dashboard: skip DOM rebuild on unchanged poll, publish-time staleness, fix boundary countdowns

poll() now compares raw payload text and re-renders only what a changed
file can affect, preserving selection, disclosure, and scroll state. Hero
freshness reflects publish time (STALE warning past 15 min while market
open), and countdowns resolve their wrap interval from data-interval
instead of reverse-looking shared TF boundaries in snapshot.timeframes.

agent_panel.py

@@ -77,6 +77,13 @@ geopolitical stress / weak dollar are gold-bullish.
 _TAKE_CONTRACT = """\
 Your review is advisory research on an already-generated signal; you are
 one voice on a panel, not the decision maker.
+Hard rules: use ONLY the data in the JSON you receive — do not invent
+numbers, events, or price levels. If the evidence your role needs is
+thin or missing, answer "neutral" with confidence below 30, unless your
+role's instructions say otherwise.
+Confidence scale (0-100): 80-100 strong one-sided evidence; 50-79 solid
+case with some doubt; 30-49 mixed evidence; below 30 little basis to
+judge.
 Write the note in plain everyday English for someone who has never
 traded: short simple sentences, no trading jargon, no acronyms, no
 abbreviations. Say "profit versus loss", not "RR"; "the 4-hour chart",
@@ -100,10 +107,19 @@ number is out), a news "sentiment" score for gold, and an optional
 Judge ONE thing: does the macro backdrop support the proposed direction?
 Weigh released surprises over stale headlines; an imminent unreleased
 high-impact event is a reason for lower confidence, not a direction.
+Stance rules:
+- support: the released data and news flow clearly push gold in the
+  proposed direction.
+- oppose: they clearly push gold the other way.
+- neutral: the picture is mixed or stale — or there are no meaningful
+  headlines or events to judge (score that low confidence).
 """ + _GOLD_DOCTRINE + """\
 Example: brief direction BUY, headlines dominated by hawkish Fed
 repricing and a hot CPI print -> {"stance": "oppose", "confidence": 70,
 "note": "Inflation is running hot, so interest rates should stay high — that usually pushes gold down."}
+Example: brief direction BUY, headlines led by an escalating conflict
+and a soft jobs report -> {"stance": "support", "confidence": 75,
+"note": "Worries about war and a cooling economy usually send money into gold."}
 """ + _TAKE_CONTRACT
 
 _TECH_SYSTEM = """\
@@ -118,9 +134,18 @@ proposed direction? Look for indicators fighting each other, the signal
 fighting the regime (e.g. a BUY in trending_down), higher timeframes
 disagreeing, price pressed into a key level, or an exhausted move being
 chased.
+Stance rules:
+- support: the indicators, higher timeframes, and regime mostly agree
+  with the proposed direction and none of the conflicts above appear.
+- oppose: one or more of those conflicts is present and serious.
+- neutral: the evidence genuinely cuts both ways, or too much of it is
+  missing to judge (score that low confidence).
 Example: brief direction SELL in regime trending_up with H1 and H4 both
 BUY -> {"stance": "oppose", "confidence": 80,
 "note": "This bets on gold falling while the bigger picture still points up."}
+Example: brief direction BUY in regime trending_up with M15 and H1 both
+BUY and exhaustion 0 -> {"stance": "support", "confidence": 70,
+"note": "Every way of looking at the chart points up, so buying goes with the flow."}
 """ + _TAKE_CONTRACT
 
 _RISK_SYSTEM = """\
@@ -133,11 +158,23 @@ Judge ONE thing: is this setup's risk acceptable as constructed? Check
 reward-to-risk adequacy, stop distance versus the volatility regime
 (a tight stop in extreme vol dies to noise; a huge stop in low vol is
 oversized), spread as a fraction of the stop, and event landmines about
-to hit. A missing setup means the signal graded too low for one —
-oppose unless the rest is exceptional.
+to hit.
+Stance rules:
+- support: the likely reward clearly justifies the risk, the stop fits
+  the current volatility, and no event landmine is imminent.
+- oppose: reward too thin for the risk, a stop mismatched to the
+  volatility, spread eating a big share of the stop, an imminent
+  high-impact event — or no setup at all (a missing setup means the
+  signal graded too low for one; oppose unless the rest is
+  exceptional).
+- neutral: acceptable but unremarkable — nothing dangerous, nothing
+  attractive.
 Example: RR 1.4 with volatility extreme and a high-impact event due ->
 {"stance": "oppose", "confidence": 65,
 "note": "The possible profit is small for such wild price swings, and big economic news is due soon."}
+Example: RR 2.4 with normal volatility and no events due ->
+{"stance": "support", "confidence": 70,
+"note": "The possible profit is more than double the possible loss, and conditions look calm."}
 """ + _TAKE_CONTRACT
 
