diff --git a/.beads/issues.jsonl b/.beads/issues.jsonl
index 1d15142..f10434c 100644
--- a/.beads/issues.jsonl
+++ b/.beads/issues.jsonl
@@ -22,6 +22,7 @@
 {"id":"homemaker-py-1p0","title":"Geometry inner loop: full-objective equal-offset ratio optimiser","description":"DESIGN.md §5.1, §7 Phase 1. Productionise experiments/optimize_fullfitness.py into homemaker: optimise(topology, x0=None) -\u003e (geometry, fitness). DOF = equal-offset division ratios of free branches (solver.free_branches, lowest-storey cut ownership), clipped to [eps, 1-eps]. Objective = full oracle fitness (never a proxy — §4.2 falsified). Must support warm-start x0 (§5.6) and a population/batch evaluation mode so each iteration scores via one batched oracle call (§4.6).","acceptance_criteria":"Reproduces or exceeds §4.5 gains (x1.24–x1.67, no new failures) on 2f45907, candidate-002, c964435; works as a library call on any corpus .dom","status":"closed","priority":1,"issue_type":"feature","assignee":"Bruno Postle","owner":"bruno@postle.net","created_at":"2026-06-11T23:36:58Z","created_by":"Bruno Postle","updated_at":"2026-06-12T08:46:31Z","started_at":"2026-06-12T00:14:19Z","closed_at":"2026-06-12T08:46:31Z","close_reason":"innerloop.optimise() lands: batched CMA-ES sigma ladder (0.05/0.15, IPOP popsize doubling, deterministic seeding) over equal-offset free-branch ratios vs full oracle fitness; warm-start x0 supported. Acceptance vs unprojected originals: x1.65/x1.66/x1.58 against bars x1.24/x1.67/x1.59, no new failures, 46 oracle calls vs NM's 200. Two near-bar results accepted as reproduced-within-noise (1% tol) — draw spread brackets the single-NM-draw bars; approved by Bruno 2026-06-12. Gotchas: equal-offset projection of legacy unequal cuts loses fitness/adds failures (midpoint projection used); pycma seed=0 means clock-seeded.","dependencies":[{"issue_id":"homemaker-py-1p0","depends_on_id":"homemaker-py-av5","type":"blocks","created_at":"2026-06-12T00:39:33Z","created_by":"Bruno Postle","metadata":"{}"}],"dependency_count":1,"dependent_count":3,"comment_count":0}
 {"id":"homemaker-py-8cs","title":"Experiment: warm-vs-cold start of inner loop (Lamarckian inheritance)","description":"DESIGN.md §5.6, §4.6. Warm-starting a child topology's inner loop from the parent's optimised ratios is the main lever for cutting per-topology cost (~3 min/topology cold). Apply single topology mutations to optimised corpus designs, re-optimise warm (surviving cuts keep values, new cuts get heuristic defaults) vs cold, compare oracle-call counts to convergence at equal final fitness.","acceptance_criteria":"Speedup factor measured across \u003e=10 mutated topologies; decision recorded (expect order-of-magnitude; if \u003c2x, revisit §4.6 Phase-2 scoping)","notes":"Experiment script committed (experiments/warm_vs_cold.py, 1cc86c8) and machinery validated oracle-free; one mutated child scored through the oracle OK. Waiting on homemaker-py-gp2 reference run to finish, then execute under URB_NO_OCCLUSION=1 (3 parents x 400 evals + 12 children x 2 x 200 evals, ~1.5-2 h oracle time). Default budgets: parent 400, child 200; target = evals to 95% of best final.","status":"closed","priority":1,"issue_type":"task","owner":"bruno@postle.net","created_at":"2026-06-11T23:36:58Z","created_by":"Bruno Postle","updated_at":"2026-06-12T11:44:45Z","closed_at":"2026-06-12T11:44:45Z","close_reason":"Measured (URB_NO_OCCLUSION=1, parent budget 400, child 200, 12 single mutations across 3 designs): cold start reached 95% of warm final in 0/12 cases within budget — speedup unbounded at practical budgets; warm finals beat cold finals x1.2-x4 in 12/12; 6/12 warm starts were within 95% at 1 eval (near-neutral mutations). Decision: Lamarckian warm-starting is MANDATORY in the memetic driver (homemaker-py-b39), not an optimisation; cold starts produce strictly worse geometry at equal budget. Note: 2 undivides were exactly fitness-neutral (same-type merge == Merge_Divided equivalence) — locality datum for homemaker-py-nyb.","dependencies":[{"issue_id":"homemaker-py-8cs","depends_on_id":"homemaker-py-1p0","type":"blocks","created_at":"2026-06-12T00:39:34Z","created_by":"Bruno Postle","metadata":"{}"}],"dependency_count":1,"dependent_count":0,"comment_count":0}
 {"id":"homemaker-py-av5","title":"Batched oracle: score many .dom files per invocation","description":"oracle.py currently scores one .dom per urb-fitness.pl call (~1.65 s/dom). DESIGN.md §4.6: batching amortises Perl startup to ~0.99 s/dom and is required so population/batch optimisers can score a whole generation in one oracle call. Extend oracle.py with a batch API: write N .dom files, one perl invocation, parse N .score/.fails pairs. Keep the single-file path for compatibility.","acceptance_criteria":"Batch of 35 corpus files scores in one perl invocation; per-file results identical to single-file calls; measured s/dom reported","status":"closed","priority":1,"issue_type":"task","assignee":"Bruno Postle","owner":"bruno@postle.net","created_at":"2026-06-11T23:36:56Z","created_by":"Bruno Postle","updated_at":"2026-06-12T00:14:06Z","started_at":"2026-06-11T23:50:40Z","closed_at":"2026-06-12T00:14:06Z","close_reason":"score_batch() lands in oracle.py; 35-file corpus parity verified single-vs-batch (1e-12 rel fitness, exact fail sets); 0.98 s/dom batched vs 1.27 single, x1.30","dependency_count":0,"dependent_count":1,"comment_count":0}
+{"id":"homemaker-py-91f","title":"Residual diagnostic on current full default construction stack","description":"Re-run the §13.1/§13.2-style per-leaf fail-breakdown diagnostic (experiments/diag_leaf_shapefail.py, diag_slack_localization.py) on the CURRENT full default stack (proportion-aware + adjacency-aware seeding, depth-balanced, leaf-sharing factor 3, interior-O odiv=3, share-aware edge cap — post homemaker-py-rq2/x3b), on harbor-house and maple-court. The last such diagnostic predates hph/rq2 (share-aware edge cap) and the erc.7 depth-balance+leaf-sharing synergy default flip, so the current floor (harbor 31.0, maple 74.0 per §13.9) has never been decomposed by failure category/leaf. This is the same read-only methodology that found leaf-sharing (erc.3), depth-balancing (erc.4), interior-O (ld2), and the edge-cap fix (hph) — DESIGN.md's own diagnostic-first discipline. Expected output: which fail category now dominates the residual, informing the next concrete construction lever (the way §13.7's edge-too-long finding directly produced hph). No code changes, no A/B — pure measurement.","design":"Reference: DESIGN.md §13.1 (erc.1), §13.2 (erc.2), §13.7 (71d.1), §13.9 (rq2). Scripts to reuse/extend: experiments/diag_leaf_shapefail.py, experiments/diag_slack_localization.py, experiments/diag_edge_too_long.py.","status":"open","priority":2,"issue_type":"task","owner":"bruno@postle.net","created_at":"2026-08-01T10:06:37Z","created_by":"Bruno Postle","updated_at":"2026-08-01T10:06:37Z","dependency_count":0,"dependent_count":0,"comment_count":0}
 {"id":"homemaker-py-1s3","title":"Multi-use leaves as permanent design goal (§26 path b, never attempted)","description":"§26 (homemaker-py-9o5/xi7/b3v) scoped two readings of multi-use leaves (a leaf legitimately serving several DIFFERENT compatible programme codes at once, e.g. study+guest-bedroom, kitchen+dining — Stewart Brand's 'loose-fit' rooms): (a) superposition as a SEARCH RELAXATION — carry uncommitted candidate types per leaf, collapse to one usage only at scoring time; (b) multi-use as the PERMANENT DESIGN GOAL, surviving into the output with no collapse. Only (a) was built and measured, and it was NULL/NEGATIVE — diagnosed as underperforming not from a relaxation gap (measured small, gap_ratio 1.01-1.23) but because the geometry floor dominates: type labels are not the binding constraint on these programmes, so easing them buys nothing while re-typing adds feasibility noise (fitness.py per-eval collapse perturbs counts/adjacency).\n\nPath (b) was never built. It's structurally different from (a): rather than a per-eval relabelling relaxation on top of the existing leaf count, it would permanently REDUCE leaf count by having one leaf serve two rooms' worth of programme requirement simultaneously — the same structural mechanism as leaf-sharing (§13.3, homemaker-py-x3b), which is the single biggest positive lever in the whole DESIGN.md log (harbor-house −21% to −32% at various stages, because it cuts leaf count in a way the search cannot mutate back — §13.4/13.5's key finding that levers the search 'cannot erode' compound, unlike shape-only levers that wash out over a 20k-eval budget).\n\nMultiple independent diagnostics (§12.3 calibration, §12.4's conclusion, §13.1's per-leaf saturation analysis) converge on: the residual fail floor at harbor/maple scale is driven by having as many leaves as there are distinct rooms (52 rooms -\u003e 73 leaves at 44% utilisation gives every leaf a high perimeter/area ratio). Leaf-sharing already exploits this for SAME-code multiplicities; path (b) would extend the same leverage to DIFFERENT-but-compatible codes, which is a materially larger addressable set on programmes with many small single-instance rooms (offices, WCs, meeting rooms — see health-centre, examples/health-centre, 19 distinct codes).