{
 "schema": "roboRSI blind harness review v1",
 "date": "2026-10-20",
 "model": "gpt-6-astra via api.ziwu.dev (sub2), Responses API, one call per case, no retries",
 "protocol": "After the fact. For each failed or stopped RealBot run, Astra received only the harness code it ran with, the raw run log (its own decisions, guard messages, end of run) and 3-6 images. Engineering fixes, engineer diagnoses, commit messages and later code were withheld; an independent agent removed leak-prone wording before the call. Two independent judges compared Astra proposals with the actual code diff.",
 "caveats": [
  "The engineering fixes were made before this review; this shows Astra reaching the same changes from the same evidence, not that Astra authored the fixes.",
  "No case covers the whole engineering change; all eight judge verdicts are partial.",
  "The gateway prepends a Codex system prompt (~4k tokens) unrelated to the task.",
  "Case 4 engineering fix is an unexecuted draft; its first item was already implied by the 15:55 operator note."
 ],
 "cases": [
  {
   "case": "case1-run1",
   "run": "20261020_144619",
   "request_id": "resp_04dfa98999b9f87d016ad745fc0fbc8194bd06d9295706463e",
   "usage": {
    "input_tokens": 62128,
    "output_tokens": 4155,
    "reasoning_tokens": 311
   },
   "response_sha256": "f1af04f7a26940bf093edf5e03163e3b43e364098f30983ed15ee6feb01611ff",
   "astra_output": {
    "diagnosis": "The primary actionable failure was a pen grasp planned around the midpoint of the open fingertips without checking the lower individual fingertip. Decision 14 selected 'tilt 30 deg across the object (az 138) jaw sign -1'. In skills.py::plan_pick_object, open_tip.z is table_z + 6 mm + half the detected object height, approximately 12.5 mm for pen 1, and the wrist is positioned from that midpoint. However, the chosen orientation also tilts the jaw-closing axis: its world-z component is approximately -0.48. At the measured 90 mm opening, one fingertip is therefore approximately 21.5 mm below the midpoint. The planner's chain() checks camera posture, IK and limited wrist separation, but not individual fingertip table clearance. The execution guard correctly rejected the first tick of the final approach at tick 103: 'left arm: fingertip_a would be -0.7 cm above the tabletop (minimum 0.4 cm)'. This was a proposed intermediate joint target, not an executed penetration. The receipt reports zero travel in that primitive and cancels closure and lift. Earlier approach tracking was accurate: decision 14's approach error was approximately 0.44 mm. The evidence points to inconsistent planning geometry, not a large arm positioning error.\n\nDecision 15 then treated this as a scalar descent correction: 'lower only 9 mm to retain table clearance' and queued closure without another observation. Images 03_tick105_left_wrist.jpg and 04_tick105_left_wrist_zoom2x.jpg show the target pen visually between widely open pads, but do not establish pad height or contact. The adjacent elongated orange object is close to the image-right finger; 05_tick105_chest.jpg also shows the oblique approach among neighboring objects. These images support checking the complete grasp envelope, not assuming image centering makes descent and closure safe. At ticks 105–107 the target clearance was only 6 mm, just 2 mm above the guard minimum. The nudge was marked complete with 4.34 mm position error and the measured wrist 3.2 mm above its target, within the generic 6 mm completion tolerance. Decision 15's public fingertip marker was a closed-finger axial point, whereas the guard violation concerned an individual open fingertip; those are different geometries.\n\nThe immediate termination must be separated from the planning failure. The last receipt is tick 107; the left jaws remained commanded open and measured 90 mm. No pen closure, lift or insertion was recorded. The run ended with an uncaught MotionBlocked reporting 4.58 degrees remaining, and the operator record says the emergency stop was pressed during the pick. The logs do not prove a table collision caused that stop. A strong code-based explanation for the uncaught exception is the queued close entering execute()'s grip-compensation back-off: its intermediate io.move_arms() calls are outside the normal MotionBlocked handler and can fail before any tick receipt is written. This remains an inference because the failing substep is not logged. The observed 0.263–0.286 degree arrival errors at ticks 105–107 alone do not establish contact.\n\nThere were additional failures that would obstruct continuation. Decision 4's holder grasp closed to 0 mm and correctly canceled the lift; decision 6 then rejected all 96 holder approaches. Holder detections varied substantially between decisions 1, 5 and 10, and the initial frame produced two upright candidates. The evidence cannot distinguish physical holder displacement from detection error. Decisions 11–13 recovered manually: a 40.8 mm jaw opening, a 40 mm lift and approximately 39 mm rim rise support attachment, also visible in 01_tick081_chest.jpg and 06_tick105_right_wrist.jpg. Nevertheless, held_objects was {} at decision 15 because ordinary grip/nudge recovery never registers a holder with SkillPlanner. Thus insert_into_holder or place_holder would subsequently refuse despite the physical grasp. The detector also treated the lifted holder's rim elevation as a 156 mm object height while keeping its bottom at table_z. Finally, decision 8's approach was partially executed before the tick-62 elbow rejection, showing why the prompt's blanket claim that a refusal means 'nothing moved' is incorrect. The episode stopped before completing any insertion or placing the holder down; it did not demonstrate task success or a proven decision-budget exhaustion.",
    "proposals": [
     {
      "rank": 1,
      "title": "Plan pen contact using both fingertips and the actual jaw opening",
      "file": "gpt_control/vendor/physical_rsi/skills.py::SkillPlanner.plan_pick_object; gpt_control/backend/realbot/geometry.py::Geometry.arm_points, tip_retract_m",
      "change": "Replace OPEN_TIP_RETRACT_M-based midpoint placement with the calibrated linkage model exposed through a shared geometry adapter. Pseudocode: opening = measured_or_calibrated_opening(side); back = tip_retract_m(opening); offsets = [(tip-back)*R[:,0] + opening/2*R[:,1], (tip-back)*R[:,0] - opening/2*R[:,1]]; tips = [wrist + offset for offset in offsets]. Require min(t.z-table_z for t in tips) >= TIP_MARGIN_M + calibrated_uncertainty_margin. Separately require the modeled finger-pad contact regions to overlap opposite sides of the observed pen at the intended grasp height; merely raising an infeasible candidate must not make it a valid grasp. Reject orientations whose jaw-axis vertical component makes safe bilateral engagement impossible. Add candidates with jaw axis horizontal and perpendicular to the pen, including finger-axis tilt along the pen when reachable. Allow a narrower pre-opening sized from object width plus localization uncertainty, but set it while safely above the scene and replan using that opening. Preserve the actual pen axis in the tool frame for insertion instead of requiring every grasp to leave it exactly along tool z.",
      "expected_effect": "The decision-14 candidate is rejected during planning because its lower open fingertip cannot safely reach the proposed grasp position. Candidate selection can instead find a reachable orientation and aperture that straddle the pen without crossing the table margin. Shared linkage geometry also removes the discrepancy between a hard-coded 25 mm retraction and the executor's measured-opening calculation.",
      "risk": "Some pens may have no feasible grasp under the current wrist and camera constraints. Smaller openings reduce tolerance to localization error, and alternative grasp orientations may make insertion harder. Pad dimensions and clearance uncertainty require calibration; the planner should return an explicit infeasibility result rather than reduce safety margins."
     },
     {
      "rank": 2,
      "title": "Preflight skills through the executor's complete safety model",
      "file": "gpt_control/vendor/physical_rsi/skills.py::SkillPlanner.chain, best, elbow_out; gpt_control/backend/realbot/drivers.py::H0Driver.__init__; gpt_control/backend/realbot/safety.py::Guard.check",
      "change": "Inject a read-only executor planning/guard adapter into SkillPlanner. For each candidate, simulate the same incremental IK updates, joint-step limits, elbow paths, gripper states and compensation stages that execution will use. For every predicted tick, call the same guard with both arms and conservative held-object geometry; reject the candidate on the first violation and retain structured reasons. Include open, approach, close/back-off, lift and retreat stages rather than checking only Cartesian waypoints. Use the common measured-opening-aware pinch and fingertip geometry for two-hand checks. Apply this to pick_object and grasp_holder as well as presentation and insertion. Revalidate from measured state at execution boundaries because a successful preflight is not a guarantee of tracking or scene accuracy.",
      "expected_effect": "The table rejection at tick 103 and elbow-margin failures such as tick 62 become candidate-selection failures before approach motion. Planning and execution agree on camera, finger, arm-separation and posture constraints, reducing recovery calls and partial skill execution.",
      "risk": "Full candidate simulation adds computation, and replanning IK can diverge from predicted solutions. Cache geometry and eliminate obviously infeasible candidates early, but keep the live guard authoritative. Conservative held-object envelopes may reject feasible approaches."
