lets7512/rlm-skill

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23 stars 품질 59 트렌드 10MIT

개요

A plugin for and implementing the pattern from MIT's paper (arXiv:2512.24601). Instead of stuffing massive data into the context window, treat it as an external variable in a REPL and write code to programmatically examine, decompose, and search it. Only results enter context. The (plugins/rlm-interceptor.ts) automatically rewrites large file reads into metadata summaries and provides custom tools for sandbox execution and knowledge base search. In OpenCode, use Ctrl+K then select: - project:rlm — invoke RLM for large-context tasks - project:rlm-stats — show token savings dashboard - @rlm — invoke the RLM agent directly The skill activates automatically when large-context tasks are detected. The interceptor silently rewrites tool calls to prevent raw data from entering context. The plugin provides MCP tools (Claude Code) and custom tools (OpenCode): Search results use — instead of returning full chunks, the search highlights windows around matching query terms with ...

README

원문 README의 일부입니다. 원문 보기.

RLM Skill

A plugin for Claude Code and OpenCode implementing the Recursive Language Model (RLM) pattern from MIT’s paper (arXiv:2512.24601). Instead of stuffing massive data into the context window, treat it as an external variable in a REPL and write code to programmatically examine, decompose, and search it. Only results enter context.

Install

Claude Code

/plugin marketplace add lets7512/rlm-skill
/plugin install rlm@rlm-skill

Restart Claude Code. Done.

Or load for a single session:

claude --plugin-dir /path/to/rlm-skill

OpenCode

# Copy agents, commands, and plugins to your project or user config
cp -r .opencode/agents/ .opencode/commands/ .opencode/plugins/ ~/.config/opencode/

# Or use from project root (auto-detected from .opencode/)
# Install plugin dependencies
cd .opencode && npm install

The RLM interceptor plugin (plugins/rlm-interceptor.ts) automatically rewrites large file reads into metadata summaries and provides custom tools for sandbox execution and knowledge base search.

In OpenCode, use Ctrl+K then select:

project:rlm — invoke RLM for large-context tasks
project:rlm-stats — show token savings dashboard
@rlm — invoke the RLM agent directly

RLM CLI (optional, for massive datasets)

uv pip install -e .

Usage

The skill activates automatically when large-context tasks are detected. The interceptor silently rewrites tool calls to prevent raw data from entering context.

Invoke directly in Claude Code:

/rlm:rlm analyze this 500MB log file for error patterns

Invoke in OpenCode:

@rlm analyze this 500MB log file for error patterns

Check token savings:

/rlm:stats

Custom Tools

The plugin provides MCP tools (Claude Code) and custom tools (OpenCode):

Tool	Purpose
`rlm_execute`	Run code in a sandboxed subprocess (python/js/shell). Only stdout enters context.
`rlm_execute_file`	Run code against a file. Content loaded as `FILE_CONTENT` variable, never enters context.
`rlm_index`	Index file content into an FTS5 knowledge base for later search.
`rlm_search`	Search indexed content with smart snippets + BM25 ranking + 3-layer fallback (porter/trigram/fuzzy).
`rlm_batch_execute`	Run multiple commands + search queries in ONE call. Saves tool-call overhead.
`rlm_fetch_and_index`	Fetch URL, convert HTML to text, chunk and index. Raw page never enters context.
`rlm_stats`	Show knowledge base statistics (indexed sources, chunk count, DB size).

Smart Snippets

Search results use smart snippet extraction — instead of returning full chunks, the search highlights windows around matching query terms with ... context bridges. This minimizes tokens while preserving relevance.

3-Layer Search Fallback

Porter stemming (FTS5 default) — handles word variants (running matches run)

GitHub에서 전체 README 보기

설치

npx skillfish add lets7512/rlm-skill

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