\n\nTask: design + build path (b) — likely: SpaceReq gains a compatibility/co-location relation (reuse or extend programme.derive_interchange_classes' S1-S4 guards, or a new explicit 'co_locate' declaration since 'interchangeable' semantics don't fit two DIFFERENT codes coexisting), a leaf can be permanently typed as serving code-pair (or code-set) X, and check_space_counts/quality functions treat the areas as shared per the k-instances-per-leaf model §13.3 already uses for same-code sharing. Gate behind a new conf flag (default OFF, bit-identical when off, per this project's established pattern for every §13.x/§20+ lever). A/B against the current default stack on harbor-house and health-centre (the diverse-room-type programme built for xyu/9yx, §31/§32) before considering a default flip — same discipline as every other lever in this log.","notes":"FINAL VERDICT: NULL. The N=3 positive result did not replicate.\n\nThree measurements collected:\n1. Original (N=3, staged, 20k budget): harbor -1.4%, health-centre -13.9% -- looked promising\n2. Confirm #1 (N=15, plain search, 3k budget, mirrors xyu/9yx protocol): harbor +6.1% worse (p=0.30),\n   health-centre +6.6% worse (Wilcoxon p=0.044) -- different protocol (budget+algorithm), but negative\n3. Confirm #2 (N=15, staged, 20k budget -- TRUE same-conditions replication): harbor +6.6% worse (p=0.15),\n   health-centre +4.7% worse (p=0.48) -- both trend negative, neither significant\n\nConfirm #2 is the one that actually matches the original protocol (only seed count differs), and it\ndisagrees with the original's direction on both programmes. Conclusion: the N=3 result was sampling\nnoise (health-centre's -13.9% was driven substantially by one seed swinging 71-\u003e43; didn't hold at N=15).\n\nmulti_use stays default OFF, not recommended even as a \"promising\" lever -- this is a clean NULL result,\nnot mixed/promising. Mechanism is complete, tested (335/335), gated off, left in the codebase as a\ndocumented option an architect could opt into per-programme, but no further investment planned.\n\nDESIGN.md §33 fully rewritten with all three measurements and the honest conclusion. This closes out both\nhalves of §26's multi-use-leaves question: path (a) search-relaxation was NULL/NEGATIVE, path (b)\npermanent-fusion is NULL after replication.\n\nTotal compute across this investigation: ~2h (original) + ~2h (precision-weighted rerun) + ~2h (mixture\nrerun) + ~1.5h (N=15 plain confirm) + ~10h (N=15 staged confirm) = ~17.5h across 5 A/B runs.","status":"closed","priority":2,"issue_type":"task","assignee":"Bruno Postle","owner":"bruno@postle.net","created_at":"2026-07-30T07:55:56Z","created_by":"Bruno Postle","updated_at":"2026-08-01T07:48:32Z","started_at":"2026-07-30T09:20:03Z","closed_at":"2026-08-01T07:48:32Z","close_reason":"Closed","dependency_count":0,"dependent_count":0,"comment_count":0}
 {"id":"homemaker-py-h10","title":"Re-run §12.3 reassociate/shape-feasibility A/B at fixed worker count","description":"§12.3 (homemaker-py-9gp) measured mutate_reassociate (M3 Wong-Liu move) and the shape-feasibility pre-filter as negative: +3.3/+4.0 fails on maple/harbor. But that A/B ran BEFORE §12.4 (homemaker-py-c3g) found and fixed a real nondeterminism bug — driver._run_batch admitted parallel futures in completion order rather than submission order, producing ±3-6 fail noise between otherwise-identical runs. §12.4's own writeup flags this explicitly: 'sub-±3 effects (the §12.3 +3-4 negatives, the §12.4 ±1.7) should be re-run at a single fixed worker count before being trusted as magnitudes.' That re-run was never done for §12.3.\n\nReassociate is the only search-machinery move in the whole DESIGN.md log verified to reach genuinely new tree topologies (confirmed on synthetic cases in §12.3's own tests) — every other outer-search-machinery lever tried (niching, graded objective, island model, grain annealing, graded connectivity, circulation repair, beam search, ruin-recreate, bubble-diagram signal) is independently null-to-negative for other reasons, so this is the one candidate whose 'negative' verdict might be pure measurement artifact rather than a real finding.\n\nTask: re-run experiments/run_9gp_ab.sh (maple-court + harbor, seeds 0/1/2, 20000 evals, staged) with the post-c3g determinism fix in place, at a single fixed worker count (matching whatever the original run used — check the script/log for workers=N). If the negative holds at fixed worker count, close as confirmed-null (upgrade §12.3's confidence). If it flips positive or neutral, this reopens the reachability question closed in §12.3/§12.4's 'residual is geometry floor, not search-reachability' conclusion — would need a larger-N confirmation before any default flip, per this project's own evidentiary bar (cf. f1d/1ph/e01 pattern).","status":"closed","priority":2,"issue_type":"task","assignee":"Bruno Postle","owner":"bruno@postle.net","created_at":"2026-07-30T07:55:15Z","created_by":"Bruno Postle","updated_at":"2026-07-30T08:14:43Z","started_at":"2026-07-30T08:06:25Z","closed_at":"2026-07-30T08:14:43Z","close_reason":"Confirmed without a full re-run: run_9gp_ab.sh/run_staged_search.py never threaded a worker count, so every §12.3 arm already ran at n_workers=1 (serial) — the mode §12.4 already proved byte-for-byte reproducible even before the completion-order fix (that bug is ProcessPoolExecutor-as_completed-only). Spot-checked empirically too: same config run twice (harbor-house s0, budget 300) gave identical fail counts at every checkpoint. §12.3's negative verdict is CONFIRMED at fixed worker count; DESIGN.md §12.4 updated with the finding.","dependency_count":0,"dependent_count":0,"comment_count":0}
 {"id":"homemaker-py-9wi","title":"Adjacency-aware discrete assignment for finish-time collapse (QAP/CP-SAT)","description":"fitness.collapse_superposition (homemaker-py-9o5/94g family) already does exact optimal relabelling of superposed leaves via brute-force permutation (CLASS_CAP\u003c=4) or Hungarian (linear_sum_assignment) beyond that -- but _best_assignment's docstring is explicit that the objective is deliberately SEPARABLE per leaf (quality_size * quality_width * quality_proportion only); perpendicular/crinkliness/access/adjacency are assumed usage-invariant within a class and left out, because adjacency quality depends on PAIRS of leaf-label assignments, not one leaf at a time, which breaks the exact separable solve.\n\nProposal: extend the collapse step to account for adjacency between candidate labels -- either a quadratic-assignment-style local search (2-opt swaps over the current Hungarian solution, accepting swaps that improve total adjacency satisfaction) or a CP-SAT (OR-Tools) encoding of the labelling problem with pairwise adjacency terms. This directly extends the one search-adjacent technique (exact/near-exact discrete assignment) that has actually paid off in this project, into territory the current separable solve cannot reach.\n\nMeasure against the current Hungarian-only collapse on harbor-house (heavy interchange-class usage: neighborhoods, meeting rooms, individual rooms) where adjacency-blind relabelling is most likely to leave adjacency fails on the table.","status":"closed","priority":2,"issue_type":"task","assignee":"Bruno Postle","owner":"bruno@postle.net","created_at":"2026-07-25T20:18:24Z","created_by":"Bruno Postle","updated_at":"2026-07-26T19:57:55Z","started_at":"2026-07-26T14:50:36Z","closed_at":"2026-07-26T19:57:55Z","close_reason":"2-opt local search DELIVERED beyond collapse_global's Jacobi adjacency relaxation:\nFitness._collapse_value (refactored per-leaf-per-code value, shared by the\nassignment matrix and the polish) + Fitness._two_opt_adjacency_polish (same-level\npairwise label-swap search, kept only on strict improvement -- monotone by\nconstruction) + collapse_global(local_search=..., local_search_passes=...) +\nhomemaker-collapse --local-search CLI flag + regression test\n(test_two_opt_polish_escapes_jacobi_plateau) that proves the Jacobi loop can\n2-cycle between two labellings satisfying ZERO of a satisfiable adjacency set,\nand that 2-opt escapes it.\n\nWent with 2-opt over CP-SAT/OR-Tools: no new dependency (project has no\nortools), directly extends the existing Jacobi machinery, and the issue listed\nit as the first alternative. QAP is NP-hard in general so this is a local\nsearch, not an exact solve, but it strictly dominates the Jacobi-only result\n(never worse, by construction).\n\nMeasured against harbor-house per the issue's own instruction: swept all 11\nevolved-*/3m/materialised .dom files, comparing collapse_global(local_search=False)\nvs (local_search=True). 10/11 matched exactly (Jacobi was already at the local\n2-opt optimum), 0 regressed, 1 improved (evolved-anneal-3M.dom 21-\u003e19 fails --\nresolved a genuine mutual da1\u003c-\u003ek1 adjacency miss). Runtime \u003c1s even on the\nlargest file (90-fail evolved-3M.dom). Findings + the plateau proof saved via\nbd remember. Default left OFF (opt-in via local_search=True /\nhomemaker-collapse --local-search) pending a broader sweep and evolve.py CLI\nwiring -- spun off as homemaker-py-cdl.\n\n298/298 tests pass (7 in test_collapse_global.py, up from 6).","dependency_count":0,"dependent_count":0,"comment_count":0}
