mind: sweep draft/ for shipped work — 11 prompts recorded complete, 9 unblocked

complete/2026/07/latent-samples-none-on-resumed-fit.md

@@ -0,0 +1,87 @@
+# latent-samples-none-on-resumed-fit
+
+- shipped: 2026-07-25 (the same day the prompt recorded the finding)
+- library-pr: https://github.com/PyAutoLabs/PyAutoFit/pull/1418 (merged) — "fix: raise SamplesException from latent computation when samples is None (resumed fits)"
+- repos:
+  - PyAutoFit
+
+## Summary
+
+The prompt was filed from the 2026-07-25 full health sweep and fixed upstream the
+same day. Nothing in PyAutoMind recorded it, so the prompt sat in `draft/` for two
+weeks looking like open work.
+
+Recorded 2026-08-09 by the draft/ sweep. No work is owed.
+
+## Verified against PyAutoFit main (`3b960609`), 2026-08-09
+
+The prompt's § Task offers two options — (a) reload persisted samples on the
+resume path, or (b) raise a clear guarded error. **Option (b) is what landed**,
+and its § Acceptance is met exactly: "either computes latent samples or fails with
+an intentional, documented message — never an `AttributeError` from inside
+`latent_samples_from`."
+
+`autofit/non_linear/analysis/latent.py` now opens `latent_samples_from` with an
+explicit `if samples is None:` guard raising `exc.SamplesException`, and the
+message names the cause and both remedies — samples output disabled via
+`output.yaml`'s `samples: false` or `general.yaml`'s `samples_to_csv: false`, so
+`result.samples` comes back `None` on the reload; enable samples output and re-run
+from cleared output, or pass a `Samples` object explicitly. It also states why
+`samples_summary.json` is not a substitute (latents are per-posterior-sample).
+
+The function's `Raises` docstring carries the same diagnosis the prompt reached
+independently — that a completed fit short-circuits to
+`NonLinearSearch.result_via_completed_fit`, which reloads from `samples.csv`.
+
+The prompt's open sub-question ("May be test-mode-specific — check whether a real
+non-bypass resumed fit also returns samples=None") was answered by the fix taking
+the general path: the guard is unconditional, not gated on `PYAUTO_TEST_MODE`.
+
+## Why it was missed
+
+This is the one class of drift the Mind cannot see by itself. Unlike the
+PyAutoArray k×s finding, there is **no completion record for #1418 anywhere in
+`complete/`** — the fix went in upstream without a Mind entry, so no amount of
+cross-referencing draft prompts against the ledger would surface it. Only reading
+the prompt's acceptance criteria against the upstream tree finds this shape.
+
+## Original prompt
+# compute_latent_samples crashes on a resumed completed fit (samples is None)
+
+Type: bug
+Target: autofit
+Repos:
+- @PyAutoFit
+Difficulty: medium
+Autonomy: supervised
+Priority: low
+Status: draft
+
+## Finding (2026-07-25 full health sweep)
+
+Running `autolens_workspace_test` `misc/latent/latent_variables_smoke.py` (and
+`latent_nan_robustness.py`) twice in the same output tree fails on the second
+run: the search resumes ("Fit Already Completed: skipping non-linear search"),
+`result.samples` comes back `None` on the resume path (PYAUTO_TEST_MODE=2
+bypass), and
+
+    autofit/non_linear/analysis/latent.py:113  latent_samples_from
+    -> samples.model  ->  AttributeError: 'NoneType' object has no attribute 'model'
+
+A fresh run (output cleared) passes. So the latent pipeline works, but the
+resume/load path hands `compute_latent_samples` a `None` samples object
+instead of the persisted samples (or a clear error).
+
+## Task
+
+Determine whether the resume path should (a) reload persisted samples so
+latent computation works on resumed results, or (b) raise a clear, guarded
+error from `compute_latent_samples` when samples are unavailable. May be
+test-mode-specific — check whether a real (non-bypass) resumed fit also
+returns samples=None.
+
+## Acceptance
+
+Second invocation of the latent smoke scripts in an existing output tree
+either computes latent samples or fails with an intentional, documented
+message — never an AttributeError from inside latent_samples_from.