 _CONTRARIAN_SYSTEM = """\
@@ -164,6 +201,10 @@ Weigh the takes into ONE consensus on whether to act on the signal:
 or "NEUTRAL" (genuinely split or low conviction). Weigh a high-
 confidence oppose from any single analyst seriously — one strong veto
 can outweigh two lukewarm supports. Do not average blindly.
+Base the verdict and rationale ONLY on the takes given — do not add
+outside analysis.
+Confidence scale (0-100): 80-100 the panel clearly leans one way; 50-79
+a lean with real dissent; below 50 split or low conviction.
 Write the rationale in plain everyday English for someone who has never
 traded: short simple sentences, no trading jargon, no acronyms, no
 abbreviations.

config.py

@@ -166,6 +166,9 @@ class NewsConfig:
     # Must stay below pre_event_buffer_minutes so an event can't cross
     # into the danger window while a stale cache says it's clear.
     context_cache_ttl_seconds: int = 600
+    # Maximum age of RSS headlines accepted for scoring. Older headlines
+    # are discarded before keyword analysis and LLM enrichment.
+    headline_max_age_seconds: int = 43200  # 12 hours
 
     rss_feeds: List[str] = field(default_factory=lambda: [
         "https://investinglive.com/feed/",

llm_provider_switch_plan.txt

@@ -0,0 +1,252 @@
+================================================================================
+MULTI-PROVIDER LLM LAYER - PLAN
+(DeepSeek for news summary, Anthropic Claude for agent panel)
+Written 2026-08-08. Plan only - no code has been changed.
+================================================================================
+
+WHY
+---
+Today every LLM feature (news enrichment + agent panel) goes through one
+hardwired client: llm_client.py -> DeepSeekClient, a module singleton reached
+via get_llm_client(). This plan describes how to route different features to
+different providers - e.g. keep DeepSeek for cheap high-volume news scoring,
+put the agent panel on Anthropic Claude for better reasoning.
+
+The repo already solved this problem once for market data: the providers/
+package (BaseDataProvider owns shared machinery, subclasses implement only
+_fetch_raw, a registry + one config knob selects the provider). This plan
+mirrors that proven pattern at the LLM layer, scaled down to a single module.
+
+BLAST RADIUS (verified by grep)
+-------------------------------
+get_llm_client() call sites:
+  - news_engine.py ....... 4 sites
+  - agent_panel.py ....... 3 sites (+1 timeout getattr)
+  - telegram_bot.py ...... 1 site (/status health; reads private _count,
+                           _count_day, _daily_cap fields)
+  - test_all.py .......... 41 locations stub via  lc._client = _StubLLM(...)
+Out of scope: static/news_summary.php (own PHP DeepSeek call + key file,
+separate deployment).
+
+DESIGN INVARIANTS (carried over unchanged)
+------------------------------------------
+1. Fail-safe contract: every call returns Optional[Dict]; any failure -> None;
+   callers keep their non-LLM fallbacks; LLM output never gates signals.
+2. Single attempt, no retries (news cache cadence is the retry); per-provider
+   UTC daily cap; warn-once logging; health stamps (last_ok, last_error).
+3. Static system prompts stay byte-identical constants - provider-neutral,
+   and they map to prompt caching on BOTH providers (DeepSeek prefix cache;
+   Anthropic cache_control ephemeral).
+4. Test compatibility: all 41 existing lc._client stub sites keep working
+   with zero edits.
+
+================================================================================
+1. llm_client.py REFACTOR  (~195 -> ~430 lines, no new files)
+================================================================================
+
+1a. BaseLLMClient - shared machinery (extracted from today's DeepSeekClient)
+    - __init__(api_key, model, timeout, daily_cap, enabled)
+    - public: name ("deepseek"/"anthropic"), timeout property,
+      usage() -> (used_today, cap)   # so telegram_bot stops reading privates
+    - owns: available property, _warn_once, _under_cap() (UTC-day counter,
+      lock), health stamps, and the template method:
+
+        def chat_json(self, system_prompt, user_payload):
+            if not self.available or not self._under_cap():
+                return None
+            try:
+                return self._request(system_prompt, user_payload)  # hook
+            except <provider-agnostic error mapping>:
+                # stamps last_error, returns None
+
+    - subclasses implement ONLY _request(system_prompt, payload) -> dict|None.
+
+1b. DeepSeekClient(BaseLLMClient) - behavior-identical move
+    Current requests-based logic relocates into _request: same URL,
+    thinking:disabled, response_format:json_object, temperature 0,
+    max_tokens 2000, sort_keys=True payload, _parse_response.
+    Review criterion: Module 19 tests pass UNMODIFIED (they patch
+    client._session, which stays).
+
+1c. AnthropicClient(BaseLLMClient) - new, official SDK
+    - Official `anthropic` Python SDK (add to requirements.txt), NOT raw
+      requests. LAZY IMPORT inside __init__: package missing -> warn-once +
+      client unavailable, so DeepSeek-only deployments never install it.