@@ -60,6 +61,9 @@
 {"id":"homemaker-py-nyb","title":"High-locality topology operators (mutation + subtree crossover)","description":"DESIGN.md §5, §7 Phase 2, §8.4. Mutation moves: divide/undivide leaf, swap children, rotate cut, retype leaf, per-floor delta edits, storey add/delete (cf. Urb Mutate.pm — but geometry sliding belongs to the inner loop, not the operator set). Crossover: area-matched subtree exchange (a subtree = a contiguous region, so crossover is meaningful — Crossover.pm). Operators must be high-locality: small genome change =\u003e small phenotype change, so warm-started inner loops stay cheap.","acceptance_criteria":"Each operator produces valid genomes (oracle scores them without error); locality measured (mean fitness/geometry perturbation per operator)","status":"closed","priority":2,"issue_type":"feature","assignee":"Bruno Postle","owner":"bruno@postle.net","created_at":"2026-06-11T23:37:27Z","created_by":"Bruno Postle","updated_at":"2026-06-12T13:07:37Z","started_at":"2026-06-12T12:54:23Z","closed_at":"2026-06-12T13:07:37Z","close_reason":"operators.py lands: 7 mutations + area-matched crossover, valid-by-construction via genome.encode repair. 115/115 oracle-valid children; locality measured: geom-pert 0.07-0.33 per op, fitness-pert 0.68-0.99 (0.5^n cliff flags raw moves — warm restart + penalty reshaping confirmed load-bearing). Also fixed dom._link stale below-links on structural mutation.","dependencies":[{"issue_id":"homemaker-py-nyb","depends_on_id":"homemaker-py-k2g","type":"blocks","created_at":"2026-06-12T00:39:36Z","created_by":"Bruno Postle","metadata":"{}"}],"dependency_count":1,"dependent_count":1,"comment_count":0}
 {"id":"homemaker-py-k2g","title":"Topology genome: base-floor tree + per-floor deltas + type assignment","description":"DESIGN.md §5.2, §7 Phase 2. Genome = base-floor slicing topology (primary) + per-leaf type assignment + per-floor divide/undivide deltas (Below-inheritance as regulariser; cut owned by lowest storey where its path is divided — §10). Must round-trip to/from dom.py Node trees so the oracle and inner loop consume it directly. Includes storey count and per-floor type overrides.","acceptance_criteria":"Genome \u003c-\u003e .dom round-trip on all 35 corpus files preserves fitness; multi-storey wall stacking preserved","status":"closed","priority":2,"issue_type":"feature","assignee":"Bruno Postle","owner":"bruno@postle.net","created_at":"2026-06-11T23:37:26Z","created_by":"Bruno Postle","updated_at":"2026-06-12T12:52:34Z","started_at":"2026-06-12T10:55:21Z","closed_at":"2026-06-12T12:52:34Z","close_reason":"genome.py encode/decode lands. 35/35 oracle fitness parity after round-trip (flag-on); genome fixed-point + owned-projection tests. Dead-field discovery: corpus upper storeys carry drifted dead divisions (97) and rotations (187) — canonicalised by decode, validated fitness-neutral.","dependency_count":0,"dependent_count":1,"comment_count":0}
 {"id":"homemaker-py-d0s","title":"Experiment: inner-loop optimiser bake-off at equal oracle budgets","description":"DESIGN.md §7 Phase 1, §8.3. DOF is only ~rooms-1 (6–7 on corpus). Compare Nelder-Mead vs CMA-ES vs batched multi-start pattern search at equal oracle-call budgets, measuring fitness gained per oracle call and wall-clock (batch-friendliness matters — §4.6). Measure, don't commit blind.","acceptance_criteria":"Table of fitness-per-budget across \u003e=3 candidates; one optimiser chosen and recorded in DESIGN.md","status":"closed","priority":2,"issue_type":"task","assignee":"Bruno Postle","owner":"bruno@postle.net","created_at":"2026-06-11T23:36:59Z","created_by":"Bruno Postle","updated_at":"2026-06-13T08:48:13Z","started_at":"2026-06-12T21:22:15Z","closed_at":"2026-06-13T08:48:13Z","close_reason":"Bake-off complete: CMA-ES confirmed as Phase 1/2 optimiser. NM wins quality per eval but sequential architecture incompatible with batching (§4.6). Compass stalls on narrow valleys. Results in DESIGN.md §8.3 and experiments/bakeoff_innerloop.*","dependencies":[{"issue_id":"homemaker-py-d0s","depends_on_id":"homemaker-py-1p0","type":"blocks","created_at":"2026-06-12T00:39:35Z","created_by":"Bruno Postle","metadata":"{}"}],"dependency_count":1,"dependent_count":0,"comment_count":0}
+{"id":"homemaker-py-b8g","title":"Investigate parallel/BLAS non-determinism noise source in n_workers\u003e1 runs","description":"DESIGN.md §14 (psk, island-model experiment) flagged a real, uninvestigated noise source: 'Phase A is unaffected by the probe, yet harbor seed 2 scored 71 then 73 on byte-identical re-runs -- parallel/BLAS non-determinism, the same +/-2-3 effect §12.4 flagged.' This is DISTINCT from the homemaker-py-xcy bug (ProcessPoolExecutor as_completed ordering), which was fixed and made same-worker-count parallel runs reproducible for the SEARCH TRAJECTORY. This remaining noise is at the SCORING level (a single fitness eval on a fixed genome apparently returning different fail counts across runs), plausibly numpy/scipy BLAS thread nondeterminism in the geometry/inner-loop math. It was never root-caused or fixed, and it widens the error bars on every A/B in this log run at n_workers\u003e1 (the great majority of them, since serial sweeps are expensive). Investigate: reproduce minimally (score the same frozen .dom N times under workers\u003e1), bisect whether it's BLAS threading (try OMP_NUM_THREADS=1/OPENBLAS_NUM_THREADS=1), floating-point summation order, or something else; fix or document a mitigation (e.g. pin thread count in worker processes).","design":"Reference: DESIGN.md §14 'Noise caveat (carry forward)', §12.4 (homemaker-py-xcy, the related-but-distinct trajectory-ordering bug already fixed). If the cause is BLAS thread count, the fix is likely a one-line env pin in the worker pool initializer (driver.py's ProcessPoolExecutor setup).","status":"open","priority":3,"issue_type":"bug","owner":"bruno@postle.net","created_at":"2026-08-01T10:07:45Z","created_by":"Bruno Postle","updated_at":"2026-08-01T10:07:45Z","dependency_count":0,"dependent_count":0,"comment_count":0}
+{"id":"homemaker-py-7xb","title":"Validate full winning construction stack generalises to health-centre","description":"The whole positive construction-quality stack (adjacency-aware + proportion-aware seeding, depth-balanced growth, leaf-sharing factor 3, interior-O odiv=3, share-aware edge cap) has only ever been measured end-to-end on harbor-house and maple-court (DESIGN.md §11-§13, cumulative -54%/-41% vs the leu.2 baseline per §13.7). examples/health-centre exists (built for homemaker-py-9yx, a non-synthetic ~20-room programme of a different building type -- primary care, not house/co-housing) but has only ever been used to NULL-test ruin_recreate; the positive stack itself has never been run there. Run the current default full stack (staged search, matching the §13.9/§13.10 default config) on health-centre at a comparable budget/seed count to harbor/maple's Phase-8 measurements, and report whether the fail-count reduction pattern (dominated by leaf-sharing, then depth-balance synergy, then interior-O) holds on a structurally different programme mix, or whether health-centre's room-type diversity (19 distinct codes, mostly single-instance, per §32) changes which lever dominates.","design":"Reference: DESIGN.md §13.3/§13.5/§13.6/§13.9 (the levers to validate), §32 (9yx, health-centre's construction and room-code tiering). No new code expected -- this is a measurement run with the existing default-on stack, comparable to the leu.1/§12.1 benchmark-establishment style.","status":"open","priority":3,"issue_type":"task","owner":"bruno@postle.net","created_at":"2026-08-01T10:07:29Z","created_by":"Bruno Postle","updated_at":"2026-08-01T10:07:29Z","dependency_count":0,"dependent_count":0,"comment_count":0}
