# synapses

> synapses — divish1032-synapses. Use this tool when you need to enhance AI coding agents with structured graph context and memory, enabling them to better understand codebases and provide more accurate suggestions. It solves problems related to code intelligence, such as navigating complex code structures and identifying relationships between different components. With inputs from git repositories and outputs of actionable code insights, synapses is ideal for use cases where AI-driven coding assistance is required.

Canonical page: https://skillsregistry.net/skills/divish1032-synapses  
JSON: https://api.skillsregistry.net/v1/skills/divish1032-synapses

## Description

A paused, local-first code intelligence project that gives AI coding agents structured graph context, memory, and MCP tools.

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** MIT
- **Updated:** 2026-09-20

## Source

- **Source listing:** [GitHub](https://github.com/Divish1032/synapses)

## 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": "divish1032-synapses"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/divish1032-synapses` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/divish1032-synapses/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