draft/feature/autoarray/oversampling_kxs_coupling.md → complete/2026/07/oversampling-kxs-coupling.md

@@ -1,3 +1,74 @@
+# oversampling-kxs-coupling
+
+- shipped: 2026-07-09 (series closed; the prompt never left `draft/`)
+- issue: https://github.com/PyAutoLabs/PyAutoArray/issues/362 (CLOSED — "series complete")
+- prs: PyAutoArray#363, #364, #365 · PyAutoGalaxy#486, #489 · autolens_workspace#236 · autolens_workspace_test#154 (all merged)
+- repos:
+  - PyAutoArray, PyAutoGalaxy
+  - autolens_workspace, autolens_workspace_test
+- phase-records: [[kxs-design]] [[kxs-core]] [[kxs-cache]] [[kxs-workspace-tests]] [[kxs-refactor]] [[kxs-surface-refactor]]
+
+## Summary
+
+This is the **source prompt** for the k×s coupling series — the five-phase plan
+it lays out was executed in full over 2026-07-08/09 and the series tracker
+PyAutoArray#362 was closed as "series complete". Six dated completion records
+already existed for the individual phases; only the prompt they all came from
+was never advanced out of `draft/feature/autoarray/`.
+
+Recorded 2026-08-09 by the draft/ sweep. No work is owed.
+
+## Verified against PyAutoArray main (`efaf3041`), 2026-08-09
+
+Graded against the prompt's own § Scope, not inferred from the phase records:
+
+1. **§1 relax the coupling rule — SHIPPED.**
+   `_validate_convolve_over_sample_size` (`autoarray/dataset/imaging/dataset.py:23`)
+   accepts any `over_sample_size` (int or adaptive `Array2D`) whose every entry
+   is divisible by `convolve_over_sample_size`, and raises `DatasetException`
+   naming the rule otherwise. Its docstring states the mechanism in the prompt's
+   own words — "the k x s coupling, whereby values evaluated at per-pixel sizes
+   k_i * s are partially binned to the uniform s the convolution requires".
+   The pre-change equality rule is gone.
+
+2. **§2 partial pre-bin — SHIPPED**, as
+   `over_sample_util.binned_to_convolve_size_from`
+   (`autoarray/operators/over_sampling/over_sample_util.py:205`). The placement
+   fork the prompt required a design paragraph for was settled and is recorded in
+   [[kxs-design]]. Covered by `test_over_sample_util.py` on both legs the prompt
+   asked for — `binned_to_convolve_size_from__uniform_k__equals_manual_reshape_mean`
+   and `__adaptive_k__and_identity_fast_path`.
+
+3. **§3 PyAutoGalaxy callers — SHIPPED** via PyAutoGalaxy#486 ([[kxs-core]]).
+
+4. **§4 tests — SHIPPED.** Library numpy-only tests as above; the
+   `convolution_over_sampled.py` adaptive + s=2 `FitImaging` leg the prompt
+   specifies landed as autolens_workspace_test#154 ([[kxs-workspace-tests]]:
+   lp round trip chi2=0, adaptive pixelized 6.6e-5, divisibility guard,
+   adaptive simulate→fit 1.1e-29).
+
+5. **§5 simulator adoption — DELIBERATELY RE-SCOPED, not skipped.**
+   [[kxs-core]] records the fork resolved as option (c): executed simulators stay
+   at `s=1`, and option (a) was split out as
+   `draft/feature/autolens_workspace/oversampled_psf_dataset_adoption.md`. That
+   prompt is correctly still a live draft — it is the residue of this §5, and is
+   NOT covered by this record.
+
+6. **Phase-5 refactor exercise — SHIPPED** as PyAutoGalaxy#489
+   ([[kxs-surface-refactor]]), plus the extra [[kxs-cache]] and [[kxs-refactor]]
+   legs the series added on top of the original plan.
+
+## Why it was missed
+
+Nothing upstream drifted — the trackers were right the whole time, exactly as in
+the 2026-08-08 `planned.md` prune. The prompt is stale purely because `draft/` is
+graded by no check, and slug-similarity is too weak to catch it: this file's stem
+against `kxs-core` scores a Jaccard of 0.25, well under any workable threshold.
+What found it was reading the prompt's acceptance criteria against the tree — and
+it was provable from PyAutoMind alone, since the six phase records were already
+sitting in `complete/2026/07/`.
+
+## Original prompt
 # Oversampled PSF: k×s evaluation/convolution coupling + simulator adoption
 
