Fix 9 seam-review findings

- Pinned target's profitability flag now overrides the extractor's bucket guess
- Extractor/target periods canonicalized so ledger forecast chaining matches
- autoRunOnDrop no longer error-loops on ungradeable inbox content; failed
  batches count as seen
- Ship 2 default graders (pipeline requires >=2 valid reports per deck)
- UI styles 'failed' deck chips as errors; .markdown discoverable
- Unknown adjudicator model disables adjudication loudly instead of silently
- Reserved rids extractor/adjudicator; teardown also clears bm-grader-* containers

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

orchestrator/bm_config.py

@@ -51,9 +51,10 @@ CONFIG_DEFAULTS = {
     "models": [
         {"alias": "grader-a", "hfModel": "Qwen/Qwen3-32B-FP8", "spark": "primary", "port": 8001},
     ],
-    # Grading panel
+    # Grading panel (>= 2 required: every deck needs >= 2 valid grade reports)
     "graders": [
         {"name": "munger-lens", "model": "grader-a", "persona": "", "temperature": None},
+        {"name": "girdley-operator", "model": "grader-a", "persona": "", "temperature": None},
     ],
     # Which catalog model runs the stage-1 structured extractor ("" = first model)
     "extractorModel": "",

orchestrator/decks.py

@@ -12,7 +12,7 @@ from __future__ import annotations
 import os
 import re
 
-SUPPORTED_EXTS = {".pdf", ".pptx", ".docx", ".txt", ".md", ".text"}
+SUPPORTED_EXTS = {".pdf", ".pptx", ".docx", ".txt", ".md", ".markdown", ".text"}
 
 # Canonical period forms: "2026-Q2", "2026-H1", "2026-05", "FY2026".
 _PERIOD_PATTERNS = [
@@ -55,6 +55,22 @@ def parse_period_from_name(filename: str) -> str | None:
     return None
 
 
+def canonicalize_period(text: str | None) -> str | None:
+    """Normalize a free-form period string ("2026-q2", "FY 2026", "2026/05")
+    to the canonical form, or None. Extractor-supplied periods and target
+    periods must pass through here so ledger lookups match filename periods."""
+    if not text:
+        return None
+    s = str(text).strip().replace("/", "-")
+    if period_sort_key(s) != _UNKNOWN_KEY:
+        return s  # already canonical
+    for pat, canon in _PERIOD_PATTERNS:
+        m = pat.search(s)
+        if m:
+            return canon(m)
+    return None
+
+
 def period_sort_key(period: str | None) -> tuple:
     """(year, start_month, granularity_rank); unknown/None sorts last."""
     if not period:

orchestrator/graders.py

@@ -83,6 +83,9 @@ def roster(cfg: dict) -> list[dict]:
     for w in (cfg.get("graders") or []):
         name = (w.get("name") or "grader").strip()
         rid = slug(name)
+        if rid in ("extractor", "adjudicator"):
+            # reserved role ids: personas/containers/outputs would collide
+            rid = f"{rid}-grader"
         if rid in seen:
             seen[rid] += 1
             rid = f"{rid}-{seen[rid]}"

orchestrator/jobs.py

@@ -70,11 +70,6 @@ REQUEST_PATH = os.path.join(STATE_DIR, "run_request")
 TICK_SECONDS = 10
 RUNNING_PHASES = ("extracting", "grading", "adjudicating", "scoring", "collecting")
 
-# Canonical-ish reporting periods: 2026-Q2, 2026-H1, FY2026, 2026-05, 2026.
-_PERIOD_RE = re.compile(
-    r"^(?:FY\s?-?\d{4}|\d{4}(?:[-/ ]?(?:Q[1-4]|H[12]|0[1-9]|1[0-2]))?)$", re.IGNORECASE)
-
-
 def _inbox_signature() -> tuple[int, str]:
     """(count, signature) of supported files anywhere in the inbox tree, for
     autoRunOnDrop stability checks (decks live in per-company subfolders)."""
@@ -229,8 +224,13 @@ class JobRunner:
             count, sig = _inbox_signature()
             if count and sig == self._last_sig and sig != self._last_done_sig:
                 # stable across two ticks and not the batch we last processed
-                triggered = True
+                if decks.discover(INBOX).get("units"):
-                self.log("[runner] inbox stable — auto-running grading")
+                    triggered = True
+                    self.log("[runner] inbox stable — auto-running grading")
+                else:
+                    # only ungradeable files (e.g. dropped at the inbox root):
+                    # mark the batch seen so we don't retrigger every tick
+                    self._last_done_sig = sig
             self._last_sig = sig
 
         if not triggered:
@@ -288,6 +288,10 @@ class JobRunner:
             needed = {r["model"] for r in valid} | {extractor_model}
             adjudicate = bool(cfg.get("adjudicatorEnabled"))
             adj_model = adj_mod.pick_model(cfg) if adjudicate else ""
+            if adjudicate and adj_model not in catalog:
+                self.log(f"[runner] WARNING: adjudicator model '{adj_model}' is not in the "
+                         "model catalog — adjudication disabled for this job")
+                adjudicate, adj_model = False, ""
             needed_all = needed | ({adj_model} if adjudicate and adj_model else set())
 