+    - Constructor: anthropic.Anthropic(api_key=..., timeout=<configured>,
+      max_retries=0)   # house rule: single attempt
+    - _request:
+        resp = self._client.messages.create(
+            model=self._model,                  # default "claude-opus-5"
+            max_tokens=4000,                    # covers thinking + JSON reply
+            output_config={"effort": "low"},    # cheap structured takes
+            system=[{"type": "text", "text": system_prompt,
+                     "cache_control": {"type": "ephemeral"}}],
+            messages=[{"role": "user",
+                       "content": json.dumps(user_payload, sort_keys=True)}],
+        )
+        if resp.stop_reason == "refusal":       # Opus 5: HTTP 200, check first
+            return None
+        text = first text block in resp.content
+        return self._parse_json(text)   # tolerant: strip ```json fences,
+                                        # json.loads, dict check
+    - DELIBERATELY ABSENT (would 400 on Claude Opus 5): temperature (removed
+      on Opus 5 - do NOT copy from the DeepSeek client), budget_tokens,
+      prefills, response_format.
+    - Error mapping: APIConnectionError -> "network",
+      APIStatusError -> "http_<code>", parse fail -> "parse"
+      (same last_error kinds the /status display already understands).
+    - Defaults: model claude-opus-5 (config-overridable, e.g. claude-haiku-4-5
+      for ~5x cheaper), timeout 30s (Claude slower than V4-Flash), own
+      daily_request_cap 500.
+
+1d. Registry + per-consumer routing
+        _PROVIDERS = {"deepseek": DeepSeekClient, "anthropic": AnthropicClient}
+        LLM_CONSUMERS = ("news", "agent_panel")
+        _clients = {}     # keyed by PROVIDER name -> two consumers on the
+                          # same provider share one instance and one cap
+        _client = None    # kept: GLOBAL TEST OVERRIDE
+
+        def get_llm_client(consumer="news"):
+            if _client is not None:          # tests: lc._client = stub
+                return _client               #   -> shadows ALL consumers
+            name = get_app_config().llm_routing.get(consumer, "deepseek")
+            create-once per provider, return _clients[name]
+
+        def reset_llm_client():              # clears _client AND _clients
+
+    Keeping _client as a documented test-override global is what makes the
+    41 existing stub sites work untouched.
+
+================================================================================
+2. CONFIG  (app_config.py + config.json.example)
+================================================================================
+- New top-level "anthropic" block, mirroring "deepseek":
+    {api_key, model, enabled, timeout_seconds, daily_request_cap}
+  plus anthropic_api_key() resolver: ANTHROPIC_API_KEY env -> config.json -> "".
+- New top-level "llm" ROUTING block:
+    {"news": "deepseek", "agent_panel": "deepseek"}
+  Validation: keys within {news, agent_panel}; values within registered
+  provider names. Absent block -> {} -> everything on DeepSeek (today's
+  behavior; zero-migration default). AppConfig.llm_routing: Dict[str, str].
+
+- The target state is then PURE CONFIG - no code changes on switch day:
+
+    "llm":       { "news": "deepseek", "agent_panel": "anthropic" },
+    "anthropic": { "api_key": "", "model": "claude-opus-5", "enabled": true,
+                   "timeout_seconds": 30, "daily_request_cap": 500 }
+
+================================================================================
+3. CONSUMER EDITS  (mechanical, ~10 lines total)
+================================================================================
+- news_engine.py:  4 call sites -> get_llm_client("news")
+- agent_panel.py:  3 call sites -> get_llm_client("agent_panel");
+                   getattr(client, "_timeout", ...) -> public client.timeout
+- telegram_bot.py _news_health_lines: iterate the DISTINCT providers actually
+  routed (news + panel); per provider print "<name>: used/cap calls today"
+  via the new usage() accessor instead of private fields. DeepSeek keeps its
+  "headlines scored" extra; cap/error warnings work off base-class stamps.
+- NO changes to prompts, payload builders, caches, or the panel's own
+  max_panels_per_day budget - all provider-agnostic already.
+
+================================================================================
+4. TESTS  (new "Module 24: LLM provider routing", ~12 tests, ~200 lines)
+================================================================================
+Reuse _StubLLM; new _FakeAnthropic (fake messages.create returning a stub
+response object) injected as client._client.
+
+ 1. app_config: anthropic block parses/validates/defaults empty.
+ 2. app_config: llm routing block - valid map round-trips; unknown consumer
+    key, unknown provider name, non-dict -> AppConfigError; absent -> {}.
+ 3. anthropic_api_key resolves env -> config.json -> empty.
+ 4. Base contract on BOTH subclasses (parametrized): keyless/disabled -> no
+    call; daily cap blocks + UTC-roll reset; failure stamps last_error,
+    success stamps last_ok.
+ 5. AnthropicClient parse: clean JSON -> dict; ```json-fenced -> dict;