 Type: feature

draft/feature/autoarray/rectangular_adapt_constant_split_guard.md → complete/2026/07/rectangular-adapt-constant-split-guard.md

@@ -1,3 +1,80 @@
+# rectangular-adapt-constant-split-guard
+
+- shipped: 2026-07-28 (phase 1 of the @rhayes777 audit epic; the prompt never left `draft/`)
+- epic: https://github.com/PyAutoLabs/PyAutoArray/issues/415 (open — phases 2-4 remain)
+- issue: https://github.com/PyAutoLabs/PyAutoArray/issues/332 (the reporter's finding), tracker #416 closed
+- prs: PyAutoArray#417 (`9411904d`) + PyAutoLens#662 (`2a3f1a63`), both merged
+- repos:
+  - PyAutoArray
+- see-also: `draft/bug/autoarray/rhayes_audit_validation_and_crashes.md` § "Phase 1 completion record — 2026-07-28"
+
+## Summary
+
+A duplicate prompt for work that shipped as phase 1 of the @rhayes777 API-audit
+epic. The Mind already held the completion record — inside the *sibling* prompt
+`rhayes_audit_validation_and_crashes.md`, which planned.md tracks — but this
+second, independently-filed prompt for the same surface never learned about it.
+
+Recorded 2026-08-09 by the draft/ sweep. No work is owed on the library leg;
+one leg of the prompt's § Verification is noted below as unconfirmed.
+
+## Verified against PyAutoArray main (`efaf3041`), 2026-08-09
+
+The prompt asks for "an explicit validation guard which rejects this unsupported
+configuration early, with an error message that tells users what to do instead".
+That guard is on main:
+
+- **Guard**: `Pixelization.__init__` (`autoarray/inversion/pixelization.py:154`)
+  raises `exc.PixelizationException` when a split regularization meets a mesh
+  that does not support it. The message names both classes and tells the user
+  the two ways out — an adaptive mesh (`Delaunay`/`KNNBarycentric`) with the same
+  regularization, or a non-split scheme (`Constant` for `ConstantSplit`, `Adapt`
+  for `AdaptSplit`) with the same mesh. Substantively the prompt's suggested text.
+- **Mechanism**: two capability flags rather than a type blacklist —
+  `AbstractMesh.supports_split_regularization` (default `True`, set `False` on
+  the rectangular family) × `AbstractRegularization.is_split_regularization`
+  (default `False`, set `True` on `ConstantSplit`/`AdaptSplit`/`AdaptSplitZeroth`).
+- **The false pass-through is gone**: `InterpolatorRectangular`'s claim that split
+  "reuses the same mappings" — the source of the `IndexError: index 4 is out of
+  bounds for axis 0 with size 4` this prompt reproduces — no longer stands;
+  `interpolator/rectangular.py:466` now records that the combination is rejected
+  at construction instead.
+
+Against the prompt's § Verification:
+
+1. **Criterion 1 (concrete construction raises) — MET.**
+   `test_autoarray/inversion/pixelization/test_split_regularization_support.py`
+   parametrizes all **9** rectangular × split combinations (the prompt reported
+   1) and asserts both class names appear in the message.
+2. **Criterion 2 (`af.Model` composition form fails before Nautilus starts) —
+   NOT CONFIRMED.** The guard sits in `Pixelization.__init__`, so it fires
+   whenever the model is instantiated rather than at composition time. A search
+   for `supports_split_regularization` in PyAutoLens returns nothing, so no
+   separate pre-fit model-inspection guard was added. In practice the concrete
+   guard is reached on the first instantiation, which is early — but that this
+   precedes sampling was not verified here and would need a run to settle. The
+   prompt itself allowed this ordering ("add the concrete PyAutoArray guard
+   first and add a companion AutoLens / analysis guard where the prior model can
+   be inspected"), so this is a possible residue, not a regression.
+3. **Criterion 3 (allowed combinations still work) — MET.** Rectangular +
+   `Constant`, adaptive + split, and rectangular + no regularization all have
+   passing parametrized tests.
+4. **Criterion 4 (low-level regression test) — MET in the form the fix took.**
+   Because the capability is deliberately absent rather than repaired, the tests
+   assert the *clear failure*; the test module says so explicitly. The prompt's
+   "do not paper over this by clipping indices" instruction was honoured.
+
+## Why it was missed
+
+Two prompts described one surface. `rhayes_audit_validation_and_crashes.md` came
+in through the audit and is tracked by `planned.md`, so it was updated when phase
+1 shipped; this one came in separately from a user repro
+(`z_help/jacob/HerBS-28…`) and, sitting in `draft/`, was graded by nothing. The
+related `draft/feature/autoarray/regularization_jax_gradient_gaps.md` § 3 flagged
+the same surface a third time and asked "merge at intake if so" — that merge is
+now moot, and its leg 3 has been marked done in place.
+
+## Original prompt
 # Users keep combining `RectangularAdaptDensity` meshes with `ConstantSplit`
 
 Type: feature

draft/feature/autofit/test_mode_representative_outputs_size_realistic.md → complete/2026/07/test-mode-representative-outputs-size-realistic.md

@@ -1,3 +1,45 @@
+# test-mode-representative-outputs-size-realistic
+
+- shipped: 2026-07-17 (the epic's own closing condition was met and never actioned)
+- issues: PyAutoFit#1378 (phase 1), PyAutoFit#1381 + PyAutoConf#126 (phase 2), autolens_profiling#70 (the closing gate — CLOSED as `completed` 2026-07-17)
+- phase-records: [[test-mode-representative-samples-phase-1-design]] [[test-mode-representative-samples-phase-2-core-api]]
+- repos:
+  - PyAutoFit, PyAutoConf (now PyAutoNerves), autolens_profiling
+
+## Summary
+
+An umbrella prompt whose four phases were all resolved, tracked in the prompt's
+own status line, and whose stated exit condition then quietly came true.
+
+The prompt is explicit that it is the umbrella — *"issue the phase files, not this
+one"* — and its 2026-07-17 status block already recorded:
+
+- phase 1 (design) **COMPLETE**, PyAutoFit#1378, record in `complete/2026/07/`
+- phase 2 (core API) **COMPLETE + MERGED**, PyAutoConf#126 + PyAutoFit#1381
+- phase 3 **ABSORBED** into slam-resume-profiling (autolens_profiling#70), prompt retired
+- phase 4 **ABSORBED** (survey found RTD has no test-mode surface), prompt retired
+- *"EPIC CLOSES when #70 ships its recipe leg."*
+
+## Verified 2026-08-09
+
+**autolens_profiling#70 is closed, `state_reason: completed`, closed 2026-07-17 by
+Jammy2211** — the same day the prompt's status block was last written. So the only
+outstanding condition the umbrella named was satisfied within hours of the note
+being taken, and nothing advanced the file.
+
+Recorded by the draft/ sweep. No work is owed.
+
+## Why it was missed
+
+This one needed neither a clone nor a code read — the prompt states its own exit
+condition, and one issue-state lookup settles it. That makes it the cheapest class
+of draft/ drift to detect and a good argument for extending the advisory
+`issues --drafts` pass: #70 is named in the prompt body but is not the kind of
+citation that pass currently nets, because the prompt cites it as a *gate* rather
+than as its own tracking issue. Worth considering whether an "epic closes when X"
+idiom should be machine-readable.
+
+## Original prompt
 # Test-mode representative outputs: size-realistic samples for instant pipeline runs
 
 Type: feature

draft/maintenance/autolens_workspace/normalise_auto_simulate_guard_idiom.md → complete/2026/08/normalise-auto-simulate-guard-idiom.md

