diff --git a/tasks/cluster_pointsolver_speed.md b/tasks/cluster_pointsolver_speed.md
index 0b3971f..3278294 100644
--- a/tasks/cluster_pointsolver_speed.md
+++ b/tasks/cluster_pointsolver_speed.md
@@ -40,6 +40,14 @@ not refresh measurements or authorize compute. Historical task text is retained.
 - Human decision TAKEN 2026-10-23 (chat): keep the 1.0″ starting grid, plus the validation check as mitigation. See the Decision section below.
 - Next bounded task: spurious-core candidates (`draft/feature/autolens/point_solver_spurious_core_candidates.md`, start_dev in progress), then the workspace validation check.
 - Review date does not refresh measurement dates. This check-in authorizes no compute, default change or merge. [Full dated check-in](../checkins/2026-10-23.md).
+- Spurious-core candidates ISSUED and SHIPPED 2026-10-23: [PyAutoLens#799](https://github.com/PyAutoLabs/PyAutoLens/issues/799) → [PyAutoLens#800](https://github.com/PyAutoLabs/PyAutoLens/pull/800) (OPEN, `pending-release`, awaiting human `/prm`). It adds `residual_threshold`, which rejects candidates with |β(θ̂) − β| > k · `pixel_scale_precision`. **Human decision 2026-10-23: on by default at k = 10** (the problem is common on cluster models; `None` disables it).
+  - Mechanism: the host is a near-critical saddle at the `r_core = 0` members, so the core points have |μ| 0.1–0.3 and the magnification filter cannot remove them.
+  - Evidence (laptop CPU fp64, diagnostic): true candidates reach at most 3.58× the precision (viz), 2.21× (`simple`) and 1.075× (1c/1d near-cusp); the core points are at least 38.5×. At k = 10 all 4 viz core points are removed and nothing else changes in 238 cases, and the 1c/1d rows are bit-identical.
+  - The rejected rule, a triangle-area consistency check, drops true near-cusp candidates.
+  - Not tested: A2744. At precision 0.01 the cut (0.1″) is above the 0.04″ residuals.
+  - Default-on checks against the branch: 952 library tests pass; workspace smoke passes (autolens 41 + 2 notebooks, workspace_test 37, euclid 9, HowToLens 50); 6 real-solve workspace_test point-source scripts pass. The filter costs one extra trace of the padded candidates per solve.
+  - Side issues filed: [PyAutoGalaxy#658](https://github.com/PyAutoLabs/PyAutoGalaxy/issues/658) (`MassSheet` fails under JAX); [autolens_profiling#445](https://github.com/PyAutoLabs/autolens_profiling/issues/445) (the stale auto-simulated `dataset/cluster/simple` is never regenerated).
+- Next: the workspace validation-check draft, then a workspace_test CI witness for the default-on `residual_threshold` (phase 2). One task at a time.
 
 ## Knowledge (2026-10-22): phase 1, cluster-scale robust PointSolver settings