gaitkeeper 0.5.2

# golden trace in the training env (runs in the mjlab environment)
python tools/record_mjlab.py --task-path <unitree_rl_mjlab> --onnx <policy.onnx> --out runs/g1_golden

# contract from the exported files
gaitkeeper inspect --onnx <policy.onnx> --yaml <deploy.yaml> --out contract.yaml

# verify a golden trace or a harness log against a contract
gaitkeeper verify runs/g1_golden --onnx <policy.onnx> --yaml <deploy.yaml>
gaitkeeper verify harness_log.npz --contract contract.yaml --policy <policy.onnx>

# with a target: boundary D, the nominal closed loop and the model counterfactual
gaitkeeper verify runs/g1_golden --contract runs/g1_golden/contract.live.yaml \
    --onnx <policy.onnx> --mjcf <scene.xml> --seeds 12
gaitkeeper residual runs/g1_golden --contract runs/g1_golden/contract.live.yaml --mjcf <scene.xml>

# a task without a reference (L1 at most): schedule, held joints, punches
gaitkeeper task --deploy <deploy.yaml> --onnx <policy.onnx> --mjcf <scene.xml> \
    --schedule tour.yaml --hold left_elbow_joint,right_elbow_joint \
    --push-every 3 --push-first 20 --push-force 600

# Unitree deploy.yaml, read as what the robot runs (SDK tables: G1 29-DoF, H1)
gaitkeeper inspect --deploy <deploy.yaml> --onnx <policy.onnx>

# closed loop in a target MJCF; every result prints the controller assumptions
gaitkeeper run --deploy <deploy.yaml> --onnx <policy.onnx> --mjcf <scene.xml> \
    --command 0.5,0,0 --kick 3,0.5,0 --push 6,0,150,0,torso_link,0.1

# checks S16, S17a, S17b, S18, S19, S21 and the command response map
gaitkeeper check --deploy <deploy.yaml> --onnx <policy.onnx> --mjcf <scene.xml> --scenario 0,0,0.2
gaitkeeper envelope --deploy <deploy.yaml> --onnx <policy.onnx> --mjcf <scene.xml>

# behavior probes: standstill in the dead zone (two backends), after a kick,
# yaw while walking, trained kicks and force punches over seeds, fragility sweep
gaitkeeper envelope --deploy <deploy.yaml> --onnx <policy.onnx> --mjcf <scene.xml> \
    --push-seeds 10 --physics --json envelope.json

# observation layout from a trace (exit 0 inferred, 3 partial or abstained)
gaitkeeper infer runs/g1_golden --json layout.json
gaitkeeper infer harness_log.npz --no-raw          # (obs, action) only

# deploy values against training values, per joint
gaitkeeper deviation --deploy <deploy.yaml> --reference runs/g1_golden/contract.live.yaml --trace runs/g1_golden

Runner backends: native_implicit (default; PD inside MuJoCo every step), explicit_zoh (torque held over the training sim_dt; the MuJoCo step is changed to divide it and the change is printed), python_pd (debugging), standin_implicit (a position-implicit drive in damping and Euler, the way some engines integrate PD; used to test that boundary D does not turn a drive difference into a cause). Torque limits come from the MJCF unless --limits contract. A field the contract takes from no source prints CONTROLLER_ASSUMED. --preset fills named training facts (for example unitree_rl_lab_g1_29dof_velocity@4960b84) with provenance preset. A controller field from a preset still prints CONTROLLER_ASSUMED: the preset reads the training config at a commit, not the run that produced the policy.

pytest runs the unit suite on synthetic traces with a stand-in linear policy anywhere. Integration tests run on the fixtures (gaitkeeper fetch all) and on golden traces recorded with the mjlab recorder under runs/ ($GAITKEEPER_RUNS); each skips, naming what is missing, when its files are absent. They show:

• A harness log built correctly from the contract passes B, A and C, where contract numbers printed to 3 decimals are admitted only through the export_rounding tolerance class; with that class removed, C fails.

• A wrong policy file fails B.

• For each injected defect (history layout, order and reset fill; both quaternion misreads, (w, x, y, z) read as (x, y, z, w) and the reverse; gyro in the world frame; joint remap skipped on input or on output; joint velocity scale; a term never filled; action scale taken from the rounded yaml; one action scale factor on every joint; action offset dropped; one and two step action delays, with a repeated or an empty (zero) delay line; raw action clipped; kp scaled, kd scaled, both scaled; gains bound by index in the wrong joint order; three defects at once; simulator state read one step late), the comparator names the boundary, the term and the defect, and nothing else, without using falls.

