Honeybee Model Editor

Use This Skill When

• The user wants a model-wide cleanup
• The user wants to remove several object categories together
• The user wants reset-like editing before rebuilding geometry
• The user wants scoped deletion on faces or rooms
• The user needs a general deletion workflow rather than a single narrow object type
• The user wants reusable schedules, modifiers, modifier sets, process loads, sensor grids, or views removed safely

Preferred Tools

query

Description Use first when the deletion scope is unclear.

Args

• target_type: str
• identifiers: list | None = None
• fields: list | None = None
• output_mode: str = "records"

Returns

• success: bool
• data: dict | list
• count: int when relevant
• missing: list

remove

Description Primary editing tool for destructive object cleanup.

Args

• operation: str
• identifiers: list | None = None
• options: dict | None = None

Returns

• success: bool
• message: str
• operation-specific result fields
• auto_save: dict when relevant

Removal Matrix

Model-wide cleanup

• remove(operation="all_apertures")
• remove(operation="all_doors")
• remove(operation="all_shades")

Face-scoped cleanup

• remove(operation="face_objects", identifiers=[...], options={...})

Use options for:

• apertures
• doors
• indoor_shades
• outdoor_shades
• sub_faces

Room-scoped cleanup

• remove(operation="room_shades", identifiers=[...], options={...})
• remove(operation="process_loads", identifiers=[...], options={...})

Room shades options:

• indoor_shades: bool
• outdoor_shades: bool

Process loads options:

• process_ids: list — List of process load identifiers to delete from the room. Omit to delete all process loads from the room.

Resource-aware cleanup

• remove(operation="schedule", identifiers=[...])
• remove(operation="schedule_day", identifiers=[...])
• remove(operation="schedule_type_limit", identifiers=[...])
• remove(operation="modifier", identifiers=[...])
• remove(operation="modifier_set", identifiers=[...])
• remove(operation="sensor_grid", identifiers=[...])
• remove(operation="view", identifiers=[...])

These operations may return blocked references instead of deleting immediately.

Examples

Reset all openings

remove(operation="all_apertures")
remove(operation="all_doors")

Remove all shading

remove(operation="all_shades")

Mixed face cleanup

remove(
    operation="face_objects",
    identifiers=["Face_1", "Face_2"],
    options={"apertures": True, "doors": True, "outdoor_shades": True}
)

Room-scoped shade cleanup

remove(
    operation="room_shades",
    identifiers=["Room_1"],
    options={"outdoor_shades": True}
)

Remove specific process loads from a room

remove(
    operation="process_loads",
    identifiers=["Room_1"],
    options={"process_ids": ["Process_A", "Process_B"]}
)

Remove all process loads from a room

remove(
    operation="process_loads",
    identifiers=["Room_1"]
)

Remove a custom schedule resource

remove(operation="schedule", identifiers=["Office_Occ_Schedule"])

Remove a sensor grid

remove(operation="sensor_grid", identifiers=["Grid_01"])

Resource deletion with blocked references

When a resource is still referenced, deletion is blocked:

# Step 1: Attempt deletion
result = remove(operation="schedule", identifiers=["OfficeOccupancy"])
# result may contain "blocked" with a list of referencing objects

# Step 2: Reassign the referencing rooms/loads to a different schedule
apply(operation="people", target_type="room", identifiers=["Room_1"],
      values={"occupancy_schedule_identifier": "AlternativeSchedule"})

# Step 3: Retry deletion
remove(operation="schedule", identifiers=["OfficeOccupancy"])

Query before delete

query(
    target_type="face",
    identifiers=["Face_1"],
    fields=["identifier", "apertures", "doors", "indoor_shades", "outdoor_shades"]
)

Return Guidance

• Use message for quick operation confirmation.
• Use results for per-face or per-room detail.
• Use removed, removed_count, or remaining_count when returned by model-wide operations.
• Use blocked and reference summaries when removal is denied for reusable resources.
• Mention auto_save when shared-memory writeback occurs.

Notes

• Prefer the narrowest valid deletion scope.
• Save a version first when the cleanup is broad or destructive.
• For reusable resources, query first and expect safe-block behavior if the resource is still referenced.
• Re-query after cleanup if the user wants confirmation or downstream editing depends on clean state.