honeybee-door-editor — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited honeybee-door-editor (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
queryDescription Use for door inspection, door counts, geometric properties, and related shade relationships.
Args
target_type: str — Use "door"identifiers: list | None = Nonefields: list | None = Noneoutput_mode: str = "records"Available fields for doors
| Field | Description |
|---|---|
identifier | Door identifier |
display_name | Display name |
boundary_condition | Boundary condition string |
is_glass | Whether the door is glass |
is_exterior | Whether the door is exterior |
has_parent | Whether the door has a parent |
parent | Parent face identifier |
top_level_parent | Top-level parent (room) identifier |
vertices | Vertex coordinates |
normal | Normal vector |
center | Center point |
area | Area (m²) |
perimeter | Perimeter (m) |
tilt | Tilt angle (degrees) |
altitude | Altitude angle |
azimuth | Azimuth from north (degrees) |
indoor_shades | Indoor shade identifiers |
outdoor_shades | Outdoor shade identifiers |
removeDescription Use for deleting doors either model-wide or face-scoped.
Args
operation: stridentifiers: list | None = Noneoptions: dict | None = NoneReturns
success: boolmessage: strauto_save: dict when relevantquery(
target_type="door",
fields=["identifier"],
output_mode="count"
)query(
target_type="door",
identifiers=["Door_1"],
fields=["identifier", "boundary_condition", "is_glass", "area",
"parent", "top_level_parent", "azimuth"]
)query(
target_type="door",
fields=["identifier", "is_glass", "boundary_condition", "area",
"tilt", "azimuth", "parent"],
output_mode="list"
)remove(operation="all_doors")remove(
operation="face_objects",
identifiers=["Face_1", "Face_2"],
options={"doors": True}
)remove(
operation="face_objects",
identifiers=["Face_3"],
options={"sub_faces": True}
)query, use data and missing.remove, use message for quick confirmation and results for per-face detail.auto_save when shared-memory writeback happens after deletion.sub_faces=True removes both apertures and doors from selected faces.~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.