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isothermal-ell-sph-oversampling-at-the-cusp

  • status: planned — NOT yet a prompt file; file one via /intake before starting
  • found: 2026-08-09, while pinning B10 of the @rhayes777 audit (complete/2026/08/autogalaxy-profile-validation-guards.md)
  • classification: library (PyAutoGalaxy) — accuracy / numerical, NOT part of the audit
  • summary: mp.Isothermal(ell_comps=(0,0)) and mp.IsothermalSph are the same profile analytically. Under the DEFAULT over_sample_size=4 their potential disagrees by up to 7% at the central pixel (0.0707 vs 0.0761). With over_sample_size=1 the disagreement collapses to 3.2e-06 — the same order as the deflections (2.4e-06). So this is an over-sampling artefact at the profile's singular centre, not a broken potential: over-sampling averages sub-pixel values across the r -> 0 cusp and the two forms diverge there.
  • benign baseline (explained, no action): the elliptical form clips axis_ratio to 0.99999 for numerical stability while IsothermalSph hardcodes 1.0; that propagates into einstein_radius_rescaled (0.5000025 vs 0.5) and accounts for the ~1e-6 floor. This is what @rhayes777 reported as B10 and it is correctly pinned.
  • why it still matters: the 1e-2 tolerance pinned in test_autogalaxy/profiles/test_validate.py::test__b10__potential_agrees_between_elliptical_and_spherical_isothermal papers over that 7% local disagreement, and the same over-sampling-at-a-singularity behaviour may affect other singular profiles.
  • CORRECTION on the record: PyAutoGalaxy#566's PR body and the comment on PyAutoGalaxy#440 describe this as the potential agreeing "three orders of magnitude worse" at 1.9e-03 relative, framed as an accuracy defect. That normalised by the GLOBAL MAX potential and mis-attributed the cause. Superseded by the analysis above.
  • RETRACTED: the guess that this shares a root cause with draft/bug/autogalaxy/nfw_truncated_potential_accuracy.md (MGE decomposition). It does not — MGE is not involved.
  • affected-repos:
    • PyAutoGalaxy

remote-mcp-deployment-tiers

  • issue: PyAutoLabs/autofit_assistant#20 (design/scope shipped 2026-07-21; build gated)
  • status: DESIGN-COMPLETE, build BLOCKED-ON-DEMAND — issue #20 holds the full auth/transport/hosting design + Richard/PyAutoMCP coordination. No code, no network surface built. Per prompt "if it earns it": build tiers 2/3 only once demonstrated demand for REMOTE access exists.
  • filed: 2026-07-21
  • prompt: draft/feature/autofit_assistant/remote_mcp_deployment_tiers.md
  • classification: feature (autofit_assistant + autolens_assistant) — transport/deployment/auth, NOT new tools
  • suggested-branch: feature/remote-mcp-deployment-tiers
  • blocked-by: (1) demonstrated demand for remote access; (2) MANDATORY security-review skill pass before any PR — never auto-ship (network-facing arbitrary-file-read surface; intake mis-sized it small/safe)
  • summary: tier2 = opt-in mcp.run(streamable-http) + bearer-token ASGI middleware + PYAUTO_MCP_ALLOWED_ROOTS path confinement behind cloudflared/ngrok (default stays stdio); tier3 = hosted OAuth/OIDC + per-user scoping (Euclid sample triage; rhayes777/aggregator-agent consumer). Coordinate with Richard FIRST (rhayes777/PyAutoMCP = broader compute/optimise MCP, no transport/auth layer yet) — converge on profiles sharing one auth/transport layer, or share only the tunnel recipe.
  • affected-repos:
    • autofit_assistant
    • autolens_assistant

samples-parameter-paths

  • prompt: draft/bug/health_fixes/samples_parameter_paths.md
  • issue: PyAutoLabs/PyAutoFit#1327 (open, parked)
  • status: parked
  • filed: 2026-07-08
  • classification: library (PyAutoFit) — bug, health_fixes cluster
  • suggested-branch: feature/samples-parameter-paths
  • blocked-by: clean-output CI re-validation (does NOT reproduce on current main)
  • summary: | Investigated the PyAutoHeart #27 release KeyError in parameter_lists_for_paths. Does NOT reproduce on current main: two legs (shapelets 125-prior Basis; multi-analysis 22-prior) pass in-memory AND via true from-disk reload (model.json + samples.csv), plus all synthetic round-trips. The 745117bd7 fix (May 2026) was already in main at the 2026-07-06 run; failure most consistent with STALE cached output/ in the release run. No library fix warranted — parked pending a clean-output CI re-run. Sibling health_fixes/ prompts from the same run are suspect too. Full trail: PyAutoFit#1327 comments.
  • affected-repos:

piemass-potential

  • prompt: draft/feature/autogalaxy/piemass_potential.md
  • status: planned
  • filed: 2026-06-05
  • classification: library (missing feature)
  • suggested-branch: feature/piemass-potential
  • summary: | PIEMass (Lenstool-ported PIE) has no potential_2d_from, so it now raises a clean NotImplementedError (post dark-matter-potentials) and crashes tracer visualization (potential FITS extension) — same class as the original NFW bug, different profile. No MGE/CSE decomposition hook exists; needs an analytic port (Kassiola & Kovner 1993, or the dPIEMass r_s->inf limit) or a new convergence-MGE hook. Validate via grad(psi)=alpha self-consistency.
  • affected-repos:
    • PyAutoGalaxy

latent-nan-guard-honest-run

  • issue: NEEDS A FRESH ISSUE — #1413 was auto-closed when PyAutoFit#1415 merged (its Closes line). Library half is DONE+MERGED; file a new issue for this workspace half at /start_dev time.
  • planned: 2026-07-22
  • classification: workspace
  • suggested-branch: feature/latent-nan-guard-honest-run
  • blocked-by: slow-skip-timeout-cap-doc (using autolens_workspace_test; PR #194 OPEN/MERGEABLE)
  • affected-repos:
    • autolens_workspace_test

knn-partial-point-block

  • issue: PyAutoLabs/PyAutoArray#609
  • filed: 2026-10-02
  • prompt: draft/bug/autoarray/fix_knn_neighbor_search_for_a_partial.md
  • classification: both
  • suggested-branch: feature/knn-partial-point-block
  • prior-blocker-cleared: Audit PRs Array611/workspace342 merged 2026-10-02; see complete/2026/10/mesh-interpolator-numerics-audit.md. Survey current claims at start-dev.
  • affected-repos:
    • PyAutoArray
    • autolens_workspace_test
  • finding-2026-10-29: fix breaks KNN+AdaptSplit gradient check (jax_grad/knn.py); split out of arc 4b (#665) by human; patch on #609; investigate mechanism first (see prompt).
  • resume: Audit#603 discovered deterministic partial-final-block neighbor corruption; filed separately per explicit user request. No implementation begun or worktree created. Audit retains strict expected-failure witness citing609. Schedule repair independently and promote regression after fix.

sibson-internal-edge-continuity

  • issue: PyAutoLabs/PyAutoArray#610
  • filed: 2026-10-02
  • prompt: draft/bug/autoarray/fix_sibson_interpolation_at_internal_edges.md
  • classification: both
  • suggested-branch: feature/sibson-internal-edge-continuity
  • prior-blocker-cleared: Audit PRs Array611/workspace342 merged 2026-10-02; see complete/2026/10/mesh-interpolator-numerics-audit.md. Survey current claims at start-dev.
  • affected-repos:
    • PyAutoArray
    • autolens_workspace_test
  • resume: Audit#603 found incorrect internal-edge Sibson weights and near-edge partition failure. Filed separately per explicit user request; strict expected-failure regressions retained in audit. No repair begun or worktree created. Plan algorithmic repair independently.

interferometer-primary-beam-persistence-mirror

  • filed: 2026-10-21
  • prompt: draft/feature/autolens/interferometer_primary_beam_persistence_mirror.md
  • status: ready — PyAutoLens claim released 2026-10-21 (point-dataset-positions-panel shipped, complete/2026/10/point-dataset-positions-panel.md); run /start_dev (docstring line + one round-trip test, no source change)
  • parent: complete/2026/10/interferometer-primary-beam-persistence.md
  • affected-repos:
    • PyAutoLens

point-plots-yaml-keys-assistant

  • status: unblocked 2026-10-23 — cosmos-web-ring-notebook merged (autolens_assistant#161, complete/2026/10/cosmos-web-ring-notebook.md); autolens_assistant free (sibling waiting on the same repo: draft/docs/autolens_assistant/ai_options_page_autolens_leg.md)
  • filed: 2026-10-22
  • parent-issue: PyAutoLabs/HowToLens#98 (closed after the HowToLens half; not this task’s tracking issue)
  • prompt: draft/docs/autolens_assistant/point_plots_yaml_keys.md
  • tracking: file a separate autolens_assistant issue at start-dev; this remaining work is not complete
  • release-gate: verify the PyAutoLens#794 release before shipping, as required by the original prompt
  • parent: complete/2026/10/point-plots-yaml-keys.md (HowToLens half merged 2026-10-22, HowToLens#99); no separate prompt file
  • scope: same point_dataset / fit_point_dataset block edit in autolens_assistant/config/visualize/plots.yaml as HowToLens; ship on its own branch feature/point-plots-yaml-keys once the claim clears