chore: repo hygiene — stale gitignore entries, finished plans, superseded research, doc drift

Removed (all recoverable from git history):
- llm_provider_switch_plan.txt: 2026-08-08 DeepSeek/Anthropic multi-provider plan that
  was never implemented (llm_client.py is DeepSeek-only, no `anthropic` anywhere)
- docs/superpowers/specs/2026-07-21-centralized-config-design.md: spec of the
  config.json migration that merged the same day; its plan sibling was already
  deleted in b936d44. app_config's docstring pointer goes with it.
- scripts/compare_oanda_tiingo.py: Phase 0 recent-tail smoke test, superseded by the
  Phase 1/2 study scripts (result recorded in the test plan)
- backtest/research/fetch_oanda_m15.py + oanda_td_divergence.py + its by-hour CSV:
  the 2026-07-24 Oanda-vs-Twelve-Data study, superseded by the 2026-08-14 feed
  divergence report (which keeps a one-line citation)
- backtest/research/burst_profile.py and hour_analysis.py: superseded by burst_map.py
  and book_report.py
- backtest/research/panel_payload_drytest_2026-08-15.py: one-off live DeepSeek probe;
  its .jsonl evidence stays

Added to git: the three 2026-08-14 research reports (feed divergence, re-pin
verification, signal parity), their CSV, and docs/data_source_change_test_plan.md -
CLAUDE.md cites them as standing evidence and their driver scripts were already
committed. The test plan no longer refers to auto-execution.

Hygiene:
- .gitignore: drop oanda_state.json (daemon removed 2026-09-03) and the vanished
  backtest/trailgrid dirs; ignore .coverage
- docs/architecture_diagram.py only writes the PNG when run as a script (it used
  to plot on import); test box refreshed to 461 tests / 31 modules; PNG regenerated
  (the committed one still drew the removed daemon)
- backtest/instructions_for_backtest.txt: manual-journal head replaced by the
  actual reporting checklist; the 2026-09-06 addendum is unchanged
- doc drift: README/publisher list all six published files; news_summary.php says
  4 h (not 24 h) and drops the pre-id sha1 fallback whose window closed;
  analyze_signal_log lists six lenses and --scan-outcomes; agent_panel cost model
  says 4 requests by default; tiingo comment cites the NY-anchored weekend;
  Module 21 title no longer says "execution lifecycle"

Suite: 461 passed, 0 failed.

Claude-Session: https://claude.ai/code/session_0156YhogLytzj9P2iH1skGbL

scripts/compare_oanda_tiingo.py

@@ -1,116 +0,0 @@
-#!/usr/bin/env python3
-"""
-Scratchpad — Oanda vs Tiingo candle parity check
-=================================================
-Fetches the last N closed XAU/USD candles from Oanda and Tiingo for
-M5/M15/H1 via the normal provider stack (make_data_provider →
-fetch_ohlcv: forming-candle drop + validate/clean included, i.e. exactly
-what the signal pipeline consumes) and reports how well they line up:
-
-  * last-bar timestamp per provider (feed-lag check)
-  * timestamp mismatches (bars present in one feed only)
-  * per-bar OHLC diff table for the common tail
-  * max/mean |diff| per column, with the Close diff also in % of price
-
-Both feeds are mid-price (Oanda mid of MBA candles; Tiingo resampled
-mid), so small diffs are expected — this measures how small.
-
-Usage:
-    venv/bin/python scripts/compare_oanda_tiingo.py [--n 10]
-"""
-
-import argparse
-import sys
-from pathlib import Path
-
-import pandas as pd
-
-sys.path.insert(0, str(Path(__file__).resolve().parent.parent))
-
-from config import PlatformConfig, Timeframe, XAUUSD
-from providers import make_data_provider
-
-TIMEFRAMES = [Timeframe.M5, Timeframe.M15, Timeframe.H1]
-OHLC = ["Open", "High", "Low", "Close"]
-
-
-def fetch_tail(provider, tf, n):
-    """Last n closed bars from one provider, or None on failure."""
-    try:
-        df = provider.fetch_ohlcv(symbol=XAUUSD, timeframe=tf)
-    except Exception as e:  # scratchpad: report, don't crash
-        print(f"  !! {provider.name} {tf.value} fetch failed: {e}")
-        return None
-    return df.tail(n)
-
-
-def compare_tf(tf, oanda_df, tiingo_df, n):
-    print(f"\n{'=' * 78}\n{tf.value} — last {n} closed bars\n{'=' * 78}")
-    if oanda_df is None or tiingo_df is None:
-        print("  skipped (a provider failed)")
-        return
-
-    print(f"  Oanda last bar: {oanda_df.index[-1]}   "
-          f"Tiingo last bar: {tiingo_df.index[-1]}")
-
-    common = oanda_df.index.intersection(tiingo_df.index)
-    only_o = oanda_df.index.difference(tiingo_df.index)
-    only_t = tiingo_df.index.difference(oanda_df.index)
-    if len(only_o):
-        print(f"  bars only in Oanda : {[str(t) for t in only_o]}")
-    if len(only_t):
-        print(f"  bars only in Tiingo: {[str(t) for t in only_t]}")
-    if not len(common):
-        print("  NO common timestamps — feeds are on different bar grids!")
-        return
-
-    o = oanda_df.loc[common, OHLC]
-    t = tiingo_df.loc[common, OHLC]
-    diff = o - t
-
-    print(f"\n  {len(common)}/{n} bars share timestamps "
-          f"(window {common[0]} → {common[-1]})\n")
-
-    # Per-bar Close table — the number that matters most.
-    hdr = f"  {'bar close (UTC)':<20}{'Oanda C':>12}{'Tiingo C':>12}{'ΔC ($)':>10}"
-    print(hdr + f"{'ΔO':>8}{'ΔH':>8}{'ΔL':>8}")
-    for ts in common:
-        row = (f"  {str(ts):<20}{o.loc[ts, 'Close']:>12.2f}"
-               f"{t.loc[ts, 'Close']:>12.2f}{diff.loc[ts, 'Close']:>10.3f}")
-        row += (f"{diff.loc[ts, 'Open']:>8.3f}{diff.loc[ts, 'High']:>8.3f}"
-                f"{diff.loc[ts, 'Low']:>8.3f}")
-        print(row)
-
-    print("\n  summary over common bars:")
-    for col in OHLC:
-        d = diff[col].abs()
-        print(f"    {col:<6} max |Δ| = {d.max():8.4f}   mean |Δ| = {d.mean():8.4f}")
-    px = o["Close"].iloc[-1]
-    dc = diff["Close"].abs()
-    print(f"    Close Δ as % of price: max {dc.max() / px * 100:.4f}%   "
-          f"mean {dc.mean() / px * 100:.4f}%")
-    exact = (diff[OHLC].abs() < 1e-9).all(axis=1).sum()
-    print(f"    bars with identical OHLC: {exact}/{len(common)}")
-
-
-def main():
-    ap = argparse.ArgumentParser()
-    ap.add_argument("--n", type=int, default=10,
-                    help="bars per timeframe to compare (default 10)")
-    args = ap.parse_args()
-
-    cfg = PlatformConfig()
-    oanda = make_data_provider(cfg, "oanda")
-    tiingo = make_data_provider(cfg, "tiingo")
-
-    for tf in TIMEFRAMES:
-        o_df = fetch_tail(oanda, tf, args.n)
-        t_df = fetch_tail(tiingo, tf, args.n)
-        compare_tf(tf, o_df, t_df, args.n)
-
-    print("\nDone. Note: Oanda=mid of MBA candles, Tiingo=resampled mid — "
-          "sub-$1 diffs on gold are normal feed divergence, not a bug.")
-
-
-if __name__ == "__main__":
-    sys.exit(main())