+{"id":"homemaker-py-fe2","title":"Experiment: 2-opt local-search polish inside collapse_insearch hot loop","description":"collapse_global's optional 2-opt adjacency polish (homemaker-py-9wi, §25) is proven positive and default-ON at finish-time (homemaker-py-cdl, §28: 46-file sweep, 0 regressions, 2 improvements incl. harbor evolved-anneal-3M 21-\u003e19). In-search collapse (collapse_insearch, homemaker-py-qpk/1ph, §20) is separately proven positive and default-ON (~11% mean fail reduction on both example programmes at N=15/20). But the two have never been combined: §28 explicitly left collapse_global's method-level local_search default OFF because 2-opt running inside the per-eval hot loop (thousands of calls per search) was 'untested and likely-costly, out of scope' for that issue -- only the one-shot finish-time cost (\u003c1s even on the largest file) was measured. This issue is the measurement: A/B collapse_insearch with local_search=True vs False (both already default-on baseline), on harbor-house and maple-court, staged search, matching the qpk/1ph protocol (equal budget, keep-better guard already monotone by construction). Report both the wall-clock cost multiplier and any fail-count effect; only recommend a default flip if positive and the cost is not prohibitive.","design":"Reference: DESIGN.md §20 (qpk), §25 (9wi), §28 (cdl) 'Where the default did NOT change' paragraph. Protocol: mirror experiments/run_qi6_ab.sh / run_lj3_qjg_ab.sh style equal-budget A/B, finish with standard --collapse, canonical homemaker-fitness re-score.","status":"open","priority":3,"issue_type":"task","owner":"bruno@postle.net","created_at":"2026-08-01T10:07:12Z","created_by":"Bruno Postle","updated_at":"2026-08-01T10:07:12Z","dependency_count":0,"dependent_count":0,"comment_count":0}
 {"id":"homemaker-py-9yx","title":"Non-synthetic third example programme to isolate ruin_recreate room-count threshold","description":"y51/xyu follow-up (option b, not run by xyu). The synthetic n=10/14/18/22 sweep scales room count by duplicating already-interchangeable programme-house room codes (count: on b1/t1/b2/t2) -- the same mechanism harbor-house itself uses 'to reduce complexity'. xyu extended n=18 to N=15 seeds (DESIGN.md 31): trend weakened but did not evaporate (9.3%-\u003e6.4%, two-sided Wilcoxon p 0.098-\u003e0.059), still ambiguous. A genuinely distinct third example programme with real room-type diversity at an intermediate room count (not a duplicated-code scale-up) would avoid the interchangeable-room confound and better isolate room count as the driving variable behind the wing-rebuild-fraction hypothesis from f1d (DESIGN.md 23).","notes":"RESOLVED (2026-07-30, DESIGN.md §32): built examples/health-centre, a 19-code/\nn=20 real health-centre programme (not duplicated-count). Wilcoxon N=15 vs\nxyu's own protocol: 8W/5L/2T, mean fails 46.13-\u003e45.13, delta=2.2%, two-sided\np=0.40, one-sided p=0.20 -- a clean null, weaker even than xyu's own\ninconclusive 6.4%/p=0.059 reading at the same room count. Converges with\nharbor-house's null-to-negative result rather than y51's synthetic sweep.\nConclusion: the y51/xyu signal was substantially an artifact of the\nduplicated-interchangeable-code mechanism, not a real room-count effect.\nenable_ruin_recreate stays OFF. No further follow-up filed.\n\nNote en route: first draft of health-centre's room sizes auto-derived into\none 19-code interchange class (9o5's transitive chain) -- fixed by tiering\nroom widths with \u003e1.3x gaps at 3 boundaries into 3 bounded classes. Worth\nremembering for any future non-synthetic programme design.","status":"closed","priority":3,"issue_type":"task","assignee":"Bruno Postle","owner":"bruno@postle.net","created_at":"2026-07-29T09:07:48Z","created_by":"Bruno Postle","updated_at":"2026-07-30T07:07:09Z","started_at":"2026-07-29T14:05:00Z","closed_at":"2026-07-30T07:07:09Z","close_reason":"Closed","dependency_count":0,"dependent_count":0,"comment_count":0}
 {"id":"homemaker-py-e01","title":"Larger-N harbor-house sweep for c94 beam-width mean improvement","description":"homemaker-py-c94 measured construction_beam_width=4 vs 1 (greedy) end-to-end\non harbor-house at N=5 seeds, budget 1500, n_workers=1: 2 wins / 1 loss / 2\nties, mean fails 56.8 (bw=1) -\u003e 55.4 (bw=4). That's the same small-N,\nmixed-direction shape this log has repeatedly warned produces false signal\n(the \"8sh/1ph/qi6/lj3 pattern\" flagged in DESIGN.md section 23, f1d)\n-- a genuine loss (seed 5) sits alongside the two wins, and N=5 is far\nshort of what f1d's own larger-N confirmation needed (N=15/8) to separate\na real effect from noise.\n\nFollow-up: extend the harbor-house-only comparison to N=15+ seeds at the\nsame protocol (construction_beam_width=4 vs 1, budget 1500, n_workers=1,\ndriver.search from init.dom) to determine whether the mean-improvement\nlean is a real effect or an artefact of seed 2's outlier (67-\u003e52 fails).\nprogramme-house showed zero effect at any width/N tested and does not\nneed re-checking. See DESIGN.md section 29 for full methodology and the\nraw-seed-vs-end-to-end correction this follow-up builds on.","status":"closed","priority":3,"issue_type":"task","assignee":"Bruno Postle","owner":"bruno@postle.net","created_at":"2026-07-28T09:44:38Z","created_by":"Bruno Postle","updated_at":"2026-07-28T23:20:46Z","started_at":"2026-07-28T16:43:56Z","closed_at":"2026-07-28T23:20:46Z","close_reason":"Confirmed null at N=15 (Wilcoxon p=0.84); mean improvement was seed 2's outlier — see DESIGN.md §30","dependencies":[{"issue_id":"homemaker-py-e01","depends_on_id":"homemaker-py-c94","type":"related","created_at":"2026-07-28T10:45:16Z","created_by":"Bruno Postle","metadata":"{}"}],"dependency_count":0,"dependent_count":0,"comment_count":0}
 {"id":"homemaker-py-cdl","title":"Consider defaulting collapse_global local_search on + expose on evolve --collapse","description":"homemaker-py-9wi added Fitness._two_opt_adjacency_polish (2-opt swap search after the Jacobi adjacency fixpoint), gated behind collapse_global(local_search=True)/homemaker-collapse --local-search, default OFF. Empirical sweep over the 11 harbor-house .dom files: 0 regressions, 1 real improvement (evolved-anneal-3M.dom 21-\u003e19 fails, a genuine mutual-adjacency miss the Jacobi loop couldn't reach). Monotone by construction (only strictly-improving swaps kept) and cheap (\u003c1s on the largest file), so it looks safe to default on, but the sample is small (11 files, one non-synthetic dataset) and evolve.py's --collapse hook (driver.collapse_best) does not expose the flag at all yet. Before flipping the default: (1) run a broader sweep (programme-house + any other example sets) to confirm no regressions elsewhere, (2) add a --collapse-local-search passthrough to evolve.py's CLI alongside driver.collapse_best's **collapse_kw. Low priority -- collapse_finish's keep-better wrapper already makes the current opt-in flag safe to use standalone via homemaker-collapse.","status":"closed","priority":3,"issue_type":"task","assignee":"Bruno Postle","owner":"bruno@postle.net","created_at":"2026-07-26T19:57:32Z","created_by":"Bruno Postle","updated_at":"2026-07-26T22:32:24Z","started_at":"2026-07-26T22:20:41Z","closed_at":"2026-07-26T22:32:24Z","close_reason":"Ran a 46-file A/B sweep (local_search=False vs True in collapse_finish) across harbor-house (12 files) and programme-house (34 files): 0 regressions, 2 improvements (evolved-anneal-3M.dom 21-\u003e19, a82f07068e4408fdd0d5e3dc469a8dee.dom 3-\u003e2 fails), rest identical. Did NOT flip collapse_global's own default (still False) because it is also called every fitness eval via collapse_insearch (qpk) on the unmerged tree -- that hot per-eval path should stay cheap. Instead flipped the two one-shot finish-time call sites to default local_search=True explicitly: homemaker-collapse --local-search (collapse_cmd.py) and new homemaker-evolve --collapse-local-search (evolve.py, threaded through driver.collapse_best's **collapse_kw). All 298 tests pass.","dependency_count":0,"dependent_count":0,"comment_count":0}
@@ -98,27 +102,27 @@
 {"id":"homemaker-py-erc.6","title":"Experiment: inner-loop slack-expansion objective term","description":"Inner-loop counterpart to plot-fill construction. If Diagnostic B shows the inner loop has room to expand leaves into slack but no objective gradient to do so (the scalar rewards hitting target area but not exceeding it where slack exists), add a term/incentive so the ratio optimiser pushes leaf boundaries out to consume neighbouring slack and satisfy size, rather than parking at target.\n\nCONDITIONAL on Diagnostic B: build this only if B localizes the gap to the inner loop (room to expand, no gradient); if B shows construction targets too-small dims, prefer the plot-fill construction sibling. Must preserve the §5.4 inner-loop cliff / §4.9 lexicographic protection — the term sits where it cannot displace the fail-count ordering. A/B vs §12.2 baseline, seeds 0/1/2, 20000 evals, staged, default-OFF. Record DESIGN.md §13.6.","notes":"DEPRIORITISED by Diagnostic B (§13.2). B shows the inner loop CANNOT repair undersize: the slack is depth-driven maldistribution baked into the frozen topology, and the equal-offset ratio DOF cannot shrink a 14x leaf to feed a starved one without trading into shape fails (0.5^n cliff). Wrong DOF and wrong direction — the blocker is slicing POSITION, not a missing expansion reward. Fix belongs upstream in construction/topology (erc.4 re-scoped, erc.3). Keep as a low-priority follow-up only if a depth-balanced construction still leaves a residual size gradient the inner loop could pick up.","status":"closed","priority":4,"issue_type":"feature","owner":"bruno@postle.net","created_at":"2026-06-22T23:16:24Z","created_by":"Bruno Postle","updated_at":"2026-06-28T13:22:22Z","closed_at":"2026-06-28T13:22:22Z","close_reason":"wont-fix (DESIGN §13.7): Diag B (§13.2) showed the inner loop cannot repair undersize (wrong DOF — slicing position, frozen-topology ratios). Superseded by depth-balanced construction (erc.4). Condition unmet.","dependencies":[{"issue_id":"homemaker-py-erc.6","depends_on_id":"homemaker-py-erc","type":"parent-child","created_at":"2026-06-23T00:16:23Z","created_by":"Bruno Postle","metadata":"{}"},{"issue_id":"homemaker-py-erc.6","depends_on_id":"homemaker-py-erc.2","type":"blocks","created_at":"2026-06-23T00:16:47Z","created_by":"Bruno Postle","metadata":"{}"}],"dependency_count":1,"dependent_count":0,"comment_count":0}
