# rlm-claude

> rlm-claude — encreor-rlm-claude. Use this tool when you need to leverage infinite memory for recursive language modeling tasks, such as enhancing code completion and generation capabilities. It solves problems related to limited memory in traditional language models, enabling more accurate and efficient coding assistance. This tool takes in code inputs and outputs optimized code suggestions, ideal for use in coding environments like git.

Canonical page: https://skillsregistry.net/skills/encreor-rlm-claude  
JSON: https://api.skillsregistry.net/v1/skills/encreor-rlm-claude

## Description

Recursive Language Models for Claude Code - Infinite memory solution inspired by MIT CSAIL paper

## Trust

- **Trust score (0–1):** 0.96
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

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

## Source

- **Source listing:** [GitHub](https://github.com/EncrEor/rlm-claude)

## 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": "encreor-rlm-claude"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/encreor-rlm-claude` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/encreor-rlm-claude/pull`

---
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