lets7512/rlm-skill
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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...
概要
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
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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 tasksproject: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 (
runningmatchesrun)
推奨ツール
別のキーワードを試すか、フィルタを外してください。
インストール
npx skillfish add lets7512/rlm-skill