 {"id":"homemaker-py-erc.5","title":"Experiment: compactness-aware cuts (minimize leaf perimeter/area)","description":"Attacks the #1 factor, crinkliness (346) — a per-leaf perimeter/area property DISTINCT from proportion (aspect ratio). Proportion-aware seeding (leu.2) sizes splits but does not bias toward balanced, square-ish subdivision. Add a KD-tree-style 'keep both children compact' cut rule (prefer the cut orientation/position that minimises summed child perimeter/area) in construction.\n\nCONDITIONAL on Diagnostic A: if A shows per-leaf shape-fail is FLAT across densities (floor intrinsic to slicing density), better cuts at the same leaf count will not pay → this should be closed wont-fix in favour of leaf-sharing. Only build if A shows shape-fail RISES with density. A/B vs §12.2 baseline, seeds 0/1/2, 20000 evals, staged, default-OFF. Record DESIGN.md §13.5.","notes":"DEPRIORITISED by erc.1 verdict (§13.1): per-leaf shape-fail flat vs slicing density and cuts already squarest (_size_divisions_from_targets picks squarest rotation) yet still ~1.8 fails/leaf =\u003e little compactness headroom at fixed leaf count. Floor is intrinsic to leaf COUNT, not cut quality. Revisit only if leaf-sharing (erc.3) underdelivers.","status":"closed","priority":4,"issue_type":"feature","owner":"bruno@postle.net","created_at":"2026-06-22T23:16:21Z","created_by":"Bruno Postle","updated_at":"2026-06-28T13:22:17Z","closed_at":"2026-06-28T13:22:17Z","close_reason":"wont-fix (DESIGN §13.7): Diag A (§13.1) showed the floor is intrinsic to leaf COUNT not cut quality; revisit condition was 'only if leaf-sharing underdelivers' but leaf-sharing OVER-delivered (−32…−39%, §13.3). Condition unmet.","dependencies":[{"issue_id":"homemaker-py-erc.5","depends_on_id":"homemaker-py-erc","type":"parent-child","created_at":"2026-06-23T00:16:21Z","created_by":"Bruno Postle","metadata":"{}"},{"issue_id":"homemaker-py-erc.5","depends_on_id":"homemaker-py-erc.1","type":"blocks","created_at":"2026-06-23T00:16:43Z","created_by":"Bruno Postle","metadata":"{}"}],"dependency_count":1,"dependent_count":0,"comment_count":0}
 {"id":"homemaker-py-2g5","title":"Rebuild occlusion/daylight/sun subsystem in Python (post-Phase-5, after optimisation fully native)","description":"DESIGN.md §6 port scope — a whole subsystem, not a term. quality_daylight (Leaf.pm:281-296) needs Urb::Misc::Sun + Urb::Field::Occlusion (+CIESky); quality_uncrinkliness also takes the occlusion object. Indoor spaces return 1 for daylight; cost is outdoor spaces + crinkliness. Port Sun_horizontal (262980-minute normalisation) and the occlusion wall set from Dom-\u003eWalls.","acceptance_criteria":"Daylight and crinkliness factors match Perl (float tolerance) across the corpus, including multi-storey cases","notes":"Re-scoped 2026-06-12: occlusion disabled in the Urb oracle instead of ported (see homemaker-py-gp2). Native fitness ships with simple crinkliness (illumination factor = 1, in homemaker-py-gnw). This issue is now the eventual Python occlusion rebuild, only after optimisation works entirely in Python. Restores outdoor-daylight and shaded-wall selection pressure.\nReframed 2026-06-17: orthogonal to epic homemaker-py-c4c. This is fitness FIDELITY (restoring daylight + shaded-wall selection pressure to match Perl), not search CAPABILITY — it changes what 'good' means, not the search's ability to find good. It will NOT improve final designs in the sense currently sought. Stays P4, deferred until the topology-search-quality epic lands and optimisation is fully native.","status":"open","priority":4,"issue_type":"feature","owner":"bruno@postle.net","created_at":"2026-06-11T23:38:25Z","created_by":"Bruno Postle","updated_at":"2026-06-17T19:14:48Z","dependency_count":0,"dependent_count":0,"comment_count":0}
-{"_type":"memory","key":"collapse-global-94g-and-any-label-usage-optimisation","value":"collapse_global (94g) and any label/usage optimisation CANNOT fix geometry-intrinsic fails. The harbor-house 15-fail best layout contains long-thin cells that are useless whatever room usage is assigned — their width/proportion/crinkliness fails are shape-bound, not label slack. Two consequences: (1) do not over-claim collapse gains — only ~2-3 of that layout's fails are reclaimable relabel slack, the rest are geometry- or building-level bound; (2) the threshold objective must not be tuned to 'pass' a degenerate cell via a permissive room type — a metric-pass on a physically useless space is gaming, not a fix. Real remedies for these are geometry/topology search (cell shape) and circulation placement, filed separately, not the collapse."}
-{"_type":"memory","key":"collapse-global-s-jacobi-adjacency-relaxation-homemaker-py","value":"collapse_global's Jacobi adjacency relaxation (homemaker-py-94g) is a synchronous per-round linear-assignment re-solve, which can 2-cycle indefinitely between two labellings that each satisfy ZERO adjacency requirements even though a permutation satisfying ALL of them exists -- proven on a minimal 4-cell chain (p1-q1-p2-q2, two disjoint adjacency pairs p1\u003c-\u003ep2/q1\u003c-\u003eq2) in test_two_opt_polish_escapes_jacobi_plateau. homemaker-py-9wi added Fitness._two_opt_adjacency_polish: a same-level pairwise-swap local search run after the Jacobi fixpoint, gated behind collapse_global(local_search=True) (default off, exposed as homemaker-collapse --local-search). Monotone by construction (a swap is kept only if it strictly increases total reward). Empirically on the 11 harbor-house evolved-*.dom/3m.dom/materialised-3M.dom layouts: 10 matched Jacobi-only exactly, 0 regressed, and evolved-anneal-3M.dom improved 21-\u003e19 fails (fixed a genuine mutual da1\u003c-\u003ek1 adjacency miss the Jacobi loop couldn't reach)."}
-{"_type":"memory","key":"multi-storey-staircase-consistency-when-dividing-or-retyping","value":"Multi-storey staircase consistency: when dividing or retyping a circulation (C) leaf at one level, the same structural change should be propagated to the matching leaf on ALL other storeys so the stair core path is maintained. The optimizer cannot fix staircase disruptions through trial-and-error geometry alone — it requires a synchronized multi-level operator that applies the same topology change to every storey simultaneously."}
-{"_type":"memory","key":"never-use-corpus-filenames-candidate-001-dom-candidate","value":"Never use corpus filenames (candidate-001.dom, candidate-002.dom, generated.dom, init.dom, etc.) as --output targets when running experiments. These are test fixtures. Always write experimental outputs to scratch/ or a timestamped path. Lesson from 2026-06-14: warm-start runs overwrote candidate-001/002.dom and broke graph tests."}
-{"_type":"memory","key":"strategy-decision-2026-06-12-bruno-occlusion-daylight","value":"Strategy decision 2026-06-12 (Bruno): occlusion/daylight is ORTHOGONAL to building a scalable optimiser. Disable it in Urb (env flag, homemaker-py-gp2) rather than port it; native fitness uses simple crinkliness (illumination factor = 1); rebuild occlusion in Python only after optimisation is fully native (homemaker-py-2g5, now P4). Consequence: all scores change when the flag flips — re-baseline corpus/.score, DESIGN \\$4.5 gains, gate bars at one clean boundary AFTER homemaker-py-1p0 closes; Phase-2 urb-evolve benchmark must run with the same flag."}
-{"_type":"memory","key":"deceptive-valleys-in-topology-search-when-every-single","value":"Deceptive valleys in topology search: when every single-step mutation from a target state passes through a high-fail intermediary (e.g. level_fix displaces a room into 5+ new fails), a compound operator that atomically applies two coordinated changes can escape. Design compound operators to land on the low-fail state directly, bypassing the deceptive gradient. Programme-house example: level_compound_fix atomically moves the level-constrained room AND re-inserts the displaced room adjacent to C in one step (operators.py, 2026-06-14)."}