+    non-JSON -> None; stop_reason "refusal" -> None; no text block -> None.
+ 6. AnthropicClient request shape: NO temperature key, max_retries=0,
+    cache_control present on system block (assert on captured kwargs).
+ 7. AnthropicClient with `anthropic` package missing (simulated) ->
+    available False, chat_json None, no crash at import.
+ 8. Routing: no llm block -> both consumers get the SAME DeepSeek singleton
+    (shared cap); routed config -> news gets DeepSeekClient while
+    agent_panel gets AnthropicClient; same-provider consumers share one
+    instance.
+ 9. Global lc._client override shadows BOTH consumers (locks the 41 legacy
+    stub sites' semantics).
+10. reset_llm_client() clears both the override and the per-provider cache.
+11. End-to-end: routing agent_panel->anthropic, attach_panel reaches the
+    anthropic fake (5 calls) while a news call reaches the deepseek stub.
+12. telegram _news_health_lines renders per-provider lines from usage()
+    without touching private fields.
+
+GATE: Modules 19 and 23 must pass UNMODIFIED - the no-regression proof for
+the refactor.
+
+================================================================================
+5. DOCS
+================================================================================
+- CLAUDE.md: llm_client bullet -> provider-abstracted (BaseLLMClient;
+  deepseek + anthropic registered); config.json "llm" block routes consumers;
+  absent = all-DeepSeek. Add ANTHROPIC_API_KEY to env-var list. Test counts.
+- config.json.example: both new blocks.
+
+================================================================================
+COMMIT SEQUENCE  (each commit green)
+================================================================================
+1. llm_client: extract BaseLLMClient; DeepSeekClient unchanged behavior
+   (+ base-contract tests)  - pure refactor, Modules 19/23 green untouched.
+2. config: anthropic block + llm consumer-routing block (+ config tests).
+3. llm_client: AnthropicClient (official SDK, lazy import) + requirements.txt
+   (+ parse/shape tests).
+4. routing: per-consumer get_llm_client + health lines - consumer call-site
+   edits, telegram usage() lines, routing/e2e tests.
+5. docs: CLAUDE.md + example config.
+
+================================================================================
+VERIFICATION
+================================================================================
+- python test_all.py green at every commit (~374 -> ~386).
+- Live smoke A (no behavior change): default config, main.py --panel ->
+  still DeepSeek, /status unchanged.
+- Live smoke B (the goal): llm.agent_panel="anthropic" + real
+  ANTHROPIC_API_KEY, run --panel -> one real Claude panel (5 requests,
+  validates JSON contract + latency + refusal-free path) while a news
+  refresh still hits DeepSeek; /status shows two provider lines.
+- Backtest untouched by construction (no LLM in replay path); one 30-day
+  run as a formality.
+
+================================================================================
+EFFORT ESTIMATE
+================================================================================
+0 new files, 8 modified, ~520 lines, est. 3-5 hours.
+
+  llm_client.py        base class + AnthropicClient + routing   +235
+  test_all.py          Module 24                                +200
+  app_config.py        anthropic + llm blocks, resolver          +55
+  telegram_bot.py      per-provider health lines                 +15
+  news_engine.py       consumer tags on call sites                +4
+  agent_panel.py       consumer tags on call sites                +4
+  config.json.example  blocks                                    +14
+  requirements.txt     anthropic                                  +1
+  CLAUDE.md            docs                                      +10
+
+================================================================================
+KEY DECISIONS EMBEDDED IN THIS PLAN
+================================================================================
+- Official Anthropic SDK, not raw requests (current API guidance for Python;
+  lazy import keeps it optional for DeepSeek-only installs).
+- Default Claude model: claude-opus-5 ($5/$25 per MTok; a full 5-call panel
+  ~ 8k in / 500 out ~ $0.05). Config-overridable to claude-haiku-4-5.
+- Two Claude gotchas handled: temperature is REMOVED on Opus 5 (sending it
+  400s - must not be copied from the DeepSeek request body), and refusals
+  arrive as HTTP 200 with stop_reason "refusal" (checked before parsing,
+  mapped to the normal None/fallback path).
+- Caps are per-provider, not per-consumer: two consumers on one provider
+  share its cap (today's semantics); splitting across two providers doubles
+  total headroom naturally.
+- The panel's own max_panels_per_day budget is untouched - it sits above
+  whichever provider serves it.
+- Not in scope: static/news_summary.php (own PHP client/key), streaming,
+  tool use, per-consumer model overrides (add a "model" key per consumer
+  later if ever needed).
+================================================================================