@@ -1,3 +1,71 @@
+# normalise-auto-simulate-guard-idiom
+
+- shipped: verified on autolens_workspace main `9974f891` (the prompt never left `draft/`)
+- follows: [[auto-simulate-guard-targets]] (autolens_workspace#359 → #364, autogalaxy_workspace#175) and the `should_simulate` migration (autolens_workspace#354)
+- repos:
+  - autolens_workspace
+
+## Summary
+
+The prompt asks for four hand-rolled auto-simulate guards to be converted to
+`al.util.dataset.should_simulate`, with one specific caution about not dropping a
+stricter check while doing it. All four are converted on main, and the caution was
+honoured — more carefully than the prompt asked.
+
+Recorded 2026-08-09 by the draft/ sweep. No work is owed.
+
+## Verified against autolens_workspace main (`9974f891`), 2026-08-09
+
+Against the prompt's § Proposed work:
+
+1. **All four idiom-B sites converted — DONE.** `cluster/likelihood_function.py`,
+   `interferometer/features/pixelization/many_visibilities_preparation.py`,
+   `imaging/features/advanced/subhalo/sensitivity/slam_source_parametric.py` and
+   `…/slam_source_pixelized.py` all call `should_simulate` now. A repo-wide sweep
+   finds **zero** remaining hand-rolled `data.fits … .exists()` simulator guards
+   (492 files use the standard idiom).
+
+2. **The `mass.csv` check was preserved — DONE, and better than specified.** The
+   prompt warned "do not silently drop it" and offered two ways out. The shipped
+   form takes the first *and* fixes an ordering subtlety the prompt did not raise:
+
+   ```python
+   if (
+       al.util.dataset.should_simulate(str(dataset_path))
+       or not (dataset_path / "mass.csv").exists()
+   ):
+   ```
+
+   with a comment recording that `should_simulate` is evaluated **first** so its
+   `PYAUTO_SMALL_DATASETS` rebuild always runs. Written the other way round, a
+   present `mass.csv` would short-circuit past the capped-rebuild side effect —
+   which is precisely the failure the conversion exists to prevent.
+
+3. **Re-running under the capped profile** — not independently re-run here; that
+   needs a real execution environment.
+
+4. **`required_files=[...]` on `should_simulate` — NOT taken.** PyAutoArray's
+   `should_simulate(dataset_path)` still has the single argument. This leg was
+   explicitly optional in the prompt ("consider whether…", and it would have made
+   the task library+workspace rather than workspace-only). The `mass.csv` clause
+   living in the script is the alternative the prompt allowed.
+
+**Not the same class, correctly left alone:** two `if not data_fits_path.exists():`
+sites survive, in `multi_dataset/features/imaging_and_point_source/modeling.py:75`
+and `cluster/start_here.py:153`. Both guard a one-off `urllib` download of real HST
+data (RXJ1131, Abell 2744), not a simulator invocation, so `should_simulate`'s
+capped-rebuild semantics would be actively wrong there — it would delete a
+downloaded file to re-download it. Converting these would be a regression.
+
+## Note on detection
+
+This is the one finding across three sweeps that `pyauto-brain intake reconcile`
+ranked `high` for the right reason: [[auto-simulate-guard-targets]] names the
+prompt's path directly in its body. That is signal 3 in
+`draft/feature/pyautomind/draft_staleness_detection_signals.md` working as
+intended — though it still arrived among 51 other `high`s.
+
+## Original prompt
 # Normalise the two auto-simulate guard idioms
 
 Type: maintenance

complete/archive/epics/jax_substructure_simulator.md

@@ -30,6 +30,16 @@ __What's already done__ (no work needed):
 
 __Outstanding__ (sequenced):
 
+> **CORRECTION 2026-08-09 (draft/ sweep): items 1-4 below are NOT outstanding —
+> they SHIPPED on 2026-06-09.** See `complete/2026/06/jax-substructure-simulator.md`
+> (PyAutoLens#543 + #544, PyAutoGalaxy direct commits, autolens_workspace_test
+> #127/#128/#129), re-verified against upstream `main`. Their four prompt files
+> stayed in `draft/` for two months after shipping and were retired into that
+> record; the relative links below are therefore dead. The only live work from this
+> epic is `draft/feature/jax_substructure/5_prng_key_vmap_noise.md` and
+> `6_deflection_equivalence_test.md`, both confirmed still open. This tracker is
+> archived material — read the completion record, not this list.
+
 1. [feature/jax_substructure/1_vmap_subhalo_deflections.md](../feature/jax_substructure/1_vmap_subhalo_deflections.md) —
    vectorized deflection path: represent N halos as `(max_N, n_params)` arrays,
    `jax.vmap` the profile deflection function, sum with mask. Integration test