remove the AI market-outlook feature (delivery-side only; books byte-identical)

Owner decision 2026-09-15. Gone: market_outlook.py, the post-H1-scan Telegram
outlook DM, main.py --outlook, the outlooks table DDL/migration/writer in
signal_log.py, the market_outlook config block + MARKET_OUTLOOK_ENABLED, and
test Module 26. Last commit containing the feature: 2836024.

- app_config: "market_outlook" stays in _KNOWN_TOP as a TOLERATED, ignored
  legacy key (oanda.account_id precedent) with one warning, so a live
  config.json that still carries the block keeps booting.
- signal_log: existing DBs keep their orphan outlooks table and rows (no
  DROP TABLE); fresh DBs never create it.
- tests: Module 26's 4-thread concurrent legacy-DB migration test (the
  suite's only one) moved to Module 31; new test for the tolerated block.
  519 -> 509 tests, 34 -> 33 modules, 0 failed.
- docs: CLAUDE.md usage/config/file-map lines and a dated state note.

Verification: W2 books (2024-09-05 -> 2026-09-05, $0.65, NumPy CPU, 0 cache
fallbacks) byte-identical before/after — M5 29120a1ee32979431d062f210d41a9d1
(781 / +146.07R / PF 1.52), M15 d185f099482a07f29502cb5a371a9bbf
(931 / +146.14R / PF 1.43).

Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>

CLAUDE.md

@@ -12,11 +12,10 @@ Every numeric threshold in `config.py` and `pair_signals/xauusd.py` was backtest
 
 ```bash
 python test_all.py                      # QA suite, no network (mocked); prints its own count
-                                        #  (519 tests / 34 modules as of 2026-09-13)
+                                        #  (509 tests / 33 modules as of 2026-09-15)
 python main.py --pair XAUUSD --timeframe H1 --detail   # CLI signal report (--json for full dump,
-                                        #  --panel for the advisory LLM agent panel, --outlook for the
-                                        #  hourly AI market brief; the violent-move watch line appears
-                                        #  when the `violent_watch` config block is enabled;
+                                        #  --panel for the advisory LLM agent panel; the violent-move watch
+                                        #  line appears when the `violent_watch` config block is enabled;
                                         #  --timeframe accepts M5/M15/H1/H4 only and the confirmation
                                         #  TFs always come from the pair factory's map)
 python telegram_bot.py                  # the bot (refuses to boot without credentials)
@@ -45,7 +44,7 @@ Python 3.12; a `venv/` exists in-repo. Dependencies in `requirements.txt` (numpy
 
 ## Configuration & credentials
 
-Precedence for every credential/deployment setting: **env var → config.json → refuse to run** (no hardcoded fallbacks). A gitignored repo-root `.env` is loaded at `app_config` import via `os.environ.setdefault`. `config.json` (gitignored; schema in `config.json.example`) holds secrets plus deployment settings: `data_providers.active` (the live-feed switch), `data_providers.streaming` (optional tick-stream provider for the level-breach monitor), `scanning.pairs`/`timeframes`, per-pair `blocked_hours_utc`, `log_level`. Key env vars: `TELEGRAM_TOKEN`, `TELEGRAM_CHAT_ID`, `TELEGRAM_CHANNEL_ID`, `TWELVE_DATA_API_KEY`, `TIINGO_API_KEY`, `OANDA_API_TOKEN`/`OANDA_BASE_URL` (the data feed needs no account id; a legacy `oanda.account_id` key is tolerated and ignored), `DEEPSEEK_API_KEY` (news LLM; the `deepseek` config.json block holds model/enabled/timeout/daily cap). The `news_archive` block (`enabled` default TRUE, `path` default `logs/newsdata.db`; env `NEWS_ARCHIVE_ENABLED`/`NEWS_ARCHIVE_PATH`) controls the durable headline corpus. The `agent_panel` config.json block (all-defaults = feature dark) controls the advisory LLM agent panel: `enabled`, per-surface `telegram`/`dashboard` toggles, `min_quality`, `max_panels_per_day`, `reuse_ttl_seconds`, plus the technical-payload enrichment knobs `candles_enabled`/`candle_bars_primary`/`candle_bars_confirm`. The dark-by-default `market_outlook` block controls the hourly advisory market brief: `enabled`, `telegram`, `max_per_day`, `candles_bars`; `MARKET_OUTLOOK_ENABLED` overrides its enabled setting. The dark-by-default `violent_watch` block controls the display-only violent-move watch: `enabled`, `alert_line`, `headsup`, `max_headsup_per_day`, `headsup_min_level` (`"watch"`/`"hot"`); `VIOLENT_WATCH_ENABLED` overrides its enabled setting.