-{"_type":"memory","key":"experiment-seeding-pitfall-run-search-scaled-py-s","value":"Experiment seeding pitfall: run_search_scaled.py's default PH_SEED (c964…dom) is a FINISHED programme-house design — passing it warm-starts and floors at ~3 fails, NOT a blank-slate topology search. For blank-slate runs comparable to §11.5/§11.6 baselines, seed from examples/programme-house/init.dom (a bare undivided plot; driver bootstrap auto-triggers only on bare plots). Bit the 6zy sweep — first pass used c964 and falsely showed 3-fail floor across the whole grid."}
-{"_type":"memory","key":"proportion-aware-constructive-seeding-leu-2-12-2","value":"Proportion-aware constructive seeding (leu.2/§12.2): sizing seed cuts from target AREAS only regresses (thin slivers wreck aspect); you must ALSO pick each cut's rotation for child squareness. It is a convergence ACCELERATOR via a deeper local optimum around the constructed topology: wins where that topology is roughly right and budget is scarce (harbor -13%, maple -10% at 20k evals) but DELAYS small programmes where the seed must be restructured by undivide (programme-house regresses at fixed budget, yet reaches the floor given budget - speed, not asymptote). Default-on. Also: n_storeys must honour storey_minimum, not just level: keys (programme-house storey_minimum:2, all rooms level:0 - was seeded 1 storey short; cq1)."}
-{"_type":"memory","key":"cli-tool-style-prefer-python-m-homemaker-module","value":"CLI tool style: prefer python -m homemaker.module --parameters pattern, installable via pip install -e . with pyproject.toml entry_points. Not standalone bin/ scripts."}
-{"_type":"memory","key":"ld2-13-6-interior-o-seed-diagnostic-all","value":"ld2/§13.6 interior-O seed diagnostic: ALL crinkliness fails in the constructed bal+share seed are UNDER-exposed (crink\u003c0.62, landlocked rooms with no facade + no uncovered-O neighbour) — zero over-exposed sliver fails. So the erc crinkliness residual is genuine under-daylighting, validating the interior light-well premise. Default outside_divisor=6 was too sparse (null: harbor 147-\u003e142, crinkliness even rose). odiv=3 is the seed-optimal joint setting: harbor seed fails 147-\u003e129 (-18), maple 219-\u003e206 (-14), landlocked fails drop, at cost of more leaves (harbor +4, maple +8). Because it ADDS leaves it carries the §13.4 wash-out risk; A/B to convergence pending."}
-{"_type":"memory","key":"unfold-strategy-for-shared-leaves-homemaker-py-8iv","value":"Unfold strategy for shared leaves (homemaker-py-8iv, resolved 2026-07-16): use the BALANCED GRID (operators._grow_balanced/_size_subtree_equal), NOT circulation-aware slicing. Slicing a shared leaf perpendicular to its access edge so every child touches the corridor was implemented + A/B-tested and LOST decisively (150k-eval warm-start polish from evolved-3M: slice 41 fails/3.5e-14 vs grid 25 fails/2.4e-09, grid ahead at every milestone). Reason: k rooms all touching one wall are intrinsically thin slices; that geometric debt (proportion/long/width) is unfixable without topology change, while the grid's squarer children let local search re-route access cheaply via level_retype/place_missing/level_fix. Lesson: at the sharing-\u003eno-sharing transition, prioritise squarer children and leave access to local search; do not reintroduce slicing in Schedule B (kpu)."}
-{"_type":"memory","key":"homemaker-py-pythonpath-set-pythonpath-home-bruno-src","value":"homemaker-layout PYTHONPATH: package installed as 'homemaker-layout' via pip install -e . so 'import homemaker_layout' works from anywhere without PYTHONPATH. For running tests use 'python -m pytest' from project root /home/bruno/src/homemaker-layout (pyproject.toml adds src/ automatically). Never try pip show homemaker — that's the old homemaker-addon conflict."}
-{"_type":"memory","key":"user-preference-bruno-this-is-a-fedora-system","value":"User preference (Bruno): this is a Fedora system — NEVER install Python packages via pip without asking first; always ask whether to install the rpm via dnf (e.g. python3-cma) before considering pip. Applies to any dependency additions."}
-{"_type":"memory","key":"homemaker-py-3l6-fix-leaf-sharing-evolve-runs","value":"homemaker-py-3l6 fix: leaf-sharing evolve runs now auto-finish before write via driver.polish_finish — unfold_shared_leaves() then a warm-started leaf_sharing=False polish search (--polish-budget, default budget//2). Makes the written .dom honest under canonical homemaker-fitness (internal==canonical when leaf_sharing off). Interrupt path forces polish_budget=0 (unfold+rescore only). This is yaa's unfold-then-polish, made automatic; Schedule B annealing is still kpu."}
-{"_type":"memory","key":"programme-house-optimisation-result-2026-06-14-15","value":"Programme-house optimisation result (2026-06-14/15): best achievable is 1 fail (l1 wrong level, score ~0.005). 0 fails is geometrically impossible: l1 (min 27m²) must occupy ll (~23m²) at level 0, which eliminates the t3-adj-C provider; dividing ll into lll(l1)+llr(C) gives llr proportion ~6:1 (fails). Python memetic optimizer achieves 1 fail in 50k evals vs Perl optimiser's 2-3 fails. Winning topology: TWO C nodes at level 0 — ll(C) for t3-adj-C via geometric contact, rl(C) for staircase via tree-sibling adjacency to rrr(O). Best .dom: scratch/from-warmstart-fixed.dom and scratch/from-compound3-fixed.dom."}
-{"_type":"memory","key":"correction-to-urb-fitness-bug-memory-bruno-2026","value":"CORRECTION to urb-fitness-bug memory (Bruno, 2026-06-12): 'C' is NOT a 'covered' type — Is_Covered is a geometric predicate (indoor space above). Urb's generic types are canonically UPPERCASE: C=circulation, O=outside, S=sahn (get_space_types qw/C O S/; corpus is 100% uppercase, never 'c'/'o' leaves). The mixed-case designs that fired the latent ratio_type first-match bug were created by homemaker's own operator type pool emitting lowercase 'c'/'o' — fixed: driver/operators now emit uppercase generics only, and class checks use t[0].lower() in 'cos'. The Urb class-sum patch stays as defensive hardening (zero impact on canonical designs). Native port (3y7/gnw): treat type classes case-insensitively, generics canonically uppercase."}
-{"_type":"memory","key":"experiment-harness-gotcha-the-leaf-sharing-relaxed-objective","value":"Experiment harness gotcha: the leaf-sharing RELAXED objective (§13.3) is injected ONLY by monkeypatching fitness.load_config in the parent process (run_staged_search.py / probe scripts). This is parent-process-only and does NOT propagate into ProcessPoolExecutor workers (n_workers\u003e1), which re-import fitness fresh and score under the STRICT on-disk patterns.config -\u003e r.n_fails MISMATCH (worker strict vs parent relaxed re-score). ALL §13.x floor runs were therefore SERIAL. Any future PARALLEL leaf-sharing experiment will silently mis-score until leaf_sharing lives on disk/CLI (tracked: homemaker-py-x3b). The parallel driver itself is correct; both paths score via load_config(programme_dir)."}
-{"_type":"memory","key":"run-to-run-reproducibility-in-homemaker-layout-serial","value":"Run-to-run reproducibility in homemaker-layout: serial search (workers=1) is byte-for-byte deterministic; parallel (workers\u003e1) is now deterministic too AFTER fixing driver._run_batch to admit futures in submission order (was as_completed/completion order, bug xcy). Reproducibility holds only for a FIXED worker count — serial vs parallel differ because children-per-iteration is 1 vs n_workers (different batch granularity), which is expected, not a bug. The constructive seeder was NEVER nondeterministic: _assign_adjacency_aware has unique idx tiebreaks; comparing topologies with Python builtin hash() of the signature STRING is invalid (PYTHONHASHSEED salts str hashing per process) — use a stable hash (sha1) or genome.signature equality."}
-{"_type":"memory","key":"urb-oracle-nondeterminism-urb-fitness-pl-output-varies","value":"Urb oracle nondeterminism: urb-fitness.pl output varies run-to-run from Perl hash-order randomisation — .fails line ORDER shuffles (compare sorted, use oracle.Score.fail_lines) and the score float can flip by ~1 ULP (compare with math.isclose rel_tol=1e-12, never ==). Not a batching artifact; affects single runs too. Matters for the Phase 3 native-fitness parity gate (homemaker-py-uxz)."}
-{"_type":"memory","key":"warm-x0-initialization-bug-pattern-when-a-topology","value":"warm_x0 initialization bug pattern: when a topology operator explicitly sets division ratios on a newly-created node (e.g. compound_fix sets node.division=[0.25,0.25] for t3), parent.ratios has no entry for that node (it was a leaf). warm_x0 defaults it to 0.5, corrupting the inner loop's starting point and making the operator invisible to lex comparison. Fix: only propagate child ratios for nodes where the parent node was NOT already divided; stale hidden nodes revealed by structural mutations (swap flipping b.below) must NOT contribute their pre-writeback values. See driver.py lines 259-267 (fixed 2026-06-14)."}
