# hippomem

> hippomem — z10-labs-hippomem. Use this tool when you need to leverage collective knowledge and avoid redundant coding efforts by accessing a shared decision memory. Hippomem solves problems of duplicated work and inconsistent implementations by providing AI coding agents with insight into previous team decisions and their rationale. It takes in queries from agents and outputs relevant decision history and context, integrating with git for seamless collaboration.

Canonical page: https://skillsregistry.net/skills/z10-labs-hippomem  
JSON: https://api.skillsregistry.net/v1/skills/z10-labs-hippomem

## Description

A team's engineering memory for AI coding agents: the decisions behind the software, and the options rejected.

## 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:** 2026-11-06

## Source

- **Source listing:** [GitHub](https://github.com/z10-labs/hippomem)

## 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": "z10-labs-hippomem"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/z10-labs-hippomem` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/z10-labs-hippomem/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