raster-at-scale — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited raster-at-scale (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.
A large raster will not fit in memory, and the naive read everything into a NumPy array is how raster jobs crash. Process big rasters the way they're built to be processed.
rasterio windowed reads, GDAL block reads). Process tile by tile and write tile by tile.gdaladdo) so display and downsampled analysis don't touch full resolution.xarray/dask or rioxarray rather than a monolithic array.-multi -wo NUM_THREADS=ALL_CPUS), not by reading arrays into Python.crs-discipline).The failure modes at scale are distinct: out-of-memory crashes, hour-long full-resolution passes that should have used overviews, and silently wrong resampling that corrupts categorical data. Windowed reads, COGs/overviews, and method-appropriate resampling turn an unworkable raster job into a fast, correct one.
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.