+Precedence for every credential/deployment setting: **env var → config.json → refuse to run** (no hardcoded fallbacks). A gitignored repo-root `.env` is loaded at `app_config` import via `os.environ.setdefault`. `config.json` (gitignored; schema in `config.json.example`) holds secrets plus deployment settings: `data_providers.active` (the live-feed switch), `data_providers.streaming` (optional tick-stream provider for the level-breach monitor), `scanning.pairs`/`timeframes`, per-pair `blocked_hours_utc`, `log_level`. Key env vars: `TELEGRAM_TOKEN`, `TELEGRAM_CHAT_ID`, `TELEGRAM_CHANNEL_ID`, `TWELVE_DATA_API_KEY`, `TIINGO_API_KEY`, `OANDA_API_TOKEN`/`OANDA_BASE_URL` (the data feed needs no account id; a legacy `oanda.account_id` key is tolerated and ignored; so is a legacy top-level `market_outlook` block, with one warning — feature removed 2026-09-15), `DEEPSEEK_API_KEY` (news LLM; the `deepseek` config.json block holds model/enabled/timeout/daily cap). The `news_archive` block (`enabled` default TRUE, `path` default `logs/newsdata.db`; env `NEWS_ARCHIVE_ENABLED`/`NEWS_ARCHIVE_PATH`) controls the durable headline corpus. The `agent_panel` config.json block (all-defaults = feature dark) controls the advisory LLM agent panel: `enabled`, per-surface `telegram`/`dashboard` toggles, `min_quality`, `max_panels_per_day`, `reuse_ttl_seconds`, plus the technical-payload enrichment knobs `candles_enabled`/`candle_bars_primary`/`candle_bars_confirm`. The dark-by-default `violent_watch` block controls the display-only violent-move watch: `enabled`, `alert_line`, `headsup`, `max_headsup_per_day`, `headsup_min_level` (`"watch"`/`"hot"`); `VIOLENT_WATCH_ENABLED` overrides its enabled setting.
 
 ## Architecture
 
@@ -73,7 +72,6 @@ Signal currency everywhere is `SignalStrength` (−2..+2). DataFrames are UTC tz
 - **`news_engine.py`** — Forex Factory calendar (MyFXBook RSS fallback) + RSS keyword sentiment with gold-inverse keywords. Class-level caches (fresh engine per scan). Optional DeepSeek enrichment via `llm_client.py` (requests-only, no SDK): batched headline sentiment overriding keyword scores, gold-direction on release surprises, and a market-summary blurb (`SignalReport.news_summary`) — **display/warning-only, keyword fallback on any failure, inert without a key**; prompts are static module constants (DeepSeek prefix-cache pricing) and requests send `thinking: disabled` (V4-Flash reasoning otherwise blows the timeout). By XAU-tuned default, event risk and sentiment **warn but do not gate signals** (`event_risk_caps_signals=False`, `sentiment_affects_signals=False`) — the LLM does not change that. **Headline pool (2026-09-04):** only headlines ≤ 4 h old with a parsable publish time (`headline_max_age_seconds=14400`, undated items dropped), and `get_fundamental_context` drops headlines whose every relevant score is inside ±0.1 (`_is_neutral_headline`, `NEUTRAL_HEADLINE_THRESHOLD`) before the per-currency mean — so `news_sentiment` from that date is a mean over directional headlines only (bolder values; log comparisons must split at the deploy date). The market summary prompt writes for someone who has never traded (no acronyms), sends headlines newest-first with the platform's own gold direction, and caps at 400 chars. **Verdict 2026-09-04** (`backtest/research/news_sentiment_value_2026-09-04.md`): `news_sentiment` is a trailing-24h echo of price (r≈0.67 with the past day, ≈0.03 with the next; flips 44 h after tops / 16 h after bottoms) — both gating flags stay False; re-check with `analyze_signal_log.py --stored-candles --news`.