     },
     {
      "rank": 3,
      "title": "Add contact checkpoints and require clearance-aware motion completion",
      "file": "gpt_control/vendor/physical_rsi/control.py::Controller.action, discard_queue; gpt_control/vendor/physical_rsi/skills.py::SkillPlanner.plan_pick_object, plan_grasp_holder; gpt_control/vendor/physical_rsi/policy.py::SKILLS_RULE; code/system_prompt.txt",
      "change": "Split grasp macros into approach, contact alignment, closure and verification phases with explicit observation checkpoints before final descent and closure. After a table-clearance rejection, suspend any queued close until a fresh observation and revised grasp-envelope validation succeed. Give contact primitives stricter, calibrated position/orientation tolerances and validate measured fingertip/pad geometry before releasing their successors; generic 6 mm wrist tolerance is unsuitable when remaining clearance slack is only 2 mm. If uncertainty exceeds available slack, reorient or retreat rather than repeatedly descend. Expose measured-opening fingertip_a, fingertip_b, pad regions and lowest clearance in context, clearly labeling closed-finger reference markers. Amend the prompt: 'Image centering does not establish contact height. Read travel_done and primitive_progress: a planning refusal may precede all motion, but an execution refusal may follow partial motion. Following a contact-clearance refusal, reobserve and validate the revised grasp before closure.'",
      "expected_effect": "The decision-15 recovery cannot silently advance from a marginal descent to closure on the strength of a projected midpoint and a loose completion tolerance. The model receives the same physical points implicated by the guard, and queued actions depend on actual measured geometry.",
      "risk": "Additional observations cost time and model calls. Tighter tolerances can cause stalls if they exceed hardware capability; use measured repeatability and explicit timeouts, and return control for recovery instead of chasing an unreachable tolerance."
     },
     {
      "rank": 4,
      "title": "Make grip compensation fail closed and log every physical substep",
      "file": "gpt_control/backend/realbot/env.py::RealBotEnv.grip_compensation, execute, _blocked_receipt; gpt_control/backend/realbot/run.py::per-tick receipt handling; gpt_control/backend/realbot/safety.py::Guard.check",
      "change": "Refactor execute into explicit phases: compensation_plan, backoff_substep, close, settle. Preflight the entire back-off with the existing opening, then the closure sweep at the compensated wrist. Guard transitions from the actual initial opening to the proposed opening; do not evaluate both current and target configurations using only the future commanded aperture. If compensation IK fails or any phase is unsafe, return a structured rejection before sending the close instead of continuing with uncompensated closure. Wrap every io.move_arms call, including compensation substeps, in the blocked-motion/error receipt path. Log phase, parent primitive, commanded and measured joints, opening, predicted tip displacement, executed substeps and partial travel. On MotionBlocked, refresh measured state, abort queued successors and synchronize controller holds. Preserve terminal emergency-stop/failed-stop handling; catching the exception must not authorize resumed motion. Report that back-off precedes closure and that blocked jaws can make final tip displacement differ from the commanded-opening prediction.",
      "expected_effect": "A recurrence of the final failure identifies the exact physical substep and leaves a receipt instead of an unexplained gap after tick 107. Closure cannot proceed after failed compensation, and the safety model covers changes in jaw geometry as well as arm motion.",
      "risk": "Additional reads and sweep checks increase latency. Emergency-stop status may be unavailable through the current hardware interface; classify it as unknown unless directly reported. This change improves safe handling and diagnosis but cannot prevent an operator emergency stop."
     },
     {
      "rank": 5,
      "title": "Unify skill and manual grasp state with explicit verification",
      "file": "gpt_control/vendor/physical_rsi/control.py::Controller.action; gpt_control/vendor/physical_rsi/skills.py::SkillPlanner.grasped, released, held_world, context, plan_insert_into_holder, plan_place_holder",
      "change": "Replace implicit registration on jaw width alone with attachment states such as candidate, verified and uncertain. Pseudocode: after closure, if aperture is unavailable, return grasp_unknown; if aperture indicates empty jaws, return grasp_missed; otherwise record candidate_attachment. After a guarded test lift and visual confirmation of object motion relative to the gripper, estimate current object geometry and commit verified_attachment. Provide an explicit association operation for a manually recovered grasp, using a selected detection/keypoint identity plus current post-grasp observations; do not associate an arbitrary nearby object from aperture alone. Preserve observed holder height from a supported measurement and estimate its current bottom/rim after lifting. Invalidate or downgrade attachment on ordinary opening commands, slip evidence or contradictory observations, not only skill grips carrying releases=True. Require verified object geometry for insertion and placement while exposing uncertainty to the model.",
      "expected_effect": "The manually recovered right-hand holder at decisions 11–13 becomes usable by present_holder, insert_into_holder and place_holder. Missing aperture feedback no longer falls through to grasped(), and an opened or slipped object does not remain silently registered.",
      "risk": "Occlusion can make visual verification inconclusive and require another viewpoint. Incorrect association can corrupt placement geometry, so uncertainty must block precision insertion rather than be replaced with stale pre-grasp coordinates."
     },
     {
      "rank": 6,
      "title": "Validate holder detections and distinguish held objects from table objects",
      "file": "gpt_control/vendor/physical_rsi/object_vision.py::detect, fit_circle, public; gpt_control/vendor/physical_rsi/skills.py::SkillPlanner.object, plan_grasp_holder",
      "change": "Attach observation tick, support assumption and geometric uncertainty to each detection. Validate upright candidates using rim coverage, supporting side-wall points and consistency across views or observations; a high circle inlier ratio alone is insufficient. Flag competing upright hypotheses such as the initial IDs 5 and 6 instead of silently selecting by shape class. When an object is associated with a hand, exclude it from table-supported geometry estimation or explicitly mark its bottom and physical height unknown; do not convert the lifted rim's 156 mm elevation into holder height with bottom fixed at table_z. Before holder closure, compare the predicted rim and pad contact locations against the current wrist image and update or reject a large mismatch. Preserve detection-frame identity so stale IDs cannot silently refer to a different object. Mark wide components as unresolved objects or clusters and require visual classification or segmentation before treating them as pens.",
      "expected_effect": "The first holder miss is less likely to proceed through closure using uncertain geometry, and detections after the successful lift no longer corrupt the holder's physical dimensions. Remaining pen inventory becomes explicit instead of treating every colored component as an insertion target.",
      "risk": "The record does not establish whether early holder shifts were physical motion or perception error; this change must allow both. More restrictive detection may miss partly occluded objects, and splitting touching components can create false instances."
     },
     {
      "rank": 7,
      "title": "Expand holder recovery candidates and evaluate insertion from the actual grasp",
      "file": "gpt_control/vendor/physical_rsi/skills.py::SkillPlanner.plan_grasp_holder, object_in, insert_candidates, insert_route, plan_present_holder",
      "change": "Search safe holder grasp heights and additional tilts, including the approximately 45-degree higher approach found reachable by decision 7, subject to the full geometry and guard checks above. Include safe retreat/reposition routes when a direct approach from the current joints is infeasible. Rank candidates using approach feasibility, contact quality and subsequent presentation/insertion feasibility. For alternate pen grasps, build insertion orientations with align_frame(actual_axis_tool, +/-holder_axis, finger_axis_hint), then sample rotation about the holder axis; the current tool-z alignment assumption should not reject an otherwise usable grasp. In plan_present_holder, distinguish 'mouth geometrically reachable' from a verified route for the actual held pen and replan after pickup.",
      "expected_effect": "The harness can recover from the decision-6 candidate exhaustion without forcing the model to improvise disconnected manual poses. Safer pen orientations introduced by the first proposal remain compatible with insertion planning.",
      "risk": "A larger search increases planning cost, and endpoint IK reachability does not establish a safe approach or reliable contact. Limit search effort and report which constraint prevented completion; do not weaken elbow, camera or table protection."
