tests: pin ink engine in _make_tui_argv npm-bootstrap tests (post-merge semantic fix)

Main's rewritten test_tui_npm_install.py tests call _make_tui_argv expecting
the Ink/npm flow unconditionally; with the dual-engine dispatch merged in,
_resolve_tui_engine() auto-selects opentui whenever ui-opentui/dist is built
in the repo, routing the call away from the path under test (first subprocess
became 'node --version' instead of 'npm run build'). Pin the engine to ink
via an autouse fixture, mirroring the existing pinning precedent in
test_tui_resume_flow.py.

cron/scripts/__init__.py

@@ -0,0 +1 @@
+"""Scripts shipped with the cron subsystem (runnable via ``python3 -m cron.scripts.<name>``)."""

cron/scripts/classify_items.py

@@ -0,0 +1,226 @@
+#!/usr/bin/env python3
+"""Classify candidate items by urgency/importance and emit only the urgent ones.
+
+The proactive-monitor pattern: a fetch step (a watcher script, an inbox dump, a
+feed) produces a list of candidate items; this script scores each with a cheap
+LLM and prints ONLY the items at or above a threshold. Below-threshold runs
+print nothing, so a cron job wrapping this stays silent unless something
+actually matters -- the classic urgency-monitor pattern (fetch -> classify
+urgency -> surface only what's above the bar).
+
+Design choices:
+  * Uses Hermes' auxiliary client with task="monitor", so the classifier model
+    is configured once in config.yaml (auxiliary.monitor.{provider,model}) and
+    can be a cheap fast model independent of the main chat model.
+  * Reads items as JSON (a list of objects) from stdin or --input-file.
+  * One LLM call scores the whole batch (cheap, single round-trip) and returns
+    structured scores; we filter locally.
+  * Empty result -> empty stdout -> the cron job's [SILENT]/empty-stdout path
+    suppresses delivery. No spam on quiet intervals.
+
+Usage (standalone):
+  cat items.json | python classify_items.py --threshold 7 \
+    --criteria "Urgent if it needs a reply today or is from my manager/family"
+
+Usage (wired to a watcher via cron, agent mode):
+  Ask the agent: "Every 10 minutes, run watch_http_json.py for my inbox feed,
+  pipe its JSON into classify_items.py with my urgency criteria, and deliver
+  whatever it prints. Stay silent if it prints nothing."
+
+Item schema (flexible): each item is an object; the classifier sees the whole
+object. A "title"/"subject"/"summary"/"text" field helps it judge. An "id"
+field (any of id/guid/message_id/url) is echoed back so duplicates can be
+deduped upstream.
+"""
+
+from __future__ import annotations
+
+import argparse
+import json
+import sys
+from typing import Any, Dict, List, Optional
+
+
+def _eprint(*args: Any) -> None:
+    print(*args, file=sys.stderr)
+
+
+def _load_items(input_file: Optional[str]) -> List[Dict[str, Any]]:
+    raw = ""
+    if input_file:
+        with open(input_file, encoding="utf-8") as f:
+            raw = f.read()
+    else:
+        raw = sys.stdin.read()
+    raw = raw.strip()
+    if not raw:
+        return []
+    try:
+        data = json.loads(raw)
+    except json.JSONDecodeError as e:
+        _eprint(f"classify_items: input is not valid JSON: {e}")
+        sys.exit(2)
+    if isinstance(data, dict):
+        # Allow {"items": [...]} or a single object.
+        if isinstance(data.get("items"), list):
+            return data["items"]
+        return [data]
+    if isinstance(data, list):
+        return [x for x in data if isinstance(x, dict)]
+    _eprint("classify_items: expected a JSON list or {items: [...]}")
+    sys.exit(2)
+
+
+def _item_id(item: Dict[str, Any], index: int) -> str:
+    for key in ("id", "guid", "message_id", "url", "link"):
+        val = item.get(key)
+        if val:
+            return str(val)
+    return f"item-{index}"
+
+
+_CLASSIFY_INSTRUCTIONS = (
+    "You are an urgency classifier for a proactive assistant. You will be given "
+    "a numbered list of items and the user's importance criteria. Score EACH "
+    "item from 0 (ignore entirely) to 10 (interrupt the user now). Return ONLY a "
+    "JSON array, one object per item, in the same order: "
+    '[{"index": <int>, "score": <int 0-10>, "reason": "<short>"}]. '
+    "No prose, no markdown fences. Be conservative: most items should score low. "
+    "Only score high when the item clearly meets the user's criteria."
+)
+
+
+def _build_prompt(items: List[Dict[str, Any]], criteria: str) -> str:
+    lines = [f"USER IMPORTANCE CRITERIA:\n{criteria}\n", "ITEMS:"]
+    for i, item in enumerate(items):
+        # Show a compact view; the model sees the salient fields.
+        view = {
+            k: item[k]
+            for k in ("title", "subject", "summary", "text", "body", "from", "sender", "url")
