Request:
- Reflect that near-final market heat can be used when the user can still place an IPO order at T0.95.
Changes:
- Added T0_95_final_heat as a separate analyst decision stage with executability and no-leakage rules.
- Added an experimental T0.95 rule overlay for late-order heat scoring and calibration discipline.
- Updated archivist guidance and the market-heat archiver so snapshots can be explicitly stored as T0_95_final_heat.
- Added market_heat_stage to the analysis dataset and refreshed the model report to show T0.95 coverage separately.
Verification:
- Ran py_compile for the modified scripts.
- Checked archive_t0_5_market_heat.py --help for the new --stage option.
- Rebuilt data/snapshots/analysis_model_v0_dataset.csv and reports/2026-06-15_analysis_model_v0.md.
- Ran git diff --check.
Next useful context:
- Current archived heat rows remain T0_5_market_heat only; there are no true T0.95 rows yet.
- external_ipo_history.public_oversubscription_times is still calibration-only unless a comparable value is archived before the executable order cutoff.
Request:
- Make analyst reports Chinese by default and record the rule in the analyst skill.
Changes:
- Add a Simplified Chinese default-language rule to the analyst skill.
- Update the single-IPO report generator to emit Chinese Markdown sections, labels, actions, risks, triggers, and exit plans.
- Preserve ticker symbols, stage codes, rule ids, score buckets, and source paths as machine-readable identifiers.
- Regenerate the 06106 T0 report in Chinese.
- Document the Chinese report default in README and the rule change log.
Verification:
- Ran py_compile for scripts/generate_ipo_report.py.
- Generated a 06106 dry-run report and checked Chinese section headings.
- Regenerated reports/2026-06-15_06106_T0_prospectus_analysis.md.
- Ran git diff --check.
Next useful context:
- Future analyst prediction and review reports should be written in Simplified Chinese unless the user explicitly requests another language.
Request:
- Include the concrete T0, T1, T2, and D1 dates in every analyst report.
Changes:
- Add a Stage Calendar section to the single-IPO report generator.
- Require analyst reports to include ticker-specific T0 subscription window, T1 allotment-result date, T2 grey-market date/window, and D1 listing date.
- Update the 06106 T0 report with its concrete stage dates.
- Document the requirement in the analyst skill, README, and rule change log.
Verification:
- Ran py_compile for scripts/generate_ipo_report.py.
- Generated a 06106 dry-run report and checked the stage calendar.
- Ran git diff --check.
Next useful context:
- For 06106, T0 is 2026-06-15 to 2026-06-18, T1/T2 is 2026-06-23, and D1 is 2026-06-24.
Request:
- Emphasize that the analyst model is for selling allocated IPO shares in T2 grey market or on D1, not for long-term holding.
Changes:
- Add explicit T2/D1 sell discipline to the analyst skill.
- Update ipo_score_v0 targets and holding policy so D1 sell return is primary and T2 is the intended extension when reliable grey-market data exists.
- Clarify that D5/D20/D60 are review labels only, not planned holding targets.
- Update the model report, single-ticker report generator, README, and the 06106 report language to reflect the short-exit horizon.
Verification:
- Rebuilt the model report with the same dataset timestamp and confirmed the analysis dataset did not change.
- Ran py_compile for build_analysis_dataset.py and generate_ipo_report.py.
- Generated a 06106 dry-run report showing T2/D1 exit discipline.
- Ran git diff --check.
Next useful context:
- T2 is still disabled in v0 until archivist approves a reliable grey-market data source; D1 remains the live modeled sell label.
Request:
- Re-analyze the IPO model using the updated historical archive after T1 demand backfill.
Changes:
- Regenerate the v0 analysis dataset from the current SQLite archive.
- Refresh the v0 calibration report with expanded T1 coverage and new empirical bucket rates.
- Update the report template to show pending T1 rows and field-level blanks.
- Clarify v0 limitations and record why the score formula stays unchanged for this refresh.
Verification:
- Ran scripts/build_analysis_dataset.py against data/hk_ipo.sqlite.
- Ran py_compile for scripts/build_analysis_dataset.py.
- Checked dataset row count, T1 demand coverage, source-only T1 gaps, and repo-relative paths.
- Ran git diff --check.
Next useful context:
- T1 structured coverage is now 291 rows, with 06106 and 06675 still pending_not_due.
- The high-conviction T1 bucket remains differentiated, but middle and low buckets are still not monotonic enough for a v1 rule change.
Request:
- Use the analyst skill to digest downloaded IPO archive data and start building an analysis model.
Changes:
- Add ipo_score_v0 as the first transparent stage-safe scoring rule set.
- Add build_analysis_dataset.py to derive model features, scores, decision bands, and empirical D1 calibration from SQLite.
- Generate analysis_model_v0_dataset.csv with 293 scored IPO rows and archived source paths.
- Add a model calibration report documenting coverage, T0/T1 bucket performance, usage, and known gaps.
- Record the initial model entry in the rule change log and document the command in README.
Verification:
- Ran py_compile for scripts/build_analysis_dataset.py.
- Regenerated the analysis dataset and report with as-of 2026-06-15T13:00:00Z.
- Checked CSV row count, source path coverage, and repo-relative path hygiene.
- Ran git diff --cached --check.
Next useful context:
- v0 should be treated as a transparent baseline, with T1 high-score calibration strongest and middle buckets still non-monotonic.
- T2 is excluded until a reliable grey-market source is approved.
geometrybase