     }
    ],
    "confirm_next_run": "First replay the recorded decision-14 detection, measured arm state and opening through the revised planner without hardware motion. The old 30-degree candidate should fail with an individual-fingertip clearance explanation before any approach command; an accepted replacement must satisfy both pad engagement and full-path guard checks. Replay the tick-62 posture case and exercise compensation failures, including a MotionBlocked during an intermediate back-off and an IK failure: each must produce a phase-specific receipt, preserve measured holds, discard closure/lift successors and avoid automatic continuation after an emergency stop. These are proposed checks, not tests already performed.\n\nOn hardware, record both measured fingertip heights, jaw opening, pad/pen alignment and uncertainty at the pre-close checkpoint. Confirm that accepted grasp paths do not reproduce the tick-103 table refusal and that contact-phase completion satisfies calibrated tolerances. Capture before/after wrist and chest views showing the pen moving with the left gripper and clearing the table; a nonzero aperture alone is insufficient. Record every compensation substep and closure so there is no unexplained receipt gap if a stop occurs. Verify that the right holder appears as a verified attachment after manual recovery or skill grasp, with approximately its original physical height rather than its elevated rim-to-table distance. Finally, demonstrate the complete task: the right hand continues supporting the holder while each visually identified pen is inserted, no target pens remain on the table, and the holder is placed upright with verified table support before release. Report unresolved broad objects explicitly. Successful completion across repeated trials, without reducing guard margins, would support the fix; one run without an emergency stop would not by itself establish that the original stop was caused by contact."
   },
   "model_returned": "gpt-6-astra",
   "created_utc": "2026-10-20T10:44:12Z"
  },
  {
   "case": "case2-run2",
   "run": "20261020_151924",
   "request_id": "resp_03be4ee0d428548f016ad744cd6de88196a329895a4615e1ca",
   "usage": {
    "input_tokens": 53409,
    "output_tokens": 3525,
    "reasoning_tokens": 143
   },
   "response_sha256": "0bdfab5e0983d27e3737cfe4a1fc5ebb07a4169bdbd4cc9b6b847376a975fadd",
   "astra_output": {
    "diagnosis": "The harness accepted a grasp plan that did not satisfy the runtime posture rule, then executed an approach that appears to have disturbed the holder before grasping it. The guard correctly refused unsafe ticks; the episode ultimately ended through an operator stop, not task completion.\n\n1. The holder skill omitted the relevant posture check. In skills.py, plan_grasp_holder calls best(..., other_wrist) without two_hand and never calls elbow_out. Consequently, chain skips its elbow-posture logic even though the hands are already within 35 cm. Log §5, history entry 2, and §6, tick 6, show the first approach refused before any wrist travel: right elbow 65.4→64.9 degrees, pinch distance 30.2 cm. The prompt's assertion that skills automatically open the arms is false for this skill. The left elbow being at 61 degrees was not itself the reported violation: the guard prohibits further inward motion below 75 degrees, rather than requiring every stationary elbow to exceed 75 degrees.\n\n2. A one-time elbow correction did not make the complete route feasible. Decision 3 successfully raised the right elbow to approximately 81.5 degrees with an essentially unchanged wrist pose (§5, entry 3). The second grasp selected the same azimuth 135/tilt 15 approach. It completed three pre-grasp moves, during which the elbow reached approximately 97 degrees and then fell to 72.4 degrees as the hands separated (§7, ticks 28–45). On re-entry to the 35 cm region, tick 46 would have reduced the elbow to 65.8 degrees at 34.7 cm, so the guard refused it. The rejected tick moved nothing, but the preceding skill steps had already moved substantially. At the resulting pose, J7 had zero lower-bound margin (§9); decision 6's requested +15-degree elbow correction was rejected by the swivel solver with 'joint limit: J7' (§5, entry 10).\n\n3. The approach lacked protection against unintended object contact and lacked intermediate scene checks. Images 02_tick16_cam_chest.jpg and 03_tick16_cam_right_wrist.jpg show an upright holder before the second attempt. Images 04_tick48_cam_chest.jpg, 05_tick48_cam_head.jpg and 06_tick48_cam_right_wrist.jpg show it lying on its side, with one open finger apparently at or inside its mouth. The jaws remained open at 90 mm throughout the executed approach (§8), and closure/lift were discarded (§5, entry 9). This strongly suggests disturbance during the executed pre-grasp motion, but the available frames do not establish the exact contact tick or exclude external disturbance. chain checks camera posture and coarse wrist separation, while the guard checks table and inter-arm geometry; neither checks the unheld holder against the moving fingers. Interpolating wrist poses toward a nominal pre-grasp pose therefore does not establish an object-clear approach.\n\n4. There was a separate, earlier scene change whose cause is unproven. Between images 01_tick08_cam_chest.jpg and 02_tick16_cam_chest.jpg, the upright holder shifted right. Detection moved from [0.0623, 0.0699] to [0.1354, 0.0751] m, approximately 73 mm (§4). The intervening executed elbow motion preserved the wrist pose, so this should not be attributed confidently to that motion. Redetection at decision 4 was appropriate.\n\n5. Perception and prompt contracts made recovery unreliable. At tick 48, the visibly toppled holder was still reported as 'upright', now with diameter 42 mm, height 104 mm and circle-fit fraction 0.54, versus 67 mm, 124 mm and approximately 0.99 before tipping (§4). object_vision.detect treats tall colored points with a plausible horizontal circle as upright and assigns a vertical axis without validating the object's support or opening orientation. SKILLS_RULE also says that a refusal means nothing moved and recommends redetect-and-retry regardless of failure cause. This obscures partial skill execution and encourages retrying geometry that redetection alone cannot make feasible.\n\nThe run stopped at 48 ticks through stop_file (§1 and §10), after six model calls. No holder grasp, pen insertion or placement was completed; held_objects was empty (§9).",
    "proposals": [
     {
      "rank": 1,
      "title": "Validate every skill against the actual guarded execution path",
      "file": "code/vendor/physical_rsi/skills.py: SkillPlanner.chain, best, plan_grasp_holder; code/vendor/physical_rsi/control_excerpt.py: Controller.action; code/backend/realbot/safety.py: Guard.check",
      "change": "Expose a read-only backend validation callback to the planner. Refactor executor target generation into a shared function used by planning and execution: for each proposed primitive, simulate its actual IK updates, step clipping, opening changes and applicable grip compensation from the current joint state; call the unchanged Guard.check for every predicted tick with both arms and held-object geometry. Validate elbow and home prefixes too. Remove the dependency between posture validation and whether the other hand holds an object: all skills must supply both arms. Pseudocode: for candidate in ranked_candidates: rollout = predict_executor(candidate, measured_state); if all(guard_accepts(tick) for tick in rollout): return candidate. Revalidate from measured state at execution boundaries and replan on material divergence. Preserve selected joint-path information or use the same solver configuration so execution cannot silently choose a substantially different redundant-arm route.",
      "expected_effect": "Rejects both recorded posture-violating routes during planning, before opening or moving along them. It also closes the mismatch between planner IK using solve_result and executor IK recomputed through solve, and replaces wrist-distance heuristics with the backend's actual checks. Runtime guarding remains authoritative.",
      "risk": "Full candidate rollouts increase planning cost and depend on accurate executor/backend modeling. Use cheap geometric filters before rollout and cache only against an unchanged scene and robot state. Predicted feasibility cannot replace runtime checks."
     },
     {
      "rank": 2,
      "title": "Plan object-clear transit before the final holder approach",
      "file": "code/vendor/physical_rsi/skills.py: SkillPlanner.plan_grasp_holder, chain, moves; code/vendor/physical_rsi/object_vision.py: detected object geometry",
      "change": "Replace direct interpolation from the current pose to a low side pre-grasp pose with candidate transit routes: leave the object's occupied region, rotate in verified free space, reach an external side stand-off, then approach with a fixed orientation. Check the swept gripper, open fingers, wrist camera and relevant arm geometry against the detected holder and other scene obstacles at the same joint-space samples used for execution. Model the holder conservatively as an extruded polygon or cylinder with uncertainty margins; permit intended pad contact only in the final grasp phase. Include the actual opening-dependent fingertip extension and the closure sweep. Reject candidates whose fingers cross the holder rim or wall during transit.",
      "expected_effect": "Prevents a nominally valid pre-grasp target from being reached through the holder. Addresses the likely tipping mechanism visible in the tick-48 chest, head and wrist images, which table and inter-arm checks cannot detect.",
      "risk": "Conservative shape envelopes can reject valid grasps, particularly with occlusion or polygonal walls. Contact allowances must be restricted to known pad-contact regions and phases; broad exemptions would recreate the failure."
