📦 WP-126 — docs(report): keypoint tier report, model card, and the fourth task everywhere¶
Engineering log · Phase 12 — Keypoint detection, v0.5.0
WP-126 — the fourth task existed everywhere except where a reader would look¶
The tier's own artifacts landed cleanly: a model card, a 0.5.0 reproduction-report section, a fourth panel on plot_training.py for the keypoint loss term. What did not land, and was not noticed until the naming of one file was questioned, is that every general-audience document still described a three-task project. README.md said "Three tasks, one trunk" and listed three; docs/index.md had a heading reading "The three tasks"; docs/TRAINING.md carried a launch section for detection, segmentation and oriented detection and none for keypoints, and its wiring-gate block listed three of the four overfit_micro.py tasks. None of that is a gate failure — every register check, link check and section check passed throughout, because each of them asks whether a named thing exists, and no gate asks whether a newly named thing has been added everywhere its three siblings appear.
The naming question that surfaced it is itself the more useful finding. The card shipped as model_cards/pose.md, describing a "pose detector", which is precisely backwards: this project's keypoint task is K-generic by construction — num_keypoints is a constructor argument the way the class count is, nothing in the head, the loss or the decode path reads a point's meaning, and the wiring gate deliberately runs a 7-point synthetic symbol schema rather than a human one (A67 exists only because that schema has no annotator variance to derive sigmas from). Human pose is one instantiation, distinguished by having a published sigma table and a ground-truth file, not by being what the architecture is for. The file is model_cards/keypoints.md, and the general docs say keypoints and then name pose as the instantiation the shipped checkpoint trained on.
The task-specific prose stays in pose terms wherever it is actually describing the shipped checkpoint — its training data is person_keypoints, its ethical-considerations section is about predicting human skeletons, and softening those into schema-neutral language would make the card describe something safer than what was trained. The distinction the rename enforces is between the architecture (keypoints) and this checkpoint (pose), not a blanket find-and-replace.
Three stale figures were corrected in passing, each found by reading a line rather than by any check: the README claimed 63 registered assumptions against an actual 73, and 20 frozen golden files against an actual 14 (the number had been read off a total that included the seven live sets); and it described roadmap 111's whole-image oriented figure as not yet measured, which had stopped being true when that row closed and the reproduction report gained the number. A document that quotes a count is a document that goes stale silently, and none of the three would have been caught by anything in make gate.
The general lesson for the next task family, whenever there is one: adding a task is not done when its own artifacts exist. The check worth running by hand is to grep for the previous task's name across the tree and ask, at each hit, whether the new one belongs beside it.