news_engine.py

@@ -770,8 +770,8 @@ class NewsEngine:
                         pub_date_el.text if pub_date_el is not None else None
                     )
 
-                    # Only recent headlines (last 24h)
-                    if pub_date and (datetime.now(timezone.utc) - pub_date).total_seconds() > 86400:
+                    # Only recent headlines (configurable: headline_max_age_seconds)
+                    if pub_date and (datetime.now(timezone.utc) - pub_date).total_seconds() > self.config.headline_max_age_seconds:
                         continue
 
                     # Dedup within and across feeds so a syndicated story

static/dashboard.html

@@ -630,6 +630,7 @@ const IND_SHORT = {ema_trend:"EMA", rsi:"RSI", macd:"MACD", bollinger:"BB",
 const ARROW = {STRONG_BUY:"⇈", BUY:"↑", NEUTRAL:"→", SELL:"↓", STRONG_SELL:"⇊"};
 const TF_LABEL = {"5min":"M5", "15min":"M15", "1h":"H1", "4h":"H4"};
 const TF_ORDER = ["5min","15min","1h","4h"];
+const TF_SECONDS = {"5min": 300, "15min": 900, "1h": 3600, "4h": 14400};
 /* 5 s polling is cheap because fetchJSON uses conditional GETs — Apache
    answers unchanged files with 304, so most polls transfer no body. */
 const POLL_MS = 5000;
@@ -783,7 +784,8 @@ function renderCards() {
     const foot = `<div class="tf-foot">
       <span>${entry.scanned_at ? "scanned " + fmtAge(entry.scanned_at) : ""}</span>
       <span class="cd">closes in
-        <span class="num" data-close="${entry.next_close_epoch || ""}">--:--</span></span></div>`;
+        <span class="num" data-close="${entry.next_close_epoch || ""}"
+          data-interval="${TF_SECONDS[tf]}">--:--</span></span></div>`;
     if (!r) {
       return `${open}<div class="tf-head"><span class="tf-name">${TF_LABEL[tf]}</span>
         <span class="spacer"></span><span class="open-hint">details ›</span></div>
@@ -1021,7 +1023,8 @@ function renderDetail() {
   $("detail-title").textContent = TF_LABEL[detailTf] || detailTf;
   $("detail-price").textContent = r?.current_price ? fmt$(r.current_price) : "—";
   $("detail-sub").innerHTML = `${snapshot?.symbol ? esc(snapshot.symbol) + " · " : ""}closes in
-    <span class="num" data-close="${entry.next_close_epoch || ""}">--:--</span>`;
+    <span class="num" data-close="${entry.next_close_epoch || ""}"
+      data-interval="${TF_SECONDS[detailTf]}">--:--</span>`;
   $("detail-body").innerHTML = detailHTML(detailTf);
 