     },
     {
      "rank": 3,
      "title": "Preserve elbow recovery margin throughout the route",
      "file": "code/vendor/physical_rsi/skills.py: SkillPlanner.elbow_out, best, chain, plan_grasp_holder, expand; code/backend/realbot/drivers_excerpt.py: rejection feedback",
      "change": "Score feasible candidates by minimum joint-limit margin and posture margin along the whole route, not just approach azimuth and tilt. Before a route enters the close-hand region, test whether the required outward swivel is reachable and guard-valid; verify its achieved elbow angle rather than assuming requested swivel equals achieved posture change. If the route loses that margin, choose another orientation or IK branch, or plan a validated retreat/reorientation that restores it. Consider moving the idle arm to a safe parking pose when useful, one arm at a time. Do not use an unchecked home prefix as an escape. Return structured recovery facts such as elbow_recovery_feasible, limiting_joint and validated alternatives instead of treating 'elbow +15' as a guaranteed remedy.",
      "expected_effect": "Avoids reaching the recorded pre-grasp pose with J7 at its lower bound and no available outward swivel. A correction is selected for its ability to support the remaining route, rather than only fixing the current elbow angle.",
      "risk": "Additional margin requirements reduce the feasible workspace, and parking or retreat introduces more motion. Thresholds should reflect calibration and tracking error, and every alternative must pass the same path validation."
     },
     {
      "rank": 4,
      "title": "Add observation checkpoints and explicit skill lifecycle status",
      "file": "code/vendor/physical_rsi/control_excerpt.py: Controller.action, discard_queue; code/vendor/physical_rsi/skills.py: SkillPlanner.expand, plan_grasp_holder",
      "change": "Execute holder grasping in resumable stages: safe transit, observed pre-grasp, final approach, observed pre-closure, close, verified lift. Insert mandatory observation checkpoints after transit and before closure; compare the holder pose with the plan and invalidate the remaining queue on displacement, tipping or insufficient visibility. Use automatic checks for routine continuation and request an H0 decision when evidence is ambiguous. Track parent skill status separately: 'expanded' when primitives are queued, 'running', 'aborted' with completed/discarded steps, and 'complete' only after all required stages. Report cumulative skill travel as well as current-primitive travel.",
      "expected_effect": "Stops execution when the holder no longer matches the upright grasp plan, and makes clear that the second refusal occurred after three successful pre-grasp moves. Prevents macro expansion being mistaken for a completed grasp.",
      "risk": "Checkpoints add latency and perception can be occluded by the hand. If evidence is unavailable, continuation must wait for a validated view or retreat rather than silently trusting stale geometry."
     },
     {
      "rank": 5,
      "title": "Reject uncertain holder orientation and stale refreshes",
      "file": "code/vendor/physical_rsi/object_vision.py: detect, fit_circle, public; code/vendor/physical_rsi/skills.py: SkillPlanner.refresh, object, plan_grasp_holder",
      "change": "Separate object identity from pose classification. Estimate holder axis/opening orientation and support consistency from depth, with confidence and visibility fields; do not infer an upright holder solely from height and a fitted XY circle. Check rim-fit quality, fit coverage and dimensions against tracked geometry. A large diameter/height change or conflicting visual orientation should yield pose_uncertain or toppled, not an executable upright grasp. Make refresh return explicit matched/stale/ambiguous status and observation age; block contact stages on stale or ambiguous geometry. Preserve identity through tipping instead of treating fragments as pens. Route a toppled holder to a separately validated recovery plan.",
      "expected_effect": "The tick-48 42 mm/104 mm/0.54 detection would trigger reassessment rather than reuse of vertical-holder grasp geometry. It also prevents silent use of an old object pose when refresh cannot find a match.",
      "risk": "Thresholds based on this single episode may overfit, and a partial rim can still be a valid upright holder. Use multiple geometric and temporal cues; return uncertainty when depth cannot resolve the pose."
     },
     {
      "rank": 6,
      "title": "Make recovery instructions match executor and guard behavior",
      "file": "code/vendor/physical_rsi/policy_excerpt.py: SKILLS_RULE, ELBOW_RULE; code/astra_instructions_as_sent.txt: generated instructions; code/backend/realbot/drivers_excerpt.py: arm_bodies",
      "change": "Replace 'a refusal says why and nothing moved' with 'the refused tick moved nothing; earlier ticks and skill steps may have executed—inspect primitive and parent-skill progress'. Replace unconditional redetect-and-retry with failure-specific guidance: perception/grasp miss → reobserve; posture/joint limit → require a changed, validated route; scene disturbance → invalidate the contact plan and assess recovery. State that elbow corrections are constrained by joint limits and require feasibility checking, especially when a joint has little margin. Remove the blanket prohibition on explicit elbow recovery, while making planner-managed recovery the default. Claim automatic elbow opening only when the implementation actually supplies it. Generate safety distances from runtime constants; remove the conflicting hard-coded 2 cm gripper/forearm claim. Explain the guard's actual inward-motion rule and separately label any stricter planning target.",
      "expected_effect": "Prevents repeating the same causal failure after redetection, improves interpretation of partially executed skills, and discourages decision 6's infeasible elbow-only recovery at the J7 bound.",
      "risk": "Prompt changes alone cannot fix planning geometry. Keep the recovery policy concise and backed by structured executor facts so it does not become another conflicting instruction block."
     },
     {
      "rank": 7,
      "title": "Require evidence before registering a held object",
      "file": "code/vendor/physical_rsi/control_excerpt.py: Controller.action expect_object branch; code/vendor/physical_rsi/skills.py: SkillPlanner.grasped, context",
      "change": "Change the current acceptance branch so missing finger feedback produces grasp_unverified and aborts dependent actions instead of registering a held object. Treat a sufficiently large jaw opening as a grasp candidate, not proof of attachment. Register tentative grasp geometry, perform a short validated lift with an observation checkpoint, and confirm coherent object motion before enabling present_holder or insertion. Invalidate attachment and tool-frame geometry on evidence of slip or contradictory observations.",
      "expected_effect": "Closes a downstream false-success path: currently opening=None falls through to grasped(), and blocked jaws alone establish held_objects. This did not cause the recorded failure because closure never ran, but would undermine validation once the approach is repaired.",
      "risk": "Visual attachment verification can be ambiguous under occlusion, and a verification lift itself needs a safe path. Preserve an explicit uncertain state and stop dependent manipulation when confirmation is unavailable."
     }
    ],
    "confirm_next_run": "First, replay the recorded initial and tick-16 states through the revised planner and shared executor rollout. The original first route must be rejected before motion for the 30.2 cm/64.9-degree posture transition; the original second route must be rejected or changed before its 34.7 cm/65.8-degree transition. From the recorded tick-48 state, an outward elbow-only recovery must report the J7 limitation without issuing motion. Test that any replacement route passes the unchanged guard, including elbow/home prefixes, opening changes and joint-space intermediate samples. Replay the supplied perception frames: tick-16 should retain a credible upright-holder estimate, while tick-48 must not authorize a vertical-holder grasp. Exercise missing gripper feedback and partial-skill rejection to verify uncertain attachment and accurate cumulative progress reporting.\n\nIn the physical run, log predicted versus measured joint paths, minimum joint margins, elbow angles, actual opening-dependent pinch distances, scene-clearance estimates and parent-skill stage receipts. Record chest/head/wrist views at transit, pre-grasp, pre-closure and lift. Confirm that the holder remains upright and stationary within measurement uncertainty until intentional grasp contact, no finger enters its opening during transit, and the measured grasp route retains the required posture and recovery margin without either recorded refusal. Confirm attachment by coherent holder motion during lift, not command echo or jaw opening alone. Finally, verify each pen enters the held holder, account for initially merged detections through subsequent views, and show the holder upright and supported on the table after release with all pens inside. An absence of guard refusals or a planner 'complete' receipt alone does not confirm the fix."
   },
   "model_returned": "gpt-6-astra",
   "created_utc": "2026-10-20T10:39:09Z"
  },
  {
   "case": "case3-run3",
   "run": "20261020_152415",
   "request_id": "resp_07cb84881488010f016ad7453103808193a93fc83ddec52cf9",
   "usage": {
    "input_tokens": 59099,
    "output_tokens": 3473,
    "reasoning_tokens": 288
   },
   "response_sha256": "c4f75f8ff368b0a65c6cbea9ee5fafe69a8e151b0c0e1d0487a4cff19fded6a7",
   "astra_output": {
    "diagnosis": "The immediate failure was a repeated grasp-classification dead end, followed by an operator stop; it was not a safety-guard rejection or a demonstrated failed lift. In log §2, decisions 2 and 4, both grasp_holder closes produced measured_opening_mm=0.0 against a 40 mm threshold. Controller.action therefore declared grasp_missed, discarded each lift, and never populated held_objects. Decision 5 then requested present_holder, which correctly refused because no holder was registered. Decision 6 requested a 30 mm upward nudge, but §4b and §5 establish that it never executed: ticks end at 78, observation 79 is the last observation, and termination was operator_stopped/stop_file. No pen was picked or inserted.\n\nThe critical unresolved issue is whether gripper telemetry represents physical aperture. The wrist images images/t048_right_wrist_after_first_close.jpg and images/t077_right_wrist_after_second_close.jpg show separated finger assemblies flanking the holder, apparently contacting opposing sides, despite the reported zero opening. The corresponding chest images show the holder still at the table, without demonstrated lift or attachment. The t079 images retain essentially the same configuration. These images support a telemetry-versus-geometry inconsistency, but cannot prove gripping force, secure attachment, or that visible linkage separation equals pad aperture. Log §4b records command-return readings 64 and 38 at ticks 44 and 73, followed by observation openings of exactly 0 mm; opening commands return 999 and 899, followed by exactly 90 mm. Under the supplied conversion, 64 and 38 mean 5.76 and 3.42 mm, not an opening consistent with a roughly 66 mm holder. These differences could include normal settling; they do not by themselves prove a command echo. However, RobotIO.read takes hand position[0] directly as measured aperture without establishing its hardware semantics, and observe labels that conversion as physical finger positions. Preflight responsiveness does not establish obstruction-sensitive position feedback. The most important next investigation is therefore telemetry provenance and calibration, rather than assuming either an empty grasp or a secure grasp.\n\nThe harness amplified the inconsistency. Controller.action interprets an implausibly small reading as definitive 'nothing between them', while a missing reading takes the opposite path and registers the object. Neither branch verifies attachment. The prompt explicitly directs detect-and-retry after grasp_missed, so decision 4 repeated the same azimuth 105 degrees, tilt 15 degrees approach after the holder centre changed only about 3 mm. A second close reproduced the same disagreement. The model then treated visual straddling as grounds for presentation and an improvised lift, without a supported diagnostic transition from unknown attachment to verified holding.\n\nThere is insufficient evidence to blame approach error or double compensation. The 5.5–5.6 mm errors in §4a are recorded before the completion tick's final command: §4b shows the wrist reaching approximately the requested pose at ticks 42–43 and 71–72 before closure. Both closes explicitly back the wrist off by 22.8 mm, consistent with the linkage model at 90 mm opening. The planner's open-tip offset and the backend's closing back-off are complementary, although their calibration and execution need improvement. All 79 tick receipts were executed without guard problems (§3). This establishes that the guard accepted its modeled geometry, not that it validated physical object attachment.",
    "proposals": [
     {
      "rank": 1,
      "title": "Validate gripper feedback provenance before using it as measured aperture",
      "file": "code/backend/realbot/gripper_io_excerpt.py :: RobotIO.read, RobotIO.set_hands; code/backend/realbot/env_excerpt.py :: RealBotEnv.observe",
      "change": "Trace st['hand_<side>']['position'][0] to the device/driver field and establish whether it is measured mechanism position, requested position, or an estimated state. Add a feedback record containing raw_value, source_field, device/sample timestamp, commanded_target, command_return_value, calibrated_opening_m, and validity. Only emit finger_joint_positions_m as physical measurements when that provenance and calibration are validated; otherwise emit an explicit unavailable/untrusted status. Validate the mapping using an empty gripper and known-width fixtures under a controlled bench procedure, comparing independent pad-gap measurements with timestamped feedback throughout closing and settling. Test whether a blocked close reports the obstruction width or merely converges to the command. Do not automatically reinitialize or cycle a gripper around a possibly held object.",
      "expected_effect": "Resolves the central ambiguity behind both grasp_missed events and prevents commanded or invalid state from masquerading as a contact measurement. If the feedback is genuinely measured and correct, the same instrumentation establishes that the next investigation must focus on physical pad placement or slipping.",
      "risk": "The available hardware interface may not expose trustworthy position feedback. Marking it unavailable will require a supported visual verification route and may slow execution. Existing calibration assumptions must not be replaced solely to make this episode pass."
     },
     {
      "rank": 2,
      "title": "Introduce an explicit uncertain-grasp state and bounded attachment verification",
      "file": "code/vendor/physical_rsi/control.py :: Controller.action grip completion; code/vendor/physical_rsi/skills.py :: SkillPlanner.grasped, context, expand and new grasp verification stage",
      "change": "Replace the binary opening threshold with states empty, candidate_contact, attachment_unknown, verified_held. Pseudo-code: if feedback is missing, untrusted, stale, or conflicts with current visual geometry: state=attachment_unknown; pause the remaining macro; return status='grasp_unverified' with evidence and permitted recovery actions. elif validated aperture is compatible with the object's cross-section: state=candidate_contact; pause before normal carry. elif validated aperture is near the calibrated empty-close value and current images support a miss: state=empty; return grasp_missed. Never call grasped() merely because opening is None or above a fixed threshold. Add a verification stage that obtains fresh wrist/global images, checks actual pad placement, and, when a guarded route and plausible support are established, permits only a slow 5–10 mm vertical attachment test. Require independently tracked holder motion in the world, a stable holder-to-wrist transform, and evidence of separation from the table before promoting to verified_held. Stop the test on slip, unexpected motion, or lost visibility. Re-measure the holder pose after successful verification before storing its tool-frame geometry. Preserve candidate geometry separately for conservative collision checking.",
      "expected_effect": "Makes contradictory feedback actionable without falsely declaring either a miss or success. A successful small verification lift can establish the prerequisite for present_holder; an unsuccessful one yields a specific recovery outcome instead of repeating the same close.",
      "risk": "Even a small lift can slip or tip an insecure object. It must be conditional on measured geometry, clearances, bounded motion, and adequate visibility. Visual tracking can confuse gripper motion with object motion, so a fixed camera and table reference are necessary."
     },
     {
      "rank": 3,
      "title": "Replace blind retry instructions with cause-specific recovery",
      "file": "code/vendor/physical_rsi/policy_SKILLS_RULE.txt :: SKILLS_RULE source in policy.py; code/vendor/physical_rsi/control.py :: grip-check and rejection feedback",
      "change": "Replace 'If a skill is refused or ends grasp_missed, run detect_objects again and retry' with: 'Use the reported failure category. For confirmed geometric misses, reobserve and change the grasp geometry before retrying. For feedback disagreement or unavailable feedback, use grasp verification; redetection alone does not resolve sensor validity. present_holder requires verified_held. Do not use an unrestricted nudge to bypass that prerequisite.' Include attachment_state, evidence_quality, retry_cause, completed_motion, and allowed_next_actions in receipts. Track failure fingerprints by associated physical object, approach, and cause rather than transient detection ID; reject an unchanged retry unless new evidence changes the diagnosis. Give grasp-verification observations and diagnostic read-only queries their own bounded allowance so the exhausted general query budget does not force a motion.",
      "expected_effect": "Prevents decisions 3–6 from becoming detect, repeat, unsupported presentation, then improvised lift. Preserves useful autonomous recovery while directing the model toward evidence that can actually distinguish a miss from faulty sensing.",
      "risk": "Overly strict fingerprinting could suppress a valid retry after object motion. Query exemptions need explicit bounds and a terminal diagnostic outcome to avoid replacing a motion loop with an observation loop."
     },
     {
      "rank": 4,
      "title": "Model closure compensation from actual aperture and replan after contact",
      "file": "code/backend/realbot/env_excerpt.py :: RealBotEnv.grip_compensation, execute; code/vendor/physical_rsi/skills.py :: tip_retract, plan_grasp_holder, plan_pick_object",
      "change": "Use one calibrated linkage and aperture model shared by the planner and backend instead of fixed OPEN_TIP_RETRACT_M plus a duplicated implementation. Preserve pad position using delta_x=tip_retract(w_before)-tip_retract(w_after), with trustworthy measured aperture or an explicitly bounded alternative. Implement guarded small closure/back-off increments so compensation follows actual closure rather than backing off for the full commanded empty-close stroke before learning where an object stops the jaws. At plausible contact, stop further commanded tightening and wrist compensation according to the validated hardware control mode. If compensation IK fails, return an explicit refusal or replan; do not silently execute the uncompensated close. Log predicted and observed pad displacement. After the contact/verification stage, generate the lift from the current measured wrist and object pose instead of retaining the pre-close absolute lift waypoint.",
      "expected_effect": "Prevents excessive back-off if a holder stops closure at a wide aperture and avoids a subsequent lift that inadvertently moves forward toward the old pre-compensation wrist position. Makes the intended fingertip trajectory auditable without assuming the logged 22.8 mm back-off was itself erroneous.",
      "risk": "Stepped compensation can introduce contact shear if aperture feedback is delayed or inaccurate. It depends on proposal 1 and needs bench validation across empty closure and representative object widths. Eliminating compensation entirely would reintroduce up to roughly 25 mm of fingertip advance."
     },
     {
      "rank": 5,
      "title": "Guard measured gripper transitions and conservatively represent uncertain objects",
      "file": "code/backend/realbot/env_excerpt.py :: RealBotEnv.held, check, execute; code/backend/realbot/safety.py :: Guard.check, spheres",
      "change": "Correct the closing-obstruction comparison in held(): a closing jaw stopped short of its requested opening has measured_w > requested_w + tolerance, not measured_w < requested_w - tolerance. Treat an opening command stopped below its target as a separate condition. Feed the guard current measured aperture and proposed aperture, then evaluate the actual arm-then-hand execution phases and sampled linkage motion; do not calculate both current and target clearances with the target opening alone. Carry candidate/unknown object geometry from proposal 2 into collision checks even when feedback reports zero. Represent the holder using its height, radius and pose uncertainty rather than only a sphere of radius aperture/2+5 mm at the pinch point. Keep joint, camera, table and arm-distance protections enabled throughout verification and recovery.",
      "expected_effect": "Fixes a concrete sign error for partially closed commands and prevents uncertain attachment from making the holder disappear from collision geometry. Also closes the gap where a grip-only motion can be treated as having unchanged clearance because the guard uses the commanded aperture for both endpoints.",
      "risk": "Conservative uncertain-object volumes can block feasible recovery or insertion. Use explicit uncertainty bounds and task-appropriate contact geometry, rather than globally weakening separation thresholds. The sign error was not the direct cause here because both closes commanded zero and the reported measured aperture was also zero."
     },
     {
      "rank": 6,
      "title": "Add a pre-close perception checkpoint and improve grasp geometry quality checks",
      "file": "code/vendor/physical_rsi/skills.py :: SkillPlanner.plan_grasp_holder, refresh, expand; code/vendor/physical_rsi/object_vision.py :: detect, fit_circle",
      "change": "Split grasp_holder into approach, pre-close validation, close, and verification stages, with a fresh observation between the contact approach and closure. Validate the holder's cross-section at the chosen grasp height, both pad locations, lateral centering, and usable opening margin; do not assume rim diameter is the body width of a tapered hexagonal holder. Return detection age, refresh success/failure, fit residual, visible rim coverage and geometry uncertainty. Reject or reobserve an unreliable refresh rather than silently using old geometry. Check circle radius and residual again after least-squares refinement. Choose pre-close opening from calibrated maximum aperture and measured body width plus uncertainty; remove the mismatch between allowing widths up to 95 mm and the 90 mm command conversion. On a confirmed geometric miss, require a measurable correction to approach, centering, or grasp height before reclosing.",
      "expected_effect": "Makes physical placement errors distinguishable from feedback errors and prevents repeated blind closure on an unchanged pose. Uses the wrist view that showed the ambiguous contact configuration before committing to another close.",
      "risk": "Occlusion may prevent reliable body-width or pad measurements and add observation latency. The initial rim fits were already strong, 0.92 and 0.97, so detector changes alone should not be presented as the established fix for this episode."
     }
    ],
    "confirm_next_run": "First validate telemetry independently: empty closure should produce the calibrated empty gap, while controlled known-width obstructions should produce consistent measured aperture with timestamps and identifiable provenance. Command-return values and subsequent observations must be explainable as the same measured trajectory; a blocked gripper must not simply report the requested endpoint. Replay the episode's zero-aperture/visible-straddling case through the revised controller: it should produce attachment_unknown, pause normal carry, and avoid the unchanged detect-and-retry sequence. Missing feedback must never register an object as held. Test the corrected held-object comparison and grip-only clearance checks, including uncertain holder geometry and a compensation IK failure.\n\nIn the robot run, save synchronized chest and wrist images immediately before closure, after closure, and after the bounded verification motion, together with raw hand telemetry, compensation displacement, measured wrist pose and attachment-state transitions. Confirmation requires the holder to rise by the measured verification displacement in the fixed-camera/world estimate, develop a visible or depth-supported table gap, and maintain its relative pose in the wrist view. These measurements must be independent of the stored held-object transform; FK predictions are not evidence of attachment. Only then should held_objects become verified and present_holder proceed without the 'holds no upright object' refusal. A stationary or slipping holder must instead trigger a specific recovery outcome without repeated tightening or a 30 mm speculative lift. Finally, verify the full task: each visually distinguished loose pen is inserted and remains in the holder, the holder is placed upright and released on the table, and the final scene contains no remaining task pens on the tabletop. An operator stop or an unexecuted requested action must remain explicitly distinguished from an executed failure or successful verification."
   },
   "model_returned": "gpt-6-astra",
   "created_utc": "2026-10-20T10:40:49Z"
  },
  {
   "case": "case4-run4",
   "run": "20261020_153210",
   "request_id": "resp_0fec6876cfdf05ba016ad7457bb3e481979687830b098abfbd",
   "usage": {
    "input_tokens": 64514,
    "output_tokens": 4213,
    "reasoning_tokens": 410
   },
   "response_sha256": "d243c2db4831d0e6490e9df8ce6d0fc47d401c0d3f1be0bfa133dcc03df5b092",
   "astra_output": {
    "diagnosis": "The episode had two distinct failures: an insertion did not leave the fifth pen inside the holder, and recovery repeatedly failed to plan a grasp of the remaining thin pen. The run then ended through the operator stop file, not a motion timeout or exhausted action budget. Log §7 states that four pens remained in the holder, decision #47 never executed, and place_holder was never called.\n\nThe fifth insertion was mechanically executed but not verified as an object-level success. Before it, img1_tick629_cam_right_wrist.jpg shows a crowded opening with a broad object occupying substantial space. Afterward, img2–img4 at tick 723 show a pen outside the holder on its right; img3 shows the crowded opening and external pen particularly clearly. Decision #42 correctly withdrew the success claim. Log §6 records the insertion reaching its wrist target, opening the left jaws to 90 mm at tick 714, and completing withdrawal at ticks 718–722, without a safety rejection. The insertion completion receipt reports only 1.718 mm wrist position error. This argues against a gross failure to execute the wrist command; it does not establish that the pen tip entered the opening. SkillPlanner.plan_insert_into_holder always targets the modeled rim centre, queues descent, release and withdrawal without a visual checkpoint, and ignores existing contents. Its pen geometry comes from a tabletop detection transformed into the measured wrist frame, rather than a measurement of the actual grasped pen. Crowding, inaccurate object registration, displacement of an existing pen, or snagging during release/withdrawal remain possible. The supplied frames cannot determine which pen escaped or when; synchronized views during ticks 664–722, especially before release and during withdrawal, would settle this.\n\nThe thin-pen planning failures have a concrete code-level explanation. Decisions #6, #14 and #44 report only two candidates, both unreachable. In plan_pick_object, the tilted candidate must satisfy abs(k) <= opening/2 - 8 mm. Given its construction of m_z, a low object requires centre_z - table_z - 6 mm >= 8 mm * abs(jaw_axis_z). For the final pen, top is approximately 13–14 mm and the grasp centre is approximately 6.5–7 mm high. This excludes the generated tilted approaches and leaves the two vertical jaw signs. Changing the starting wrist orientation, as proposed in #47, does not expand that candidate family. Also, expand's fallback from the home pose applies to pick_object and grasp_holder, but excludes pick_and_insert, despite that composite using the same picking planner. Decisions #18/#20 additionally show reachable IK probes at the J6 bound followed by execution refusals in #19/#21; the omitted reach_failure and kinematics implementation prevent identifying the precise solver mismatch.\n\nOther failures exposed mismatches between planning and execution. At ticks 340 and 349, skills labeled 'open to 73/76 mm' actually narrowed the previously 90 mm jaws, triggering grip compensation and violating the elbow rule. Some compensation steps already moved the wrist, despite receipts saying nothing moved on the rejected tick. Skill planning does not include this compensation path. At tick 564, the runtime sphere guard rejected an insertion route that the skill planner had accepted using wrist distance and posture checks. The guard's jaw-width sphere also cannot represent a long pen, the holder's full extent, or its contents. The earlier contact at tick 182 occurred well above the table, consistent with decision #11's reported overlap at the holder, although no supplied image captures that event.\n\nThe holder tilt cannot explain the fifth insertion failure: img5 at tick 744 already shows the external pen before the right-hand nudge. The tilt executed at ticks 744–747; subsequent picks were refused before movement. Img6 at tick 752 still shows loose objects and the holder in the right hand. Finally, automatic homing proceeded with that hand occupied, according to §7; no additional damage is established, but the shutdown policy did not complete a controlled placement.",
