Commit graph

9 commits

Author SHA1 Message Date
Jun-te Kim
003defcf55 Add find-weird-recommendations skill + its two detectors
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>
2026-07-01 11:06:03 +00:00
Daniel Roth
db27a6153f
Merge pull request #1374 from Hestia-Homes/audit/bad-lodged-source-data
fix(audit): Class C — silence effective-lodged-divergence for implausible lodged scores (#1361)
2026-07-01 09:15:45 +01:00
Daniel Roth
afe1801273 implausible-lodged-score check fires for bad upstream EPC data (lodged < 13, gap >= 15) 🟩
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-30 15:27:19 +00:00
Daniel Roth
e70df63ee6 implausible-lodged-score check fires for bad upstream EPC data (lodged < 13, gap >= 15) 🟥
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-30 15:26:29 +00:00
Daniel Roth
fe1d04983b effective-lodged-divergence is silent for implausible lodged scores (< 13) 🟩
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-30 15:25:02 +00:00
Khalim Conn-Kowlessar
4a110d13cd Guard the portfolio audit against the 26m-row recommendation seq-scan
The `recommendation` table (~26m rows) has no index on `plan_id`, so any query
reaching it via `plan_id` — including the audit's own rollup — seq-scans the
whole table and saturates the shared DB (it blocked the DB during the
portfolio-796 audit). Make the audit safe-by-default:

- statement_timeout (120s) on the audit connection — a hard ceiling so a bad
  plan aborts instead of hammering the DB.
- The recommendation rollup (the two solar checks) is now opt-in via
  --with-recommendations, and EXPLAIN-gated: it refuses to run (raising
  RecommendationScanError) when the plan contains a Seq Scan on recommendation,
  which it does on any large portfolio until idx_recommendation_plan_id exists.
- SKILL.md documents the plan_id-no-index trap, the reach-via-property_id /
  EXPLAIN-first / confirm-with-user rules, and the index as the real fix.

Verified on 796/1268: default run is bounded and completes (2,952 anomalies over
31,919 properties); --with-recommendations aborts pre-scan portfolio-wide but is
allowed for a single property.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-30 13:23:26 +00:00
Khalim Conn-Kowlessar
2d6b078bd8 feat(audit): self-improvement loop in the skill + provenance convention 🟩
Add Phase 6 (self-improve) to audit-ara-portfolio: when a run confirms a
novel systematic problem, codify it as a check — gated on systematic (>=5
props, root-caused), not-already-covered, and /grill-me-pressure-tested.
Each check records provenance (motivating cause + example properties) so the
registry stays sharp and compounds every run.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-26 19:57:57 +00:00
Khalim Conn-Kowlessar
e3c9107313 feat(audit): --scenario filter + audit-ara-portfolio skill 🟩
Script takes an optional --scenario to restrict to one scenario's plans. New
skill drives the full loop: run the deterministic scan, review groups,
deep-dive samples via run_modelling_e2e, characterise sub-classes, and
cross-reference open PRs/ADRs — then proposes new checks to codify.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-26 19:49:48 +00:00
Khalim Conn-Kowlessar
37c7a2c186 feat(audit): solar + high-SAP checks; group under scripts/audit/ 🟩
Add recommendation-level rollups (solar SAP points + solar bill saving) and
checks: impossible-sap-over-100 (found 1), excessive-solar-sap (oversized
array, 51), low-solar-bill-savings (SEG/self-consumption pricing, 83),
unusually-high-post-sap (21). Move to scripts/audit/anomalies.py
(python -m scripts.audit.anomalies).

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-26 19:46:23 +00:00