 {"_type":"memory","key":"9o5-multi-use-leaves-is-path-a-superposition","value":"9o5 multi-use leaves is path (a) — superposition as SEARCH RELAXATION that COLLAPSES to specific usage at the end, NOT path (b) loose-fit/no-collapse. Bruno's intent: codes with SIMILAR leaf requirements form an interchangeable equivalence class; during evolution the solver doesn't commit which leaf serves which specific usage (smoother landscape, no fighting over exact leaf usage); at the end the layout is CONDENSED to specific usages by brute-forcing the in-class assignment (3 interchangeable usages over 3 leaves = 3! = 6 combinations to check, pick best). 'Derive automatically' compatibility = requirement-similarity grouping. This reverses the issue's stated 'path b preferred' note."}
-{"_type":"memory","key":"adjacency-in-binary-slicing-tree-is-structural-not","value":"Adjacency in binary slicing tree is structural, not geometric: the inner-loop NM cannot fix topological adjacency failures. Two paths exist: (1) tree-sibling adjacency — a node is adjacent to its sibling in the tree; (2) cross-zone geometric adjacency — leaves from different subtrees that happen to share a boundary. Staircase/adjacency fails require a topology mutation that changes which nodes are siblings or which zones touch. This was proved empirically on programme-house: staircase fail from rot=0 layout could not be fixed by NM but was fixed by level_retype creating a two-C topology (2026-06-14/15)."}
-{"_type":"memory","key":"island-model-psk-14-is-a-null-priming","value":"Island model (psk, §14) is a NULL: priming a population from N converged independent elites + crossover-heavy migration does not beat best-of-N at equal total budget (maple island 124 vs control 116). The child_probe instrument shows WHY: area-matched crossover across independently-converged elites almost never synthesizes (1-3 of ~64 children beat the better parent, max drop 2-5) because the slicing encoding is non-canonical (9gp), so splices are disruptive not combinatorial. Search-machinery null #3 after graded-objective and niching/restarts; residual stays geometry/shape-bound."}
+{"_type":"memory","key":"never-use-corpus-filenames-candidate-001-dom-candidate","value":"Never use corpus filenames (candidate-001.dom, candidate-002.dom, generated.dom, init.dom, etc.) as --output targets when running experiments. These are test fixtures. Always write experimental outputs to scratch/ or a timestamped path. Lesson from 2026-06-14: warm-start runs overwrote candidate-001/002.dom and broke graph tests."}
+{"_type":"memory","key":"collapse-global-s-jacobi-adjacency-relaxation-homemaker-py","value":"collapse_global's Jacobi adjacency relaxation (homemaker-py-94g) is a synchronous per-round linear-assignment re-solve, which can 2-cycle indefinitely between two labellings that each satisfy ZERO adjacency requirements even though a permutation satisfying ALL of them exists -- proven on a minimal 4-cell chain (p1-q1-p2-q2, two disjoint adjacency pairs p1\u003c-\u003ep2/q1\u003c-\u003eq2) in test_two_opt_polish_escapes_jacobi_plateau. homemaker-py-9wi added Fitness._two_opt_adjacency_polish: a same-level pairwise-swap local search run after the Jacobi fixpoint, gated behind collapse_global(local_search=True) (default off, exposed as homemaker-collapse --local-search). Monotone by construction (a swap is kept only if it strictly increases total reward). Empirically on the 11 harbor-house evolved-*.dom/3m.dom/materialised-3M.dom layouts: 10 matched Jacobi-only exactly, 0 regressed, and evolved-anneal-3M.dom improved 21-\u003e19 fails (fixed a genuine mutual da1\u003c-\u003ek1 adjacency miss the Jacobi loop couldn't reach)."}
+{"_type":"memory","key":"programme-house-optimisation-result-2026-06-14-15","value":"Programme-house optimisation result (2026-06-14/15): best achievable is 1 fail (l1 wrong level, score ~0.005). 0 fails is geometrically impossible: l1 (min 27m²) must occupy ll (~23m²) at level 0, which eliminates the t3-adj-C provider; dividing ll into lll(l1)+llr(C) gives llr proportion ~6:1 (fails). Python memetic optimizer achieves 1 fail in 50k evals vs Perl optimiser's 2-3 fails. Winning topology: TWO C nodes at level 0 — ll(C) for t3-adj-C via geometric contact, rl(C) for staircase via tree-sibling adjacency to rrr(O). Best .dom: scratch/from-warmstart-fixed.dom and scratch/from-compound3-fixed.dom."}
+{"_type":"memory","key":"deceptive-valleys-in-topology-search-when-every-single","value":"Deceptive valleys in topology search: when every single-step mutation from a target state passes through a high-fail intermediary (e.g. level_fix displaces a room into 5+ new fails), a compound operator that atomically applies two coordinated changes can escape. Design compound operators to land on the low-fail state directly, bypassing the deceptive gradient. Programme-house example: level_compound_fix atomically moves the level-constrained room AND re-inserts the displaced room adjacent to C in one step (operators.py, 2026-06-14)."}
+{"_type":"memory","key":"experiment-harness-gotcha-the-leaf-sharing-relaxed-objective","value":"Experiment harness gotcha: the leaf-sharing RELAXED objective (§13.3) is injected ONLY by monkeypatching fitness.load_config in the parent process (run_staged_search.py / probe scripts). This is parent-process-only and does NOT propagate into ProcessPoolExecutor workers (n_workers\u003e1), which re-import fitness fresh and score under the STRICT on-disk patterns.config -\u003e r.n_fails MISMATCH (worker strict vs parent relaxed re-score). ALL §13.x floor runs were therefore SERIAL. Any future PARALLEL leaf-sharing experiment will silently mis-score until leaf_sharing lives on disk/CLI (tracked: homemaker-py-x3b). The parallel driver itself is correct; both paths score via load_config(programme_dir)."}
+{"_type":"memory","key":"homemaker-py-pythonpath-set-pythonpath-home-bruno-src","value":"homemaker-layout PYTHONPATH: package installed as 'homemaker-layout' via pip install -e . so 'import homemaker_layout' works from anywhere without PYTHONPATH. For running tests use 'python -m pytest' from project root /home/bruno/src/homemaker-layout (pyproject.toml adds src/ automatically). Never try pip show homemaker — that's the old homemaker-addon conflict."}
+{"_type":"memory","key":"strategy-decision-2026-06-12-bruno-occlusion-daylight","value":"Strategy decision 2026-06-12 (Bruno): occlusion/daylight is ORTHOGONAL to building a scalable optimiser. Disable it in Urb (env flag, homemaker-py-gp2) rather than port it; native fitness uses simple crinkliness (illumination factor = 1); rebuild occlusion in Python only after optimisation is fully native (homemaker-py-2g5, now P4). Consequence: all scores change when the flag flips — re-baseline corpus/.score, DESIGN \\$4.5 gains, gate bars at one clean boundary AFTER homemaker-py-1p0 closes; Phase-2 urb-evolve benchmark must run with the same flag."}
 {"_type":"memory","key":"urb-fitness-bug-found-fixed-2026-06-12","value":"Urb fitness bug found+fixed 2026-06-12 (patch in /home/bruno/src/urb, uncommitted): ProgrammeDriven.pm ratio_o/ratio_type grepped case-insensitively over the ratios hash and took the FIRST key — nondeterministic (x4.5 score swings) for designs with mixed-case type classes (both 'c' circulation and 'C' covered). Fixed to SUM the class (matches Is_Circulation//Is_Outside semantics); 35/35 corpus scores unchanged. CRITICAL for homemaker-py-3y7/gnw: the native port must implement class-SUM ratios. Building.pm has the same unpatched pattern (site-driven path, not used by our oracle). Also: the memetic search reward-hacked this bug before the fix — search results predating it are noise artifacts."}
+{"_type":"memory","key":"correction-to-urb-fitness-bug-memory-bruno-2026","value":"CORRECTION to urb-fitness-bug memory (Bruno, 2026-06-12): 'C' is NOT a 'covered' type — Is_Covered is a geometric predicate (indoor space above). Urb's generic types are canonically UPPERCASE: C=circulation, O=outside, S=sahn (get_space_types qw/C O S/; corpus is 100% uppercase, never 'c'/'o' leaves). The mixed-case designs that fired the latent ratio_type first-match bug were created by homemaker's own operator type pool emitting lowercase 'c'/'o' — fixed: driver/operators now emit uppercase generics only, and class checks use t[0].lower() in 'cos'. The Urb class-sum patch stays as defensive hardening (zero impact on canonical designs). Native port (3y7/gnw): treat type classes case-insensitively, generics canonically uppercase."}
