fix(loop): compress old experiment history in proposal prompt to reduce context size

- Summarize all but the 2 most recent experiments to compact bullet lines
  (factor name, PASS/FAIL, IC value, 120-char observation snippet) instead
  of including full verbatim traces; reduces prompt from ~121k to ~40-60k tokens
- Fix _evaluate_factor_directly and _save_factor_values to look for result.h5
  and factor.py in sub_workspace_list instead of experiment_workspace
- Fix Series.to_parquet() → Series.to_frame().to_parquet() in _save_factor_values
- Update factor_data_template README: correct bars-per-day (1440, not 96)
- Update prompts to accept 2024-only debug dataset output as valid factor result
- Fix factor_coder prompts: allow 2024 debug data in date-range instruction

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

rdagent/components/coder/factor_coder/prompts.yaml

@@ -53,7 +53,7 @@ evolving_strategy_factor_implementation_v1_system: |-
   - ALWAYS use `min_periods=N` where N equals the window size in rolling calculations (e.g., `.rolling(20, min_periods=20)`)
   - ALWAYS handle infinite values after division: `.replace([np.inf, -np.inf], np.nan)` before saving results
   - ALWAYS use `groupby(level=1)` or `groupby('instrument')` before rolling operations on MultiIndex dataframes
-  - Process the COMPLETE date range (2020-2026), do NOT filter by date
+  - Process the COMPLETE date range available in the HDF5 file (do NOT filter by date — the file may contain 2024 debug data or full 2020-2026 data)
   - Use `groupby().transform()` instead of `groupby().apply()` for single-column assignments
 
   Notice that you should not add any other text before or after the json format.