geo-infer-norms
Normative inference and compliance tracking for geospatial governance. Use when evaluating spatial policy compliance, tracking governance metrics, computing normative content influence (Jaccard similarity), or managing multi-criteria regulatory frameworks.
Best use case
geo-infer-norms is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Normative inference and compliance tracking for geospatial governance. Use when evaluating spatial policy compliance, tracking governance metrics, computing normative content influence (Jaccard similarity), or managing multi-criteria regulatory frameworks.
Teams using geo-infer-norms should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/GEO-INFER-NORMS/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How geo-infer-norms Compares
| Feature / Agent | geo-infer-norms | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Normative inference and compliance tracking for geospatial governance. Use when evaluating spatial policy compliance, tracking governance metrics, computing normative content influence (Jaccard similarity), or managing multi-criteria regulatory frameworks.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# GEO-INFER-NORMS
## Instructions
### Core Capabilities
- **Compliance tracking**: Threshold, range, and boolean evaluation with weighted scoring
- **Normative inference**: Content influence measurement via Jaccard similarity
- **Policy evaluation**: Multi-criteria governance assessment with configurable metrics
- **Regulatory frameworks**: Spatial regulation management, jurisdiction tracking
### Key Imports
```python
from geo_infer_norms.core.compliance_tracking import compliance_tracking
from geo_infer_norms.core.normative_inference import NormativeInference
from geo_infer_norms.models.metrics import Metric, ComplianceResult
```
## Examples
```python
from geo_infer_norms.core.compliance_tracking import compliance_tracking
from geo_infer_norms.models.metrics import Metric
metrics = [
Metric(name="air_quality", value=42, threshold=50, type="threshold"),
Metric(name="noise_level", value=65, range=(0, 70), type="range"),
Metric(name="green_space", value=True, type="boolean"),
]
result = compliance_tracking(metrics)
print(f"Overall compliance: {result.score:.1%}")
```
## Guidelines
- Content influence uses Jaccard similarity (real implementation)
- Compliance evaluation handles threshold/range/boolean types correctly
### Integrations
- Integrates with METAGOV for governance compliance monitoring
- Integrates with REQ for requirements compliance tracking
- Test: `uv run python -m pytest GEO-INFER-NORMS/tests/ -v`