             # Air-gapped mode can't route to second-Spark models (internal net).
@@ -364,6 +368,9 @@ class JobRunner:
             self.message = f"Grading failed: {e}"
             self.log(f"[runner] JOB FAILED — {e}")
             self.log(traceback.format_exc().splitlines()[-1])
+            # A failed batch counts as seen — otherwise autoRunOnDrop retries
+            # the same failing inbox every other tick.
+            self._last_done_sig = _inbox_signature()[1]
             try:
                 serving.tear_down_all(cfg, self.log)
             except Exception:
@@ -545,8 +552,8 @@ class JobRunner:
         (flagged as period_inferred in the extraction's red-flag candidates)."""
         if unit.get("period"):
             return unit["period"], _token(unit["period"])
-        p = ((ext_obj.get("deck") or {}).get("period") or "").strip()
+        p = decks.canonicalize_period((ext_obj.get("deck") or {}).get("period"))
-        if p and _PERIOD_RE.match(p):
+        if p:
             self.log(f"[runner] period '{p}' taken from the deck text")
             return p, _token(p)
         try:

orchestrator/ledger.py

@@ -109,6 +109,7 @@ class Ledger:
     def prior_targets(self, slug: str, period: str) -> list[dict]:
         """Forward targets an earlier deck set for `period` (this deck's exam)."""
         company = self.get_company(slug)
+        period = decks_mod.canonicalize_period(period)
         if not company or not period:
             return []
         return (company.get("extracted_targets", {}).get(period) or {}).get("targets", [])
@@ -143,7 +144,9 @@ class Ledger:
         from_key = decks_mod.period_sort_key(period)
         by_period: dict[str, list[dict]] = {}
         for ft in forward_targets or []:
-            tp = ft.get("target_period")
+            # Extractor-supplied target periods are free-form ("2026-q3");
+            # canonicalize so the next deck's filename period finds them.
+            tp = decks_mod.canonicalize_period(ft.get("target_period"))
             if tp:
                 by_period.setdefault(tp, []).append(ft)
         for tp, targets in by_period.items():

orchestrator/scoring.py

@@ -87,7 +87,8 @@ def _resolve_target(kpi: dict, pinned_targets: list[dict], prior_targets: list[d
     cand, via = match_kpi(canon, pinned_cands, aliases)
     if cand is not None:
         p = cand["_src"]
-        return {"target": p.get("target"), "direction": p.get("direction") or kpi.get("direction")}, "pinned", via
+        return {"target": p.get("target"), "direction": p.get("direction") or kpi.get("direction"),
+                "profitability": p.get("profitability")}, "pinned", via
     cand, via = match_kpi(canon, prior_targets or [], aliases)
     if cand is not None:
         return {"target": cand.get("target"),
@@ -166,10 +167,15 @@ def score_deck(extraction: dict, grades: list[dict], pinned_targets: list[dict],
             target = float(tgt["target"])
             credit = _credit(float(k.get("actual", 0)), target,
                              tgt.get("direction") or k.get("direction") or "gte", floor)
+        # The operator's pinned classification beats the extractor's guess —
+        # a pinned profitability KPI must score in the profitability bucket.
+        profitability = bool(k.get("profitability"))
+        if tgt is not None and tgt.get("profitability") is not None:
+            profitability = bool(tgt["profitability"])
         kpi_results.append({
             "canonical_name": k.get("canonical_name"), "name": k.get("name"),
             "actual": k.get("actual"), "unit": k.get("unit") or "",
-            "direction": k.get("direction"), "profitability": bool(k.get("profitability")),
+            "direction": k.get("direction"), "profitability": profitability,
             "target": target, "target_source": source, "matched_via": via,
             "credit": None if credit is None else round(credit, 4),
         })

orchestrator/serving.py

@@ -167,6 +167,7 @@ def tear_down_all(cfg: dict, log) -> None:
     """Best-effort: remove every Boardroom Map serving container + the network."""
     for sp in sc.sparks(cfg):
         sc.run(sp, "docker ps -aq --filter name=bm-vllm- | xargs -r docker rm -f; "
+                   "docker ps -aq --filter name=bm-grader- | xargs -r docker rm -f; "
                    f"docker rm -f {PROXY_NAME} 2>/dev/null; true", timeout=120)
     remove_network(cfg, log)
     log("[serving] all serving torn down")

orchestrator/templates/index.html

@@ -490,7 +490,7 @@ async function refresh(){
 
     const deckChips=(rt.decks||[]).map(d=>{
       const st=d.status||'pending';
-      const cls=st==='done'?'done':st==='error'?'error':(st==='pending'?'':'busy');
+      const cls=st==='done'?'done':(st==='error'||st==='failed')?'error':(st==='pending'?'':'busy');
       const tail=d.composite!=null?(' · '+(+d.composite).toFixed(1)):(d.error?' · error':'');
       return `<span class="chip ${cls}">${esc(d.company)}${d.period?' '+esc(d.period):''}${tail}</span>`;
     }).join('');

startos/file-models/config.ts

@@ -86,7 +86,9 @@ export const configShape = z.object({
       }),
     )
     .default([
+      // >= 2 graders required: every deck needs >= 2 valid grade reports.
       { name: 'munger-lens', model: 'grader-a', persona: '', temperature: null },
+      { name: 'girdley-operator', model: 'grader-a', persona: '', temperature: null },
     ]),
 
   // Which catalog model runs the stage-1 structured KPI extractor over each