# gilhari_relationships_inline_attribs_example

> gilhari_relationships_inline_attribs_example — softwaretree-gilhari-relationships-inline-attribs-example. Use this tool when you need to manage complex JSON objects with nested child attributes, as it provides a RESTful microservice for object-relational mapping (ORM) with inline attribute mapping. This tool solves problems related to storing and retrieving hierarchical data, allowing for efficient data retrieval and manipulation. It accepts JSON objects as input and outputs the mapped data, ideal for use cases involving nested data structures in applications using git version control.

Canonical page: https://skillsregistry.net/skills/softwaretree-gilhari-relationships-inline-attribs-example  
JSON: https://api.skillsregistry.net/v1/skills/softwaretree-gilhari-relationships-inline-attribs-example

## Description

A RESTful Gilhari microservice demonstrating ORM for JSON objects with INLINE mapping for storing child object attributes in parent's table row

## Trust

- **Trust score (0–1):** 1.00
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/SoftwareTree/gilhari_relationships_inline_attribs_example)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "softwaretree-gilhari-relationships-inline-attribs-example"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/softwaretree-gilhari-relationships-inline-attribs-example` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/softwaretree-gilhari-relationships-inline-attribs-example/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt