The neighbour SAP-divergence cohort was (postcode, property_type, built_form),
which mixed electric- and gas-heated dwellings. Electricity scores materially
lower in SAP than mains gas for identical fabric, so a mixed-fuel postcode
produced cross-fuel false outliers — an electric dwelling flagged only for being
electric among gas neighbours.
Add the main-heating fuel class to the cohort key (electricity variants — 29/30
+ off-peak 31-40 — collapse to one class; every other code is its own bucket).
Now every flagged divergence is a same-fuel comparison worth investigating. On
portfolio 814 this refined 20 raw divergences to 17 same-fuel ones while keeping
the genuine within-fuel outliers (e.g. the all-electric WC2B 4AW flats at SAP
26/38 vs a cohort median of 67).
Reaches the fuel via epc_main_heating_detail through the indexed property_id —
still never touches the recommendation table. Surfaced by the portfolio-814
recommendation audit (Work item B, #1388).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
A focused sibling to audit-ara-portfolio: that skill audits baselines/plans/SAP;
this one audits the *recommendations themselves* — why a measure was or wasn't
offered. Motivated by the portfolio-814 review (Khalim's HHRSH-on-community-
heating, missing-HHRSH, missing-secondary-heating-removal, and a neighbour split).
Adds:
- .claude/skills/find-weird-recommendations/SKILL.md — scan -> neighbour scan ->
live re-model deep-dive -> root-cause -> codify, with a seeded known-bug
catalogue and the query-safety rules inherited from audit-ara-portfolio.
- scripts/audit/anomalies.py: new `plan-stops-short-of-goal` HIGH check — the
default plan ends below the goal band on an unlimited-budget scenario (the
deterministic worklist for "why didn't this get recommended X"). Adds
scenario_budget to the bundle/query so budget-capped scenarios are excluded.
- scripts/audit/neighbour_divergence.py: groups a portfolio by (postcode,
property_type, built_form) and flags effective-SAP outliers vs the cohort
median. Never touches the 26m-row recommendation table, so it is safe
portfolio-wide.
- Tests for both (12 passing).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
