检查矢量几何有效性、拓扑错误、属性完整性与 CRS 一致性，输出分级质量报告。Validate geometry validity, topology, attribute completeness and CRS consistency for vector data and emit a graded quality report.
1 installs
Memory
Geoskill: Geospatial Data Quality Audit
Try itUnified geospatial data quality audit for GIS data packages. Checks raster, vector, table, NetCDF, and directory structure. Outputs JSON/HTML reports, issue layers, checksums, and machine-readable exit codes. Use when the user wants to validate data packages, check delivery quality, find CRS/nodata/ geometry issues, or generate QA reports.
What it does
Unified geospatial data quality audit for GIS data packages. Checks raster, vector, table, NetCDF, and directory structure. Outputs JSON/HTML reports, issue layers, checksums, and machine-readable exit codes. Use when the user wants to validate data packages, check delivery quality, find CRS/nodata/ geometry issues, or generate QA reports.
The skill document
Prerequisites / 先准备 X 文件
⚠️ 必读 — 本 skill 不属于即用型，需要先准备特定文件才能跑。
本 skill 不下载数据，只审计你给的 本地数据目录。
👉 完整教程见仓库根目录 PREREQUISITES.md 2.3 节。
先准备 X 文件：随便指一个 GIS 数据目录就能跑。
快速试跑命令：
python geospatial_data_quality_audit.py /path/to/your/data --html --issues-geojson
Geospatial Data Quality Audit
⚠️ 本 skill 不下载数据。它只审计本地
input_dir下的文件。--bbox/--aoi-file接口仅为上下文记录 (写到output-manifest.json)，不会触发任何下载。
Unified QA tool for GIS data packages. Recursively discovers geospatial files, runs per-file and cross-file checks, and produces structured reports.
Trigger
Use when the user wants to:
- Check/validate a directory of spatial data
- Find CRS, nodata, geometry, encoding issues
- Generate QA reports (JSON/HTML) for data delivery
- Verify cross-file consistency (CRS, extent, resolution)
- Produce checksums or issue layers
Boundaries
- Read-only by default (
--fix-safenot implemented in this version) - Does not modify source data
- Does not download external data
- Compliance/certification conclusions require human review
CLI Usage
# Basic audit
python scripts/geospatial_data_quality_audit.py /path/to/data
# With HTML report and issues GeoJSON
python scripts/geospatial_data_quality_audit.py /path/to/data --html --issues-geojson
# Custom rules
python scripts/geospatial_data_quality_audit.py /path/to/data --rules rules.json
# Fail on warnings too
python scripts/geospatial_data_quality_audit.py /path/to/data --fail-on warning
# Non-recursive with checksums
python scripts/geospatial_data_quality_audit.py /path/to/data --no-recursive --checksums
Arguments
| Argument | Description |
|---|---|
input_dir | Directory to audit (required) |
--output-dir, -o | Output directory (default: /qa-output) |
--rules | Custom rules JSON file |
--no-recursive | Don't recurse into subdirectories |
--html | Generate HTML report |
--issues-geojson | Generate spatial issues GeoJSON |
--checksums | Generate MD5 checksums file |
--fail-on | Fail on error (default) or warning |
--sample-size | Max files to check (0=all) |
Output
| File | Description |
|---|---|
qa-report.json | Full JSON report with all findings |
qa-report.html | Human-readable HTML report (with --html) |
qa.json | Summary: score, error/warning counts |
spatial_issues.geojson | Point layer of spatial issues (with --issues-geojson) |
checksums.txt | MD5 checksums (with --checksums) |
output-manifest.json | Machine-readable manifest |
Exit Codes
| Code | Meaning |
|---|---|
| 0 | All checks pass (or only warnings) |
| 2 | Argument error |
| 3 | Dependency missing |
| 6 | Data validation failure (errors found) |
| 7 | Processing failure |
QA Score
score = max(0, 100 - errors * 10 - warnings * 2)
Supported Formats
- Raster: GeoTIFF, IMG, ASC, GRD
- Vector: Shapefile, GeoJSON, KML, GML, GPKG, GPX
- Table: CSV, TSV, Parquet, Excel
- NetCDF: NC, NC4, HDF, HDF5
- LAS: LAS, LAZ (basic checks)
- Document: DOCX, PDF, MD (basic checks)
Rule Engine
Built-in rules cover file readability, CRS presence, nodata, geometry validity, encoding, companion files, and cross-file consistency. Custom rules via JSON config extend with size limits, required CRS, and forbidden extensions.
See references/rules.md for full rule catalog.
Workflow
- Recursively discover geospatial files (skip hidden/cache dirs)
- Detect file type from extension + content sniff
- Run per-file checks (type-specific)
- Run cross-file consistency checks
- Apply rule engine (built-in + custom)
- Generate reports and exit with appropriate code
Dependencies
- Pure Python stdlib for basic checks
rasterio(optional) for deep raster checksfiona(optional) for deep vector checksnetCDF4(optional) for deep NetCDF checks- Missing optional deps produce warnings, not errors
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