survey-data-processor

Survey data processing skill for point clouds, DTM generation, and coordinate transformation

509 stars

Best use case

survey-data-processor is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Survey data processing skill for point clouds, DTM generation, and coordinate transformation

Teams using survey-data-processor 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

$curl -o ~/.claude/skills/survey-data-processor/SKILL.md --create-dirs "https://raw.githubusercontent.com/a5c-ai/babysitter/main/library/specializations/domains/science/civil-engineering/skills/survey-data-processor/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/survey-data-processor/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How survey-data-processor Compares

Feature / Agentsurvey-data-processorStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Survey data processing skill for point clouds, DTM generation, and coordinate transformation

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

# Survey Data Processor Skill

## Purpose

The Survey Data Processor Skill processes survey data including point cloud processing, DTM/TIN generation, coordinate transformation, and traverse adjustment.

## Capabilities

- Point cloud processing
- DTM/TIN generation
- Coordinate transformation
- Traverse adjustment
- Level loop adjustment
- GNSS data processing
- Contour generation
- Feature extraction

## Usage Guidelines

### When to Use
- Processing survey data
- Creating terrain models
- Transforming coordinates
- Adjusting measurements

### Prerequisites
- Survey data collected
- Control points established
- Coordinate system defined
- Quality requirements known

### Best Practices
- Check data quality
- Verify transformations
- Document adjustments
- Archive raw data

## Process Integration

This skill integrates with:
- Geotechnical Site Investigation
- Highway Geometric Design

## Configuration

```yaml
survey-data-processor:
  data-types:
    - point-cloud
    - total-station
    - GNSS
    - level
  processing:
    - DTM-generation
    - adjustment
    - transformation
    - feature-extraction
```

## Output Artifacts

- DTM surfaces
- Adjusted coordinates
- Transformation reports
- Survey maps

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