 - **`news_archive.py`** — durable headline corpus in its OWN database (`logs/newsdata.db`), separate from `signals.db` so a signal-log rotation cannot take the news with it (that is exactly how the 3-week corpus behind `news_sentiment_value_2026-09-04.md` was lost — 4,054 distinct headlines, unrecoverable, `logs/` is gitignored). One row per distinct headline keyed on `sha256(headline)`, carrying the text, description, link, publisher, publish time, the score, `score_source` (`keyword`/`llm`/`model` — a new `NewsSentiment` field, also mirrored into `signal_log._headline_to_dict`), and `teacher_model`/`teacher_prompt_sha1` so labels made under a changed prompt are never pooled with older ones. **Writes are one atomic UPSERT per row and upgrade-only**: an `llm` score always replaces a `keyword` one (the >25/cycle batch-overflow tail gets its DeepSeek label on the next fetch window in a long-running process — verified: 13/13 upgraded) but a `keyword` score can never overwrite an `llm` one; re-seeing a headline always bumps `seen_count`. A read-then-write pair loses increments when the bot, the dashboard publisher and the tests first see a headline together, and the WAL switch itself needs `_with_lock_retry` — both are regression-tested with 3 concurrent writers. Hooked at the END of `news_engine._fetch_news_sentiment_raw`, **before** `_is_neutral_headline` runs in `get_fundamental_context`: archiving downstream of that ±0.1 filter is why `signals.db` holds almost no neutral headlines and would teach a trained scorer that "neutral" barely exists. Never raises (fail-safe by contract, like `signal_log`). The backtester never builds a `NewsEngine`, so replays never archive (test-locked). Seeded by `scripts/backfill_news_archive.py`, which reads both DB shapes read-only and **recomputes** provenance (stored score vs the keyword scorer: differs → `llm`, exact non-zero match → `keyword`, both zero → `unknown`) because neither source recorded it. Purpose: training data for a local numpy-only headline scorer to replace the 24/78 keyword fallback — see the note below.
 - **`agent_panel.py`** — ai-hedge-fund-style advisory panel: 4 DeepSeek persona calls (macro/technical/risk/contrarian, concurrent on a panel-private pool) + 1 synthesizer producing an **ADVISORY-ONLY** consensus (`AGREE/NEUTRAL/OPPOSE` + confidence + rationale) written onto `SignalReport.panel_*` fields. Attached **post-hoc** by consumers (`telegram_bot` alert path, `main --panel`, `dashboard_publisher`) — never runs inside `analyze_from_dataframes` (backtest parity, test-locked) and no gate reads its fields. Persona payloads are role-filtered: macro gets high-impact events plus only code-scored directional news; technical gets strategy/pattern, primary indicators, MTF, levels, and ATR-normalized candles; risk gets setup strategy, strategy cost assumption, trailing semantics, volatility/events/warnings (never the median candle range as spread); contrarian gets directional news, setup, timestamped latest-closed price, indicators, reasons, and warnings. Spend is bounded by exact cache, full-evidence-identity TTL reuse, and `max_panels_per_day`; changed evidence never inherits a direction-only cached verdict (test-locked — which also means TTL reuse effectively never fires live because price/candles change every bar; the daily cap is the real spend bound). Verdict provenance logs creation time, `MISS`/`EXACT_HIT`/`TTL_REUSE`, and a SHA-256 payload hash. Prompts forbid outside knowledge and outputs remain short. **OPPOSE guard (2026-09):** the 3-week signal-log scorecard showed the contrarian/risk/technical personas oppose almost every trend entry (chair said OPPOSE 73% of the time; opposed trades made +30R, PF 2.6) while the macro persona was the only informative voice (macro=support → 88% win). `_apply_oppose_guard` therefore downgrades a chair OPPOSE to NEUTRAL unless macro opposes, or technical opposes while macro is not supportive; the synthesizer prompt states the same rule. Re-score with `analyze_signal_log.py --stored-candles` (persona scorecard) before changing it again. **Verdict source (2026-09-03, owner decision):** all four personas still run and are logged (`panel_takes_json`), but `agent_panel.verdict_source` defaults to `"macro"` — the alert verdict is the macro persona's stance (support/neutral/oppose → AGREE/NEUTRAL/OPPOSE) and the synthesizer call is skipped (4 LLM calls per panel instead of 5); `"chair"` restores the four-voice synthesizer + OPPOSE guard. Re-score personas monthly with `analyze_signal_log.py --stored-candles`; weights are not to be tuned before ~300 graded outcomes with a held-out half.
