquisition, per
  glas-harness ADR-002 (Option B) — glas-harness does not broker this.
- runner.py/hub.py: commit-verified success criterion + State Hub
  progress/token reporting, mirroring rein-aharness's model.

26 tests, all mocked at the httpx/subprocess boundary — no real
OpenRouter or OpenBao calls made. T05 (Forgejo repo creation) stays
open, deferred to the operator.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>

src/rein_openweights/loop.py

@@ -0,0 +1,75 @@
+"""Minimal agentic tool-use loop: plan -> tool call -> observe -> repeat."""
+
+from __future__ import annotations
+
+import json
+from dataclasses import dataclass, field
+from pathlib import Path
+from typing import Any
+
+from rein_openweights.budget import BudgetExceededError, BudgetTracker
+from rein_openweights.openrouter_client import OpenRouterClient
+from rein_openweights.tools import call_tool, openai_tool_schemas
+
+_SYSTEM_PROMPT = (
+    "You are a bounded coding agent. You may only act through the provided "
+    "tools. When the task is complete, call git_add_commit with a "
+    "descriptive message, then reply with a final message containing the "
+    "word DONE and no further tool calls."
+)
+
+
+@dataclass
+class LoopResult:
+    turns: int
+    finished: bool
+    transcript: list[dict[str, Any]] = field(default_factory=list)
+    error: str | None = None
+
+
+def run_loop(
+    client: OpenRouterClient,
+    repo_root: Path,
+    title: str,
+    description: str,
+    *,
+    max_turns: int = 20,
+    budget: BudgetTracker | None = None,
+) -> LoopResult:
+    messages: list[dict[str, Any]] = [
+        {"role": "system", "content": _SYSTEM_PROMPT},
+        {"role": "user", "content": f"# {title}\n\n{description}"},
+    ]
+    tools = openai_tool_schemas()
+
+    for turn in range(1, max_turns + 1):
+        data = client.chat(messages, tools=tools)
+
+        if budget is not None:
+            usage = data.get("usage", {})
+            try:
+                budget.consume(usage.get("total_tokens", 0))
+            except BudgetExceededError as exc:
+                return LoopResult(turns=turn, finished=False, transcript=messages, error=str(exc))
+
+        message = data["choices"][0]["message"]
+        messages.append(message)
+
+        tool_calls = message.get("tool_calls") or []
+        if not tool_calls:
+            finished = "DONE" in (message.get("content") or "")
+            return LoopResult(turns=turn, finished=finished, transcript=messages)
+
+        for call in tool_calls:
+            fn = call["function"]
+            name = fn["name"]
+            try:
+                args = json.loads(fn.get("arguments") or "{}")
+                result = call_tool(repo_root, name, args)
+            except Exception as exc:  # noqa: BLE001 - report failure to the model, keep looping
+                result = f"error: {exc}"
+            messages.append(
+                {"role": "tool", "tool_call_id": call.get("id", name), "content": result}
+            )
+
+    return LoopResult(turns=max_turns, finished=False, transcript=messages, error="max_turns exceeded")