geo-infer-ops
Operations, monitoring, and observability for geospatial infrastructure. Use when setting up monitoring dashboards, configuring alerts, tracking system health, or managing deployment of spatial services.
Best use case
geo-infer-ops is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Operations, monitoring, and observability for geospatial infrastructure. Use when setting up monitoring dashboards, configuring alerts, tracking system health, or managing deployment of spatial services.
Teams using geo-infer-ops 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-OPS/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How geo-infer-ops Compares
| Feature / Agent | geo-infer-ops | 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?
Operations, monitoring, and observability for geospatial infrastructure. Use when setting up monitoring dashboards, configuring alerts, tracking system health, or managing deployment of spatial services.
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-OPS
## Instructions
### Core Capabilities
- **Monitoring**: System health metrics, spatial operation performance
- **Alerting**: Threshold-based and anomaly-based alerts
- **Log aggregation**: Structured log collection and querying
- **Deployment**: Configuration management for spatial services
- **Observability**: Distributed tracing for cross-module operations
### Key Imports
```python
from geo_infer_ops.core.monitoring import MonitoringEngine
from geo_infer_ops.core.alerting import AlertManager
from geo_infer_ops.core.deployment import DeploymentManager
```
## Examples
```python
from geo_infer_ops.core.monitoring import MonitoringEngine
monitor = MonitoringEngine()
monitor.register_metric("h3_index_latency_ms", type="histogram")
monitor.register_metric("active_queries", type="gauge")
# Record spatial operation metrics
with monitor.timer("h3_index_latency_ms"):
cells = backend.tessellate(region, resolution=7)
monitor.gauge("active_queries", value=42)
dashboard_url = monitor.export_prometheus(port=9090)
```
```python
from geo_infer_ops.core.alerting import AlertManager
alerts = AlertManager()
alerts.add_rule(
name="high_latency",
metric="h3_index_latency_ms",
condition="p99 > 500",
action="notify_slack"
)
alerts.start_watching()
```
## Guidelines
- Uses structured logging (JSON format)
- Prometheus-compatible metrics export
- Test: `uv run python -m pytest GEO-INFER-OPS/tests/ -v`
### Integrations
- **API** → Endpoint monitoring and rate limiting
- **AGENT** → Agent telemetry collection and dashboards
- **IOT** → Sensor health monitoring and alerts
- **LOG** → Logistics operation monitoring
- **SEC** → Security event aggregation