    "proposals": [
     {
      "rank": 1,
      "title": "Make crowded insertion a staged, visually verified operation",
      "file": "code/vendor/physical_rsi/skills.py: SkillPlanner.plan_pick_and_insert, plan_insert_into_holder, insert_candidates; code/vendor/physical_rsi/control.py: Controller.action",
      "change": "Replace the single insertion queue with persistent stages: verified_grasp -> stand_off -> verify_alignment -> incremental_insert -> verify_seating -> release -> verify_release -> withdraw -> verify_retention. End the primitive queue at each observation-dependent stage and expose the pending stage to the model. At stand-off, estimate the actual lower pen endpoint, holder opening boundary, and occupied regions using current calibrated views. Choose a target within free space after accounting for pen cross-section and measurement uncertainty; do not always use the rim centre. Replan whenever the holder moves. Descend in bounded increments near contents, and do not enqueue release until images support entry into the opening. After release, inspect before withdrawing along a path that avoids standing pens. If visibility cannot establish entry, obtain another view or retreat while retaining the pen. Record insertion success only after the pen remains inside following withdrawal.",
      "expected_effect": "Directly addresses the unobserved failure between stand-off, release and withdrawal in the fifth insertion. It also makes the operator's free-slot instruction actionable: tilting the holder or reducing depth alone does not make the existing centre-targeting skill choose that slot.",
      "risk": "Additional observations increase runtime. Occlusion and reflective depth may make verification inconclusive; the system must pause or reobserve rather than fabricate a clear corridor. Shallow insertion can leave a pen unstable, so 25 mm must not become an unconditional fallback depth."
     },
     {
      "rank": 2,
      "title": "Generate feasible thin-pen grasps and repair the composite fallback",
      "file": "code/vendor/physical_rsi/skills.py: SkillPlanner.plan_pick_object, expand, plan_pick_and_insert",
      "change": "Log candidate counts before and after geometry filtering, with reasons and per-waypoint IK failures. Replace the fixed 8 mm pad-end allowance with a calibrated contact model using actual pad geometry, pen thickness, measured opening, fingertip clearance and uncertainty. Search a finer set of tilts and jaw openings, plus grasp positions along a single pen's measured axis where the pads can make contact safely. For every candidate, check both fingertips throughout closing and compensation; do not simply lower PEN_TIP_ABOVE_TABLE_M or remove the contact allowance. Refactor the empty-hand pick fallback into a shared function used by both pick_object and pick_and_insert, and validate the route to its alternative start pose. Return a structured 'no safe grasp in candidate family' result when appropriate.",
      "expected_effect": "Prevents the remaining thin pen from repeatedly receiving only the same two vertical candidates. Exposes whether the limiting factor is contact geometry, reachability or path clearance, and gives pick_and_insert the recovery behavior already available to pick_object.",
      "risk": "A larger search costs planning time. End grasps can slip or change the insertion endpoint substantially, so the grasped object's geometry must be remeasured. Calibration must establish that any newly admitted contact is physically possible; broadening candidates must not weaken table protection."
     },
     {
      "rank": 3,
      "title": "Plan grip compensation explicitly and report partial motion truthfully",
      "file": "code/backend/realbot/env_excerpt.py: grip_compensation, execute; code/vendor/physical_rsi/skills.py: plan_pick_object; code/vendor/physical_rsi/control.py: rejection and hold synchronization",
      "change": "Extract a side-effect-free grip-transition planner that takes measured joints and aperture and returns compensation targets, jaw transition geometry and guard results. Preflight its complete sequence before executing the first back-off substep, then retain runtime checks against measured state. Include this transition in skill feasibility checks. If it violates posture near the holder, first plan a clearance retreat at the existing aperture, then resolve the grip transition again from the new state. On any later rejection, return executed_substeps, measured final joints/wrist, whether the jaw command was applied, and remaining motion; synchronize Controller.hold from that measured state. Replace blanket 'nothing moved' wording with separate statements about the rejected substep and preceding executed motion.",
      "expected_effect": "Prevents the repeated ticks 340/349 compensation failures and eliminates misleading no-motion receipts after 8.7 mm or 4.7 mm of wrist travel. Makes an operation labeled 'open' correctly account for narrowing from a previous wider opening.",
      "risk": "Preflight cannot eliminate discrepancies caused by actual motion or contact, so runtime guarding remains necessary. Compensation must remain enabled to protect fingertip position. A generic 100 mm retreat is insufficient; clearance must be measured and its whole path checked."
     },
     {
      "rank": 4,
      "title": "Use the runtime safety model during planning and represent object extent",
      "file": "code/vendor/physical_rsi/skills.py: SkillPlanner.chain, insert_route, plan_place_holder; code/backend/realbot/safety.py: Guard.check, spheres, surface_distance; code/backend/realbot/env_excerpt.py: held",
      "change": "Provide the planner with a read-only backend collision-check interface using the same geometry, units, thresholds and interpolation policy as runtime. Validate planned motion, elbow, home and compensation segments against both arms before selecting a candidate. Retain runtime checks because execution may differ. Add conservative object geometry derived from verified measurements: an oriented capsule or box for a pen, holder wall/base geometry, and occupied volumes for inserted contents. Permit the intended pen to enter only a verified free interior corridor; do not exempt all held-object pairs from collision checking. Review held(): its current 'blocked' test w < commanded_opening - 5 mm detects failure to open, whereas an object resisting closure usually leaves w > commanded_opening + 5 mm. Separate these cases and combine them with verified attachment state.",
      "expected_effect": "Rejects or reroutes the tick-564 inter-arm conflict before entering it and reduces collisions with objects that jaw-width spheres cannot cover, including the earlier approach near the holder. Preserves the existing safety margins.",
      "risk": "A solid bounding sphere for the whole holder would incorrectly block legitimate insertion, while an overly permissive hollow model could miss wall contact. Object uncertainty must inflate occupied geometry without erasing the intended cavity. Jaw aperture alone remains insufficient evidence of attachment."
     },
     {
      "rank": 5,
      "title": "Treat held-object geometry as a verified estimate with provenance",
      "file": "code/vendor/physical_rsi/control.py: Controller.action expect_object branch; code/vendor/physical_rsi/skills.py: grasped, held_world, context, refresh; code/vendor/physical_rsi/object_vision.py: detect",
      "change": "Change grasp registration to pending rather than verified on jaw settling. If aperture is inconsistent or unavailable, stop dependent insertion steps and request a fresh observation. After a guarded lift, verify attachment through before/after views and measure the pen endpoints or holder rim/base in the current wrist frame. Store source tick, measurement method, uncertainty and verification status in held_objects; invalidate or update the estimate after observed slip or displacement. Report detection refresh failures rather than silently using stale geometry. Associate refreshed objects using appearance, dimensions and position, not nearest position alone. Mark wide detections as unresolved clusters until evidence identifies the grasped item. Preserve the holder's actual height after lifting: a fresh detector's height above the table is not its physical height.",
      "expected_effect": "Reduces insertion errors caused by treating pre-grasp tabletop coordinates as the actual grasp geometry. Prevents unconditional grasped() registration from promoting an unverified grasp to fact. Avoids confusing the elevated, partially occluded holder with its contents; detected rim diameters changed from 66 mm initially to about 32–34 mm late in the episode.",
      "risk": "Object landmarks can be occluded, and the supplied record does not prove that registration error caused the fifth failure. Reobserving may delay execution. The existing tool-frame transform already follows wrist motion, including the right-hand tilt; this change should improve measurement validity rather than discard that correct behavior."
