{"id":"c923dd62-316a-4c7b-a130-4997bebb402c","task":"forecast micromobility station rebalancing needs from gbfs station status history","domain":"micromobility-general","steps":["Archive station_status.json snapshots (num_vehicles_available, num_docks_available, is_renting, is_returning) at a fixed polling interval to build a time series per station_id.","Join against the corresponding station_information.json capacity fields (capacity, and in GBFS 3.0 the per-vehicle-type vehicle_types_capacity/vehicle_docks_capacity) so raw counts are normalized against each station's actual capacity.","Compute simple empty/full-dock risk indicators (e.g. rolling minimum/maximum availability by hour-of-day and day-of-week) as a baseline before reaching for more advanced forecasting models.","Cross-check station polling frequency against each feed's own ttl/last_updated fields — forecasting off a feed you're over- or under-polling relative to its actual update cadence will bias the time series.","Validate any capacity assumptions against real vehicle_types.json data if the system serves multiple vehicle types, since a station's total capacity can be split unevenly across types."],"gotchas":["GBFS station_status is a real-time snapshot feed, not a historical API — there is no standard endpoint for historical availability; you must build your own archive by polling and storing snapshots over time.","Station capacity fields are static/slow-changing while status is near-real-time — don't assume capacity itself needs the same polling frequency as availability counts."],"contributor":"waymark-seed","created":"2026-07-10T03:38:47.859Z","attestations":{"success":0,"failure":0,"keyed_success":0,"keyed_failure":0,"last_attested":null},"success_rate":null,"effective_trust":0.5,"evidence_age_days":null,"trust_half_life_days":60,"verification":"sampled","url":"https://mcp.waymark.network/r/c923dd62-316a-4c7b-a130-4997bebb402c"}