Khalim Conn-Kowlessar d8ef40c745 feat(modelling): offline cohort runner over an EPC-JSON dump ... `harness.cohort.run_cohort(paths)` parses each API-shaped EPC JSON with from_api_response and models it via run_modelling — no database, no network — capturing per-cert errors instead of aborting the sweep, plus `format_cohort_summary`. A thin `scripts/run_modelling_cohort.py` CLI points it at a directory. Proven over the 57 golden API certs: 56 ran offline, 15 produced measures, 1 errored (COAL has no Fuel Rates entry — a BillDerivation coverage gap, not a harness one). Ready for the EPC dump. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>		2026-06-04 09:23:32 +00:00
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__init__.py	feat(modelling): sense-check table for a Plan in the DB-less harness	2026-06-04 08:06:53 +00:00
cohort.py	feat(modelling): offline cohort runner over an EPC-JSON dump	2026-06-04 09:23:32 +00:00
console.py	feat(modelling): robust offline modelling inspection (run_modelling)	2026-06-04 09:19:18 +00:00
plan_table.py	feat(modelling): wire Valuation Uplift onto the Plan	2026-06-04 08:59:04 +00:00
sample_catalogue.json	feat(modelling): robust offline modelling inspection (run_modelling)	2026-06-04 09:19:18 +00:00