• Effort limits are reported, never compared. A harness that clips effort below the contract's limit passes C with a LIMIT_DIFFERENCE_ACTIVE finding; the clip level is inferred from the effort plateau only when the joint follows the PD law on every other row, so a gain error is not explained away as a clip.

• On segments that cannot tell the contract from a known alternative (standing at zero command; one constant walking command), it returns UNDETERMINED rather than PASS, including when such an invisible defect is present.

• When two equally simple explanations fit, it names neither.

• A trace written by gaitkeeper's own runner is labeled SELF_CONSISTENT and capped at evidence L1.

• The reader finds the rounded wrist action scale in the shipped deploy.yaml, and the recorded mjlab G1 golden trace passes against the contract read from the exported files (integration tests).

• The Unitree deploy reader binds gains by SDK index and pose, scale and history by policy index, skips H1's empty SDK slot, and reads the mjlab G1 wrist action scale 0.07 as exact; against the ONNX metadata that is 6.7% low and the wrist kd 3.0% high, reported as deviations of the deployment.

• The streaming observation builder used by the runner gives the same vectors as the batch builder the comparator uses. Recurrent state is carried and zeroed at reset.

• S17a's bound of 4 matches a simulated one-joint PD (3.9 decays, 4.1 diverges). S17b separates a slow tipping mode from negative, complex and fast modes. S16 finds 0 mismatched pairs in the shipped unitree_rl_lab G1 yaml, 9 when the default pose is read in SDK order, and 3 kp and 3 kd when the gains are read in policy order.

• On the unitree_mujoco G1 scene (integration tests, Appendix A bounds): the unitree_rl_lab policy walks 4.69 m in 10 s at 0.5 m/s under python_pd; ignores vx 0.20 and walks at 0.22, ignores vy 0.25 and walks at 0.28, under both python_pd and native_implicit; does not turn in place at wz 0.2; falls in 1 to 2 s under zero action; falls under 1 s with armature 0 under python_pd and walks under native_implicit. The wrist roll margin is 3.88 at 2 ms; native_implicit has only the tipping mode outside the unit circle and python_pd with armature 0 has 11, the most negative near -49. The mjlab policy walks 4.82 m.

• Behavior probes (unit tests on hand-built inputs; integration tests on the unitree_mujoco G1 scene with the unitree_rl_lab policy): stillness needs all three measures (action std, joint speed, no contact change); the fall time comparison is suppressed when S17a warns or a joint sits at its torque limit; a fragility row names numerical instability only when S17a or S17b fires beyond the nominal model. The dead zone is a true standstill under both backends; after a (0.5, 0.5) m/s kick the robot returns to standstill at the vx and wz edges but starts walking sideways at the vy edge (+-0.25) and does not stop; over 3 seeds it survives the trained kicks and falls to 300 to 600 N punches; with armature 0 under python_pd it falls in under 1 s (no-policy baseline 0.62 s on the same model and backend), S17a warns, S17b fails with a tipping time constant between 0.2 and 0.6 s, and the fall time comparison is suppressed; under native_implicit it walks.

• Boundary D on the three mjlab golden traces against their own recorded model: at the calibrated floor (legs 1e-6 to 4e-5 N m clean RMS, arms 8e-5 to 5e-4, waist up to 1.8e-3, root 0.51 N and 0.11 N m; float32 source, float64 analysis). Legs are judged on swing steps only. An injected ankle armature change (+0.01, -0.002) is named on both legs, and the research fit recovers it with the right sign and size; armature, damping and effort limit changed together on one leg are named as that chain, never as one parameter (AT11); with joint friction on both sides an armature search recovers a wrist change; the stand-in drive shows armature -h^2 kp and damping -h kp exactly (Appendix B).

• The counterfactual on the mjlab golden trace with the target changed: floor friction 0.1 gives PHYSICS with contact parameters as the group whose swap restores the outcome; torso +15 kg gives mass and inertia, then body masses. The source's own model with a dead-zone task gives POLICY_UNDER_TASK (AT9). Armature 0 and floor friction 2.0 never give CONTRACT (AT1). A source with the stand-in drive is far above floor on every chain, its behavior unchanged, and a dead-zone task failure gives POLICY_UNDER_TASK, never PHYSICS (AT15).

• Every row of the plan's decision table is a test, with the invariants (no PHYSICS without a nominal failure, D above a calibrated floor and a counterfactual change; no PHYSICS or CONTRACT without a reference).

• The issue 145 setup (unitree_rl_lab policy on unitree_mujoco's G1, arms held, small commands, in-place turns, 600 N punches) gives TASK_FAILURE_OBSERVED / BEHAVIORAL_LIMITATION at L1, exit 5, with the caveats that a silent contract error is not excluded and nothing is attributed.

• infer recovers history length, layout, order and init on all four layouts from (obs, action) alone; labels every term with its scale and joint order from raw state (including a world-frame gyro); abstains with no boundaries when a column is constant or copies more than one column (a constant command, AT4), and claims no history length when noise removes the exact copies. On a 30 s closed-loop rl_lab trace with a command schedule it returns history 5, term major, oldest first, repeat-first init, gyro scale 0.2, joint velocity scale 0.05 and the Isaac joint order.

Measured outside the test suite (scripts and outputs under runs/, not committed):

• The 29 development harness logs (G1, unitree_rl_lab policy, unitree_mujoco scene, regenerated with qpos and qvel): verify names 29 of 29 as labeled (16 observation, 12 gain or action, 1 clean that returns UNDETERMINED because its command never changes). E0's baseline named 11 of 16 and 0 of 12. This is a development set: the comparator was fixed on it (effort clip levels, kp and kd named apart, empty delay lines, the second quaternion misread, zero scale as an unfilled term), so it is not evidence of accuracy on unseen harnesses. On the falling logs the harness clips at the MJCF limits (hip roll 88, waist roll and pitch 50) where training uses 139 and 25, reported as LIMIT_DIFFERENCE_ACTIVE.
• infer abstains on all 29 development logs (constant command), returns the full layout on the three recorded mjlab golden traces (no history, the phase pair labeled from observations, SDK joint order), keeps the structure but loses most labels under per-frame noise stored in history, and abstains under independent per-entry noise.
• Envelope, unitree_rl_lab G1 policy on unitree_mujoco (runs/step3): dead zone vx 0.20 (+) and 0.15 (-), vy 0.25, no in-place turning; yaw while walking tracks 67% to 73% inside the limit range; the vy kick hysteresis above; trained kicks survived on 10 of 10 seeds, punches on 0 of 10. The lateral and in-place yaw scenarios are NONE: no tracked command sits 1.25 times past the dead zone edge inside the limit range (vy edge 0.25, limit 0.30). Fragility: friction 2.0 (stand drift, fwd + yaw), softer contacts (stand drift) and kp x0.8 (fwd + yaw) miss the bar; armature 0 and a 5 ms step under python_pd are numerical (S17a and S17b fire); S17b passes at 5 ms under native_implicit. The mjlab G1 policy has only its by-design 0.05 dead zone, tracks yaw while walking at 74% to 99% and survives 2 of 10 punch runs; its rerun under the new rules is unchanged.
• S17b at a 5 ms step (unitree_rl_lab policy, unitree_mujoco G1): the complex pair at modulus 1.0001 is a real slow mode of the linearized standing system, not numerical. It is the same for finite difference steps 1e-4 to 1e-9, centered or forward; it is present at 2 ms with the same rate per second (0.025/s against 0.023/s, turning 0.025 rad/s), where the per-step tolerance hides it; it lives in base y, yaw and ankle roll, next to the exact translation and yaw symmetries, and comes and goes with the settle time. With the policy in the loop a yaw offset stays at 0.0100 rad for 45 s (the mode would predict 0.028). S17b now reports such a pair as drift, as it already did slow real modes; the per-step tolerance is unchanged.
• results.json (tools/results.py): 62 cases with a known cause (the injection corpus, the 29 development logs, the physics and task cases above), 55 confident outputs, 0 false confident attributions, abstention 6.5%; A detected 27 of 27, C 25 of 25, D 3 of 3. The development logs were used to fix the comparator, so this is not a measure on unseen harnesses.

They do not show that any of this holds for other frameworks, other robots, real harness logs, or the robot itself. Runner results are labeled with the controller assumptions they rest on and are evidence L1 at most.