-- **`market_outlook.py`** — hourly DeepSeek market brief for XAU/USD, using ATR-normalized M15/H1/H4 candles, visible indicator states, levels, news, and recent signal history (read `mode=ro`). It returns a written **ADVISORY-ONLY** bias/setup-forming assessment and persists it independently in `outlooks` within `logs/signals.db` together with the news, indicator/regime/level, and candle evidence sent to the model. It may be sent post-scan by Telegram or requested with `main.py --outlook`; it never imports or runs inside the signal path. Hourly dedup is by UTC hour BUCKET (the old `now − last < 3600` rule dropped every other hour because the H1 loop fires at boundary+10 s+scan time) plus its own UTC-day cap (default 12); every silent early return logs `market outlook: skipped (...)` and an empty LLM reply logs a warning — a dark feature must be visible in `logs/telegram.log`. Provider/news failures leave a safe partial brief while LLM/database failures degrade to no outlook.
 - **`violent_watch.py`** — **display-only** violent-move watch, dark by default (`violent_watch` config block: `enabled`, `alert_line`, `headsup`, `max_headsup_per_day`, `headsup_min_level`; env `VIOLENT_WATCH_ENABLED`). Flags when a "violent bar" (range ≥ 3× prior ATR14) is unusually likely and stamps `SignalReport.watch_line` **post-hoc** via `attach_watch` (telegram alert path, `main.py`, `dashboard_publisher`) — same contract as the agent panel: never imported by `signal_aggregator`/`engine`/`backtest/`, never raises, never read by a gate (test-locked, Module 30). Triggers: a high-impact **USD** calendar release within ±30 min (hot), hot clock slots (weekday 12–14 UTC, weekday 01 UTC, Sunday reopen 22–23 UTC), and **price-extreme** indicator readings (outside the Bollinger bands, RSI <30 / ≥70, outside the Keltner channel). Level = hot when the calendar fires or a clock slot plus ≥1 price extreme; watch on a clock slot alone or ≥2 price extremes. Context readings (ADX slope >3, volatility "extreme", regime "transitioning", MACD STRONG_BUY/STRONG_SELL) are printed but **never raise the level** — the first draft that let them count flagged 27% of bars "hot" at only ~2× odds; the shipped rule flags 8.6% at 3–5× (evidence: `backtest/research/sizing_campaign_2026-09.md` addenda). Direction is called DOWN on bearish readings (70–78% on M5 and M15) and UP only on M5. Telegram also sends a standalone heads-up on the fastest scanned TF (`_HEADSUP_TF`), rate-limited per UTC hour+trigger-set and per day; it explicitly tells the owner **not** to touch open trades — every protection tested lost money, the stop is the protection.