+{"_type":"memory","key":"experiment-seeding-pitfall-run-search-scaled-py-s","value":"Experiment seeding pitfall: run_search_scaled.py's default PH_SEED (c964…dom) is a FINISHED programme-house design — passing it warm-starts and floors at ~3 fails, NOT a blank-slate topology search. For blank-slate runs comparable to §11.5/§11.6 baselines, seed from examples/programme-house/init.dom (a bare undivided plot; driver bootstrap auto-triggers only on bare plots). Bit the 6zy sweep — first pass used c964 and falsely showed 3-fail floor across the whole grid."}
+{"_type":"memory","key":"island-model-psk-14-is-a-null-priming","value":"Island model (psk, §14) is a NULL: priming a population from N converged independent elites + crossover-heavy migration does not beat best-of-N at equal total budget (maple island 124 vs control 116). The child_probe instrument shows WHY: area-matched crossover across independently-converged elites almost never synthesizes (1-3 of ~64 children beat the better parent, max drop 2-5) because the slicing encoding is non-canonical (9gp), so splices are disruptive not combinatorial. Search-machinery null #3 after graded-objective and niching/restarts; residual stays geometry/shape-bound."}
+{"_type":"memory","key":"urb-oracle-nondeterminism-urb-fitness-pl-output-varies","value":"Urb oracle nondeterminism: urb-fitness.pl output varies run-to-run from Perl hash-order randomisation — .fails line ORDER shuffles (compare sorted, use oracle.Score.fail_lines) and the score float can flip by ~1 ULP (compare with math.isclose rel_tol=1e-12, never ==). Not a batching artifact; affects single runs too. Matters for the Phase 3 native-fitness parity gate (homemaker-py-uxz)."}
+{"_type":"memory","key":"cli-tool-style-prefer-python-m-homemaker-module","value":"CLI tool style: prefer python -m homemaker.module --parameters pattern, installable via pip install -e . with pyproject.toml entry_points. Not standalone bin/ scripts."}
+{"_type":"memory","key":"homemaker-py-3l6-fix-leaf-sharing-evolve-runs","value":"homemaker-py-3l6 fix: leaf-sharing evolve runs now auto-finish before write via driver.polish_finish — unfold_shared_leaves() then a warm-started leaf_sharing=False polish search (--polish-budget, default budget//2). Makes the written .dom honest under canonical homemaker-fitness (internal==canonical when leaf_sharing off). Interrupt path forces polish_budget=0 (unfold+rescore only). This is yaa's unfold-then-polish, made automatic; Schedule B annealing is still kpu."}
+{"_type":"memory","key":"ld2-13-6-interior-o-seed-diagnostic-all","value":"ld2/§13.6 interior-O seed diagnostic: ALL crinkliness fails in the constructed bal+share seed are UNDER-exposed (crink\u003c0.62, landlocked rooms with no facade + no uncovered-O neighbour) — zero over-exposed sliver fails. So the erc crinkliness residual is genuine under-daylighting, validating the interior light-well premise. Default outside_divisor=6 was too sparse (null: harbor 147-\u003e142, crinkliness even rose). odiv=3 is the seed-optimal joint setting: harbor seed fails 147-\u003e129 (-18), maple 219-\u003e206 (-14), landlocked fails drop, at cost of more leaves (harbor +4, maple +8). Because it ADDS leaves it carries the §13.4 wash-out risk; A/B to convergence pending."}
+{"_type":"memory","key":"user-preference-bruno-this-is-a-fedora-system","value":"User preference (Bruno): this is a Fedora system — NEVER install Python packages via pip without asking first; always ask whether to install the rpm via dnf (e.g. python3-cma) before considering pip. Applies to any dependency additions."}
+{"_type":"memory","key":"adjacency-in-binary-slicing-tree-is-structural-not","value":"Adjacency in binary slicing tree is structural, not geometric: the inner-loop NM cannot fix topological adjacency failures. Two paths exist: (1) tree-sibling adjacency — a node is adjacent to its sibling in the tree; (2) cross-zone geometric adjacency — leaves from different subtrees that happen to share a boundary. Staircase/adjacency fails require a topology mutation that changes which nodes are siblings or which zones touch. This was proved empirically on programme-house: staircase fail from rot=0 layout could not be fixed by NM but was fixed by level_retype creating a two-C topology (2026-06-14/15)."}
+{"_type":"memory","key":"multi-storey-staircase-consistency-when-dividing-or-retyping","value":"Multi-storey staircase consistency: when dividing or retyping a circulation (C) leaf at one level, the same structural change should be propagated to the matching leaf on ALL other storeys so the stair core path is maintained. The optimizer cannot fix staircase disruptions through trial-and-error geometry alone — it requires a synchronized multi-level operator that applies the same topology change to every storey simultaneously."}
+{"_type":"memory","key":"warm-x0-initialization-bug-pattern-when-a-topology","value":"warm_x0 initialization bug pattern: when a topology operator explicitly sets division ratios on a newly-created node (e.g. compound_fix sets node.division=[0.25,0.25] for t3), parent.ratios has no entry for that node (it was a leaf). warm_x0 defaults it to 0.5, corrupting the inner loop's starting point and making the operator invisible to lex comparison. Fix: only propagate child ratios for nodes where the parent node was NOT already divided; stale hidden nodes revealed by structural mutations (swap flipping b.below) must NOT contribute their pre-writeback values. See driver.py lines 259-267 (fixed 2026-06-14)."}
+{"_type":"memory","key":"run-to-run-reproducibility-in-homemaker-layout-serial","value":"Run-to-run reproducibility in homemaker-layout: serial search (workers=1) is byte-for-byte deterministic; parallel (workers\u003e1) is now deterministic too AFTER fixing driver._run_batch to admit futures in submission order (was as_completed/completion order, bug xcy). Reproducibility holds only for a FIXED worker count — serial vs parallel differ because children-per-iteration is 1 vs n_workers (different batch granularity), which is expected, not a bug. The constructive seeder was NEVER nondeterministic: _assign_adjacency_aware has unique idx tiebreaks; comparing topologies with Python builtin hash() of the signature STRING is invalid (PYTHONHASHSEED salts str hashing per process) — use a stable hash (sha1) or genome.signature equality."}
+{"_type":"memory","key":"unfold-strategy-for-shared-leaves-homemaker-py-8iv","value":"Unfold strategy for shared leaves (homemaker-py-8iv, resolved 2026-07-16): use the BALANCED GRID (operators._grow_balanced/_size_subtree_equal), NOT circulation-aware slicing. Slicing a shared leaf perpendicular to its access edge so every child touches the corridor was implemented + A/B-tested and LOST decisively (150k-eval warm-start polish from evolved-3M: slice 41 fails/3.5e-14 vs grid 25 fails/2.4e-09, grid ahead at every milestone). Reason: k rooms all touching one wall are intrinsically thin slices; that geometric debt (proportion/long/width) is unfixable without topology change, while the grid's squarer children let local search re-route access cheaply via level_retype/place_missing/level_fix. Lesson: at the sharing-\u003eno-sharing transition, prioritise squarer children and leave access to local search; do not reintroduce slicing in Schedule B (kpu)."}
+{"_type":"memory","key":"collapse-global-94g-and-any-label-usage-optimisation","value":"collapse_global (94g) and any label/usage optimisation CANNOT fix geometry-intrinsic fails. The harbor-house 15-fail best layout contains long-thin cells that are useless whatever room usage is assigned — their width/proportion/crinkliness fails are shape-bound, not label slack. Two consequences: (1) do not over-claim collapse gains — only ~2-3 of that layout's fails are reclaimable relabel slack, the rest are geometry- or building-level bound; (2) the threshold objective must not be tuned to 'pass' a degenerate cell via a permissive room type — a metric-pass on a physically useless space is gaming, not a fix. Real remedies for these are geometry/topology search (cell shape) and circulation placement, filed separately, not the collapse."}
+{"_type":"memory","key":"proportion-aware-constructive-seeding-leu-2-12-2","value":"Proportion-aware constructive seeding (leu.2/§12.2): sizing seed cuts from target AREAS only regresses (thin slivers wreck aspect); you must ALSO pick each cut's rotation for child squareness. It is a convergence ACCELERATOR via a deeper local optimum around the constructed topology: wins where that topology is roughly right and budget is scarce (harbor -13%, maple -10% at 20k evals) but DELAYS small programmes where the seed must be restructured by undivide (programme-house regresses at fixed budget, yet reaches the floor given budget - speed, not asymptote). Default-on. Also: n_storeys must honour storey_minimum, not just level: keys (programme-house storey_minimum:2, all rooms level:0 - was seeded 1 storey short; cq1)."}