     },
     {
      "rank": 6,
      "title": "Unify IK probing, candidate acceptance and execution",
      "file": "code/vendor/physical_rsi/control.py: Controller.ik_probe, reach_failure, action move/nudge branches; code/vendor/physical_rsi/skills.py: SkillPlanner.solve",
      "change": "Route probe, skill feasibility and motion initialization through a shared solve-and-validate implementation with explicit seed, usable joint bounds, tolerances and solver settings. Return a planning token containing the solved joints and relevant state version; reuse the validated result when that state remains valid, otherwise replan and state why. Prefer solutions with joint-limit margin. Include solver identity, residuals and bound violations in every IK refusal. Add a regression reproducing the #18/#19 and #20/#21 targets with the same measured seed; a probe accepted from that state must either initialize successfully or report a documented state change.",
      "expected_effect": "Removes the repeated 'reachable' probe followed by an unexplained execution refusal at J6, and makes boundary failures actionable.",
      "risk": "The exact mismatch cannot be established from the excerpts because reach_failure and the underlying solver are omitted. Sharing the solver does not establish collision safety, and a cached solution must never bypass current-state validation or the runtime guard."
     },
     {
      "rank": 7,
      "title": "Make recovery depend on changed evidence and verified task progress",
      "file": "code/vendor/physical_rsi/policy_SKILLS_RULE.py: SKILLS_RULE; code/vendor/physical_rsi/harnesses/h0_multi.py: policy, act and episode state",
      "change": "Replace the blanket 'detect again and retry' instruction with reason-specific recovery. Cache a failure signature comprising object association, geometry, candidate family, seed and rejection cause. Allow another attempt when one of those inputs meaningfully changes; otherwise select another reachable object or invoke the expanded grasp planner. State explicitly that changing the seed cannot create orientations absent from the candidate family. Describe held_objects as estimates and skill 'complete' as primitive completion only. Maintain a persistent inventory with states on_table, grasp_pending, held_verified, insertion_pending, retained_verified and uncertain. If a pen appears outside the holder, reopen the corresponding progress claim and resolve identity before updating counts. Require final inspection of the table and holder, then place_holder and visual confirmation of support and release before declaring completion.",
      "expected_effect": "Avoids the repeated thin-pen retry loops and preserves the good behavior in #42, where the model recognized that completed motion was not insertion success. Makes the unresolved small rear object and the escaped pen explicit remaining work.",
      "risk": "Object identity may remain ambiguous after occlusion or displacement, so counts must remain provisional. A failure cache must expire when genuine geometry or posture changes occur. Additional observations should target uncertainty rather than repeatedly request identical detections."
     },
     {
      "rank": 8,
      "title": "Stop safely without automatically transporting an occupied hand home",
      "file": "code/backend/realbot/env.py: end-of-episode homing path, omitted from env_excerpt.py",
      "change": "At an operator stop, stop both arms immediately and preserve the stop. Before any automatic homing, evaluate measured aperture, closing command, verified/pending held-object state and recent visual evidence. If a hand is occupied or attachment is uncertain, inhibit default homing for that arm and report the held load and current pose. Any subsequent controlled placement or recovery must occur through a separately authorized recovery procedure. During normal task completion, use place_holder with current geometry and confirm table support before release and final retreat.",
      "expected_effect": "Prevents an incomplete episode from automatically carrying the filled holder toward home, as happened after this stop. Clearly separates successful task placement from shutdown motion.",
      "risk": "Remaining stationary with a load requires suitable hardware hold behavior; power loss or an emergency stop may require a different established hardware procedure. The omitted shutdown implementation must be inspected before editing, and the bundle does not show that the recorded homing caused a spill."
     }
    ],
    "confirm_next_run": "Confirm the changes at both component and task levels. First, log candidate filtering and replay a thin pen with approximately 12–13 mm width and 13–14 mm measured top height: the planner should evaluate physically justified alternatives beyond the two vertical jaw signs, or return a specific safe infeasibility reason without repeating unchanged attempts. Reproduce the near-holder 90-to-73/76 mm aperture transitions: preflight should either accept the complete guarded compensation path or choose a safe clearance motion before starting, and any interruption must report actual partial travel. Reproduce the J6-bound probe targets using identical measured seeds and verify probe/execution agreement. Replay the tick-564 route and confirm that the planning guard identifies the conflict before execution while runtime margins remain unchanged.\n\nFor insertion, save synchronized chest, head and wrist frames at verified grasp, stand-off, each near-contact descent, immediately before release, after release and after withdrawal. Record measured pen endpoints, target free-space region, holder transform, uncertainty, minimum planned clearance and actual wrist/aperture traces. In a comparably crowded holder, evidence should show the incoming endpoint entering the selected free corridor, the pen remaining inside after withdrawal, and existing contents remaining retained. If a pen moves outside, the log must identify the stage and suspend success rather than continue the macro. Those frames will also discriminate misalignment, grasp slip, collision with contents and withdrawal snagging, which this bundle cannot settle.\n\nThe end-to-end confirmation is a reconciled inventory with all task pens retained, no unresolved pen-like objects left on the table, a completed place_holder operation, and images showing the holder supported on the table after the right hand opens and retreats. Primitive completion, confidence, jaw closure and absence of guard rejections alone are insufficient. Exercise an occupied-hand stop separately and verify immediate stopping without automatic homing of that hand."
   },
   "model_returned": "gpt-6-astra",
   "created_utc": "2026-10-20T10:42:03Z"
  }
 ],
 "judged": [
  {
   "case": "case1-run1",
   "engineering_fix": "pick_object opens only to object width + 25 mm, places the wrist by the fingertip retraction at that opening, lower fingertip 6 mm above the table (deployed 15:19)",
   "astra_matching": "Plan pen contact using both fingertips and the actual jaw opening",
   "verdict": "partial (core change same; other parts of the fix not proposed)"
  },
  {
   "case": "case2-run2",
   "engineering_fix": "every skill computes the two-hand posture case and passes it to the planner; elbow kept out only when hands are near (deployed 15:21)",
   "astra_matching": "Remove the dependency between posture validation and whether the other hand holds an object: all skills must supply both arms",
   "verdict": "partial (core change same; near-only elbow gating not proposed)"
  },
  {
   "case": "case3-run3",
   "engineering_fix": "a low gripper reading is reported as UNVERIFIED, the object is still registered and lifted, and the model is told to check the wrist image (deployed ~15:31)",
   "astra_matching": "Introduce an explicit uncertain-grasp state and bounded attachment verification",
   "verdict": "partial (same mechanism; Astra pauses and verifies with a small lift before registering, more conservative than the engineering fix)"
  },
  {
   "case": "case4-run4",
   "engineering_fix": "draft, not yet run: planner uses the guard arm-to-arm surface distance with 1 cm margin; open jaws only at pre-grasp; along-axis grasp offsets; lift and side retreat after release",
   "astra_matching": "Use the runtime safety model during planning and represent object extent",
   "verdict": "partial (planner-uses-runtime-safety-model same; other items partly or not proposed)"
  }
 ],
 "astra_found_unaddressed": [
  "held(): the blocked test compares in the wrong direction (an object resisting closure leaves the jaws wider than commanded); raised independently in cases 3 and 4, confirmed in code",
  "grip-compensation back-off substeps are outside the MotionBlocked handling (possible cause of the uncaught end of run 1)",
  "objects picked by manual primitives are not registered as held (run 1)",
  "a toppled holder is still classified upright (run 2)",
  "pick_and_insert has no home fallback (run 4)",
  "the prompt says a refused action moved nothing, which is not always true (all cases)",
  "auto HOME is triggered while a hand still holds the holder (run 4)"
 ]
}