 - **`telegram_bot.py`** — owner-locked bot + subscriber channel; candle-boundary auto-scan loops (M5/M15/H1/H4, boundary+10 s), alert quality threshold + fingerprint dedup (committed only after a successful send; the fingerprint is signal+direction — grade is NOT part of it, a grade UPGRADE re-alerts, an A↔B flicker does not), 📰 LLM market-context line on alerts when available, WebSocket level-breach monitor fed by the streaming provider (`data_providers.streaming`, falling back to the active provider; auto-disabled when the resolved provider can't stream or has no API key — Oanda does not stream, Tiingo does). The breach handler reuses this bar's M15 report (`_cached_or_scan`, keyed by closed-bar epoch) instead of rescanning — it used to log 3.5 M15 rows per candle. **Alerts require a trade setup (2026-09-08):** `_is_alert_candidate` (shared by the scan and breach paths) needs non-neutral + grade ≥ threshold + `trade_setup`; a signal every generator declined used to go out anyway (a B-grade no-setup SELL under a "costs would eat the edge" warning). **Sends are logged:** every delivered alert / breach alert / violent-move heads-up writes an `… sent:` INFO line carrying the signal-log row id, and a no-setup candidate writes `alert skipped: … (gate reason)` — before this only failures were logged and a review had to reconstruct sends from panel rows. Rotating log: `logs/telegram.log`, one file per server-local day × 30 backups (was 3-h × 240 until 2026-09-08; the old `_HH`-suffixed files on the live box are not matched by the daily cleanup and need one manual delete).
 - **`dashboard_publisher.py` / `static/dashboard.html`** — web dashboard as a **static publisher** (live LAMP server): standalone daemon scans at candle closes via `produce_signal` and atomically writes `snapshot.json`/`news.json`/`dashboard.html` to `$DASHBOARD_OUT_DIR` (Apache serves them; page is public by owner decision). **Hard independence rule: never imports, and is never imported by, `telegram_bot`** — confirmation map and boundary math are deliberate local copies, so a web-side failure can only mean a stale page. Due-TF classification uses the RAW wake time (flooring wake−buffer skips every H1/H4 scan — 2026-08-02 bug). News panel reads `NewsEngine.get_fundamental_context()` plus the additive `get_week_events()` accessor (display-only; no signal path calls it); as a separate process it has its own news caches and DeepSeek daily cap. News/calendar rows are clickable (detail dialog); headlines carry `id` = sha1(headline) in news.json, and exactly one on-demand endpoint exists: `static/news_summary.php` (installed by `install_static`), which serves a DeepSeek gold-impact summary per headline — whitelist-gated against news.json ids, cache-forever in `ai/`, own fail-closed daily cap (150/day, file-based, separate from the publisher's), key at `/etc/gold-dashboard/deepseek.key`, never reads repo config. Deployment checklist: `deploy/README-dashboard.md`.
@@ -116,3 +114,4 @@ Signal currency everywhere is `SignalStrength` (−2..+2). DataFrames are UTC tz
 - 2026-09-09 weight-change test (`backtest/research/weight_test_2026-09-09.md`, first use of the recorded replay files): a drift-adjusted per-bar screen ranked 108 regime-multiplier candidates per TF; the top 3 per TF (24 h-sign filter) went through the full 2-year replay against same-harness controls plus the 2024-06→2025-03 OOS window under a rule pre-registered before any run. M5: all three MACD candidates FAIL (−10 to −46R; the screen ranked them first — never trust the per-bar screen on M5 without a replay). M15: ema_trend × 2 FAILS (PF 1.32, DD 26R, +55% trades), divergence → 0 in trending FAILS (H1 −3R, DD); **RSI multiplier × 0.5 in every regime PASSES a–f** (2-yr 793/+117.6R/PF 1.41 → 931/+146.1R/PF 1.43, halves +27.9/+0.6, OOS +40.6 → +60.7R PF 1.49, 3-yr +151.9 → +186.6R PF 1.39 but max DD 15.5 → 19.3R and 2026 −4R; added trades are mostly B-grade BUYs). SHIPPED the same day on the owner's decision as an M15-only `technical.regime_weights_override` in `pair_signals/xauusd.py` (M15 override 5: the shipped table with RSI halved in every regime — 0.5 trending family / 0.75 ranging / 0.5 transitioning; derived from the default table, pinned literally by the Module 9 equivalence test) — the factory run without `--set` reproduces the validated candidate book byte-for-byte (parity MD5 in `weight_test_2026-09-09.md`); M15 canonical book re-pinned to `backtest/oanda_m15_2yr_065_20260909.csv`. Live M15 `engine_fingerprint` changes from that deploy; signal-log comparisons across it must split at the deploy time. Suite 499 tests.