   dlg.querySelectorAll("details[data-dkey]").forEach(d => {
@@ -1160,8 +1163,12 @@ function renderWire() {
   };
   const head = items.slice(0, 12).map(item).join("");
   const rest = items.slice(12);
+  /* preserve the disclosure across poll re-renders — otherwise an expanded
+     list snaps shut within one poll cycle (renderDetail does the same via
+     data-dkey; there is only one of these, so a class lookup suffices) */
+  const moreOpen = $("wire").querySelector("details.more")?.open ?? false;
   $("wire").innerHTML = head + (rest.length
-    ? `<details class="more" style="padding-top:6px"><summary>${rest.length} more headlines…</summary>
+    ? `<details class="more" style="padding-top:6px"${moreOpen ? " open" : ""}><summary>${rest.length} more headlines…</summary>
        <div class="wire">${rest.map(item).join("")}</div></details>` : "");
 }
 
@@ -1342,37 +1349,55 @@ wireNewsOpeners($("cal-body"), "data-ev-key", openCalDetail);
 async function fetchJSON(name) {
   /* no-cache = revalidate with the server every time (If-Modified-Since);
      unchanged files come back 304 with no body, so aggressive polling
-     stays nearly free. */
+     stays nearly free. Returns raw TEXT, not parsed JSON: a 304 is
+     transparent to fetch (the browser answers with the cached body and a
+     200), so poll() detects "unchanged" by comparing the payload itself
+     and skips the DOM rebuild entirely. */
   const res = await fetch(name, {cache: "no-cache"});
   if (!res.ok) throw new Error(`${name}: HTTP ${res.status}`);
   /* The Date header is stamped at RESPONSE time — snapshot.server_time_epoch
      is stamped at publish time, minutes stale between candle closes. */
   const dateHdr = res.headers.get("Date");
-  const data = await res.json();
-  return {data, serverNow: dateHdr ? Date.parse(dateHdr) / 1000 : null};
+  const text = await res.text();
+  return {text, serverNow: dateHdr ? Date.parse(dateHdr) / 1000 : null};
 }
 
 let refetchTimer = null;
+let lastSnapText = null, lastNewsText = null;   // change detection for the render-skip below
 async function poll() {
   try {
     const [snap, nw] = await Promise.all([
       fetchJSON("snapshot.json"),
       fetchJSON("news.json").catch(() => null),  // news outage ≠ page failure
     ]);
-    snapshot = snap.data;
-    news = (nw && nw.data) || news;
-    clockOffset = (snap.serverNow ?? snap.data.server_time_epoch) - Date.now() / 1000;
+    const snapChanged = snap.text !== lastSnapText;
+    const newsChanged = nw != null && nw.text !== lastNewsText;
+    if (snapChanged) { snapshot = JSON.parse(snap.text); lastSnapText = snap.text; }
+    if (newsChanged) { news = JSON.parse(nw.text); lastNewsText = nw.text; }
+    clockOffset = (snap.serverNow ?? snapshot.server_time_epoch) - Date.now() / 1000;
     lastPollOk = new Date();
     $("banner-fail").style.display = "none";
-    renderHero(); renderContext(); renderCards(); renderCalendar(); renderWire();
+    /* re-render only what new data can actually change — an unchanged
+       payload keeps the existing DOM (selection, disclosure state, scroll)
+       intact; countdowns and the freshness line tick from it regardless.
+       Trade-off: "Xm ago" ages in the wire/calendar only advance when the
+       payload changes. */
+    if (snapChanged) {
+      renderHero(); renderCards();
       renderDetail();   // keep an open detail view in sync with the new scan
+    }
+    if (newsChanged) {
+      renderCalendar(); renderWire();
       renderNewsDlg();  // same for an open news/calendar dialog
+    }
+    if (snapChanged || newsChanged) renderContext();   // blurb reads news, risk chip reads snapshot
     tick();  // countdowns appear immediately, not after the first 1 s tick
 
     /* one-shot refetch shortly after the next expected publish, so a
        fast scan appears ~2 s after the publisher wakes instead of
        waiting out the poll interval (the regular POLL_MS loop covers
        slower scans) */
+    if (snapChanged) {
       const nextScan = Math.min(...TF_ORDER.map(tf =>
         snapshot.timeframes[tf]?.next_scan_epoch || Infinity));
       if (isFinite(nextScan)) {
@@ -1380,6 +1405,7 @@ async function poll() {
         const delay = (nextScan - nowServer() + 2) * 1000;
         if (delay > 0) refetchTimer = setTimeout(poll, delay);
       }
+    }
   } catch (err) {
     const last = lastPollOk ? ` Last update ${lastPollOk.toLocaleTimeString()}.` : "";
     const b = $("banner-fail");
@@ -1388,28 +1414,46 @@ async function poll() {
   }
 }
 
-/* 1 s countdown ticker (server-clock anchored) */
+/* 1 s countdown ticker (server-clock anchored). The wrap interval comes
+   from data-interval stamped at render time — reverse-looking the epoch up
+   in snapshot.timeframes mis-resolves shared boundaries (M5/M15/H1 all
+   close on the hour) to the first matching TF in TF_ORDER. */
 function tick() {
   if (!snapshot) return;
   const now = nowServer();
   document.querySelectorAll("[data-close]").forEach(el => {
-    let t = parseFloat(el.dataset.close);
+    const t = parseFloat(el.dataset.close);
     if (!t) return;
-    const tf = TF_ORDER.find(k => snapshot.timeframes[k]?.next_close_epoch === parseFloat(el.dataset.close));
     let secs = t - now;
     if (secs < 0) {  // boundary passed while waiting for next publish
-      const interval = {"5min": 300, "15min": 900, "1h": 3600, "4h": 14400}[tf] || 300;
-      secs = ((secs % interval) + interval) % interval;
+      const interval = parseFloat(el.dataset.interval);
+      /* one-shot countdowns (calendar releases) carry no data-interval:
+         clamp at zero until the next poll re-renders them as "released …" */
+      secs = interval > 0 ? ((secs % interval) + interval) % interval : 0;
     }
     el.textContent = fmtCountdown(secs);
   });
   const m5 = snapshot.timeframes["5min"]?.next_close_epoch;
   if (m5) {
     let secs = m5 - now;
-    if (secs < 0) secs = ((secs % 300) + 300) % 300;
+    if (secs < 0) secs = ((secs % TF_SECONDS["5min"]) + TF_SECONDS["5min"]) % TF_SECONDS["5min"];
     $("hero-cd").textContent = fmtCountdown(secs);
   }
-  if (lastPollOk) $("hero-updated").textContent = `updated ${fmtAge(lastPollOk.toISOString())}`;
+  /* publish-time freshness, not poll health — a dead publisher behind a
+     healthy Apache would otherwise read as "updated just now" forever */
+  const pubEpoch = snapshot.server_time_epoch;
+  if (pubEpoch) {
+    const age = now - pubEpoch;
+    const el = $("hero-updated");
+    /* M5 publishes every 5 min while the market is open, so anything older
+       than 15 min means the pipeline is down, not between scans. The
+       weekend case is already covered by the market-closed banner. */
+    const stale = !snapshot.market_closed && age > 900;
+    el.textContent = (stale ? "STALE — published " : "published ") +
+      fmtAge(new Date(pubEpoch * 1000).toISOString());
+    el.style.color = stale ? "var(--amber)" : "";
+    el.style.fontWeight = stale ? "600" : "";
+  }
 }
 setInterval(tick, 1000);