+            if k in item
+        }
+        if not view:
+            view = item  # fall back to the whole object
+        lines.append(f"[{i}] {json.dumps(view, ensure_ascii=False)[:1200]}")
+    lines.append(
+        "\nReturn the JSON array of scores now (one object per item, same order)."
+    )
+    return "\n".join(lines)
+
+
+def _parse_scores(content: str, n_items: int) -> Dict[int, Dict[str, Any]]:
+    text = (content or "").strip()
+    # Tolerate accidental markdown fences.
+    if text.startswith("```"):
+        text = text.strip("`")
+        if "\n" in text:
+            text = text.split("\n", 1)[1]
+    try:
+        arr = json.loads(text)
+    except json.JSONDecodeError:
+        # Last-ditch: find the first [...] block.
+        start = text.find("[")
+        end = text.rfind("]")
+        if start >= 0 and end > start:
+            try:
+                arr = json.loads(text[start : end + 1])
+            except json.JSONDecodeError:
+                _eprint("classify_items: could not parse classifier output")
+                return {}
+        else:
+            _eprint("classify_items: classifier returned no JSON array")
+            return {}
+    out: Dict[int, Dict[str, Any]] = {}
+    if isinstance(arr, list):
+        for obj in arr:
+            if not isinstance(obj, dict):
+                continue
+            idx = obj.get("index")
+            if isinstance(idx, int) and 0 <= idx < n_items:
+                out[idx] = obj
+    return out
+
+
+def main() -> int:
+    parser = argparse.ArgumentParser(description="Classify items by urgency; emit only urgent ones.")
+    parser.add_argument("--criteria", required=True, help="Plain-language importance criteria.")
+    parser.add_argument("--threshold", type=int, default=7, help="Minimum score (0-10) to surface. Default 7.")
+    parser.add_argument("--input-file", default=None, help="Read items JSON from this file instead of stdin.")
+    parser.add_argument("--format", choices=["text", "json"], default="text", help="Output format for surfaced items.")
+    args = parser.parse_args()
+
+    items = _load_items(args.input_file)
+    if not items:
+        # Nothing to classify -> silent. This is the common quiet-interval case.
+        return 0
+
+    # Import here so --help works without the package importable.
+    try:
+        from agent.auxiliary_client import call_llm
+    except Exception as e:  # pragma: no cover - import guard
+        _eprint(f"classify_items: cannot import auxiliary client: {e}")
+        return 3
+
+    prompt = _build_prompt(items, args.criteria)
+    try:
+        resp = call_llm(
+            task="monitor",
+            messages=[{"role": "user", "content": prompt}],
+            max_tokens=1024,
+            temperature=0,
+        )
+        content = resp.choices[0].message.content
+        if not isinstance(content, str):
+            content = str(content) if content else ""
+    except Exception as e:
+        # Classification failure is NOT silent -- surface it so a broken monitor
+        # doesn't quietly swallow important items. Non-zero exit -> cron alerts.
+        _eprint(f"classify_items: classifier call failed: {e}")
+        return 4
+
+    scores = _parse_scores(content, len(items))
+    surfaced = []
+    for i, item in enumerate(items):
+        s = scores.get(i)
+        score = s.get("score") if isinstance(s, dict) else None
+        if isinstance(score, int) and score >= args.threshold:
+            surfaced.append((i, item, s))
+
+    if not surfaced:
+        # Below threshold -> silent. Empty stdout; cron suppresses delivery.
+        return 0
+
+    if args.format == "json":
+        out = [
+            {
+                "id": _item_id(item, i),
+                "score": s.get("score"),
+                "reason": s.get("reason", ""),
+                "item": item,
+            }
+            for (i, item, s) in surfaced
+        ]
+        print(json.dumps(out, ensure_ascii=False, indent=2))
+    else:
+        blocks = []
+        for (i, item, s) in surfaced:
+            title = (
+                item.get("title")
+                or item.get("subject")
+                or item.get("summary")
+                or _item_id(item, i)
+            )
+            url = item.get("url") or item.get("link") or ""
+            reason = s.get("reason", "")
+            block = f"## [{s.get('score')}/10] {title}"
+            if url:
+                block += f"\n{url}"
+            if reason:
+                block += f"\n_{reason}_"
+            blocks.append(block)
+        print("\n\n".join(blocks))
+    return 0
+
+
+if __name__ == "__main__":
+    sys.exit(main())