# gilhari_relationships_implicit_attribs_example

> gilhari_relationships_implicit_attribs_example — softwaretree-gilhari-relationships-implicit-attribs-example. Use this tool when you need to manage complex JSON object relationships with implicit attributes for automatic foreign key management. It solves problems related to object referencing and key management in RESTful APIs, providing a seamless interface for contained object interactions. Ideal for use cases involving nested JSON data, this microservice accepts JSON inputs and outputs managed object relationships.

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

## Description

A RESTful Gilhari microservice demonstrating ORM for JSON objects with implicit attributes for automatic foreign key management in contained (referenced) objects

## 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_implicit_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-implicit-attribs-example"
    }
  }
}
```

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