Four independent tools
plan_observation— Compare proposed observations using their predicted effect on position uncertainty.stress_test_observation— Search declared calibration and timing perturbations for a counterexample to a stability claim.assimilate_observation— Refit supplied tracks with new angular observations, keeping measured and synthetic origins explicit.improve_schedule— Compare affordable deadline and optional-task changes, then check one finalist with a separate simulation.
Choose where to observe
plan_observation fits the supplied angular tracks, then compares up to 64 proposed observation series at the same future time. It predicts the longest one-standard-deviation position axis from the full position/velocity covariance and new angular information. It checks cost, station identities, sample limits and geometric elevation. It never treats predicted angles as measurements. The best candidate is best among the supplied admissible alternatives, under the stated local linear model.
Add information and check the forecast
assimilate_observation refits every original and newly supplied angular pair once. The original fitted mean initializes the solver; the old covariance is not added again as a prior. A new series can come from a later station without overlapping the old track times. Its measured or synthetic origin remains caller-declared and unverified. A smaller conditional covariance does not prove smaller error against unknown truth.
Look for a counterexample
stress_test_observation examines up to 32 fixed hypothetical angular biases or clock-correction changes. It asks whether the reconstruction remains usable and within a declared position-shift limit. Invalid perturbations are inadmissible; solver non-convergence is inconclusive. No counterexample found in a finite list is not a global robustness guarantee.
Apply the same approach to a schedule
improve_schedule compares up to 32 approved combinations of deadline extensions and optional-task removals. Required tasks are preserved. Positive caller-defined cost weights make changes comparable. Fixed Monte Carlo search uses a simultaneous error budget; one finalist receives a separately seeded fixed confirmation. Failed confirmation does not trigger retries on other finalists using the same validation results.
Assumptions remain visible
The observation model assumes constant velocity in spherical Earth-fixed coordinates, exact station positions and corrected clocks, and independent angular errors. Its covariance is a local conditional approximation. The schedule model assumes independent uniform duration variation. Neither model is automatically calibrated to real-world observations.
Optional orchestration
The capability planner can return a direct binding to each complete request. Its structural graph cost does not measure scientific quality. Forecast receipts cannot satisfy an acquired-observation contract: the system will not invent missing measurements. Tools can always be called independently over the public MCP endpoint.
Inspect and replay
The laboratory preserves the exact submitted example, returned native result and browser timing in a downloadable receipt. Public examples use synthetic data. Private scientific inputs and outputs are not copied into the public activity journal.