 - 2026-09-10 improvement cycle 1 (`backtest/research/cycle_2026-09-10.md`; 501 tests; no signal-core change): HEAD baseline re-established on the 3-yr window at $0.65 (M5 870/+153.6R/PF 1.50, M15 1273/+186.6/1.39, H1 253/+70.0/1.98, H4 114/+21.7/1.59) and the three pinned MD5s (M5 2-yr, M15 2-yr, M15 OOS) reproduced exactly. Robustness: the cost ladder trips no red flag (every TF keeps PF ≥ 1.3 with positive halves at $0.80; at $1.30 M5 PF 1.36, M15 1.29, H1 1.89, H4 1.53); the intraday edge is a fat right tail (top 5% of trades carry 94% of M5 R and 96% of M15 R, versus 48% on H1; M5 2024 was flat at +1.0R over 102 trades). Pre-registered bucket screen: exactly one qualifying bucket — M15 grade-A SELLs (230 / −14.4R, negative in all three years and OOS; the 2026-09-03 5-yr run said the opposite) — parked as the only cycle-2 candidate. **C1 REJECTED:** H1 divergence multiplier → 0 in every regime (the parked 2026-09 candidate on its now-sanctioned vehicle): 3-yr ΔR +1.0, second half −1.5R, PF 1.98 → 1.89 (its OOS book 88/+21.9/PF 1.92 is trade-identical to the old `disabled_indicators` run, so a 0.0 regime multiplier ≡ disabling for the composite). **C2:** the M15 RSI × 0.5 ship sits on a stable plateau (k = 0.25 / 0.75 keep 78% / 71% of its 2-yr gain, both OOS-positive; R is monotone in k across 0…1.5) — no other k proposed. **Seeding parity SHIPPED:** live fetches floor at `MIN_LIVE_BARS = 1000` (H4 380 → 1000, D1 300 → 1000; measured ema_trend flips 2/267 H4 and 1/313 D1 bars at the old depths, none ≥ 600; the live D1 bar of 2026-09-10 itself read SELL at 300 bars and NEUTRAL at 1000/5000) and the backtester pad targets the same depth (`_history_pad_days`: 62 / 234 / 1400 days) — M5/M15 3-yr books byte-identical, H1/H4 trade-identical with only window-start float noise in the exported columns, so no re-pin. Also fixed in these notes: no PDF docs exist; `pyarrow` is a dev-venv-only dependency of the backtester/recorder.
 - 2026-09-13 bug audit (plan file `~/.claude/plans/you-are-python-software-joyful-teacup.md`; 519 tests / 34 modules; the five reference books — M5 W2 `29120a1ee32979431d062f210d41a9d1`, M15 W2 `d185f099482a07f29502cb5a371a9bbf`, M15 OOS `6f8f24b49597ced28f50a19e08c3472f`, H1 W3 `3b45d12bade823178b267c13bc698458`, H4 W3 `e75adae13c839b15736f69c0114e6aa5` (the H1/H4 values are the post-pad books, `cycle_2026-09-10/w3_{1h,4h}_pad.csv`) — byte-identical before and after every change, 0 GPU cache fallbacks). Verified sound, no change: composite = Σwscore/Σeff_weight × 50 on 400/400 DB rows; scan-outcome labels reproduce later scan prices to 0.000 on 844 rows; outcome-model exits reproduced on rows 578/1372/1500; Oanda H4/D1 alignment is UTC; no look-ahead in engine/backtester/chart_patterns; no cross-bar state; parquet caches hold only holiday gaps. Fixed (all delivery/measurement side, books unchanged): (1) NEUTRAL-signal C/B setups now alert (see `_attach_core_setup`); (2) a missing confirmation frame fails the scan (`scan_kind='failed'`, warning `DATA UNAVAILABLE:`); (3) `pd.Timestamp.utcnow()` (deprecated, removed in pandas 4) replaced in `providers/base.py`/`engine.py`, `requirements.txt` pins `pandas<4`, `numpy<3`; (4) advisory outcomes keep locked-profit floors and the rebuild fires on both gap reasons; (5) scan-outcome labeler max-age/anchor bound; (6) the daily settlement pause (Mon–Thu 17:00 NY) is a scheduled closure for the freshness gates — `_is_daily_maintenance`/`_is_scheduled_closure`/`_scheduled_closed_seconds` in `providers/base.py`, the expected label walks back only past labels whose WHOLE span lies in a closure (a D1 bar labelled Sunday 00:00 UTC and an H4 bar labelled Sunday 20:00 exist), and the bot/dashboard skip scans whose just-closed label sits in the pause (61 false "stale" rows in 3 nights before); (7) `fetch_range` retries a failed page in place (3 failures on one window raise) and logs an ERROR for interior gaps of >3 unscheduled bars (holidays look identical — verify, never fatal); (8) `_replay_span` returns the per-span GPU cache-miss count, `run_backtest` sums/logs it (must be 0) and writes `cache_fallbacks` to the `--record` manifest; (9) `regime_weight_table` raises on a partial `regime_weights_override` (every regime × all nine indicators); (10) Telegram boundary loops go through `_cached_or_scan`, `_remember_scan` files a report under the bar it analysed (label + duration), a breach inside 20 s after an M15 boundary waits for the loop's scan (15 duplicate M15 rows in 5 days before), and the rotating file handler is attached in `main()` only (importing the module in tests wrote fixture alerts into `logs/telegram.log`); (11) dashboard `catch_up_timeframes` re-scans any TF whose newest closed boundary is newer than its last scanned one (missed while a cycle overran or the process was down). Semantics recorded, NOT changed (rule 1): `blocked_hours_utc` is applied to the bar LABEL hour in the core (6b) AND the bar CLOSE hour in the live wrapper/backtester, so H1 can only trade bars closing 04–09, 15, 18–20 UTC and H4 only bars closing 08:00/12:00 — parity holds and every book was validated that way. Post-deploy: `scripts/backfill_signal_outcomes.py --reseed-unresolvable` floors the two Sep-8 shorts on the live DB; the `--stored-candles` scorecard (`analyze_signal_log.replay_stored`) still calls `advance_outcome` without the floor step (owner decision pending).
+- 2026-09-15 market outlook REMOVED (owner decision; plan `~/.claude/plans/you-are-quant-software-logical-cake.md`): `market_outlook.py`, the post-H1-scan Telegram 🔭 DM, `main.py --outlook`, the `outlooks` table DDL/migration/writer in `signal_log.py`, the `market_outlook` config block + `MARKET_OUTLOOK_ENABLED`, and test Module 26 are gone; the last commit containing the feature is `2836024`. A legacy top-level `market_outlook` block in config.json is TOLERATED and ignored with one warning (kept in `_KNOWN_TOP`, the `oanda.account_id` precedent) so the live bot/dashboard keep booting — delete the block from the live config.json at deploy. Existing `logs/signals.db` files keep their orphan `outlooks` table and rows (nothing reads or drops it; drop by hand during a weekend VACUUM if wanted); fresh DBs never create it. Module 26's 4-thread concurrent legacy-DB migration test (the suite's only one) moved to Module 31. Nothing in the signal path changed: the W2 books (2024-09-05→2026-09-05, $0.65, NumPy CPU, 0 cache fallbacks) are byte-identical before/after — M5 `29120a1ee32979431d062f210d41a9d1` (781 / +146.07R / PF 1.52), M15 `d185f099482a07f29502cb5a371a9bbf` (931 / +146.14R / PF 1.43). Suite 509 tests / 33 modules.