XiaoConstantine contributor

Rlm

Register the rlm marketplace plugin to process very large contexts recursively and save tokens in Claude Code.

Overview

rlm is a plugin marketplace for the Build phase that adds a Recursive Language Model skill for large-context, token-efficient processing in Claude Code.

What is this marketplace?

  • Recursive Language Model (RLM) skill packaged as Claude marketplace plugin v0.1.0
  • Targets large context processing with token efficiency
  • Official marketplace schema from anthropic.com/claude-code
  • Single-plugin rlm bundle from XiaoConstantine
  • Skill source at ./plugins/rlm with ./skills/rlm entry
  • Marketplace lists 1 plugin: rlm at version 0.1.0
  • Plugin includes skills path ./skills/rlm from ./plugins/rlm

Compatible agents: Claude Code

Community signal: 15 GitHub stars.

What problem does it solve?

Massive documents and repos overflow normal context windows and waste tokens on naive single-shot prompts.

Who is it for?

Builders juggling huge codebases, logs, or research corpora who need an RLM skill inside Claude Code.

Skip if: Simple tasks with small prompts where a vanilla agent session needs no recursive context machinery.

What do I get? / Deliverables

After you add the rlm plugin, Claude Code can apply recursive language modeling to break down and handle oversized inputs more efficiently.

  • rlm v0.1.0 plugin with bundled RLM skill
  • Recursive decomposition workflow for oversized inputs

Plugins in this marketplace

1 plugin — install individually after you add the marketplace.

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Journey fit

Large-context LLM patterns are adopted when wiring agent integrations during product build, even when used later for research. The rlm plugin bundles an ./skills/rlm skill for Recursive Language Model processing—a core LLM integration pattern.

How it compares

LLM large-context skill plugin, not a DevOps pipeline or voice/TTS marketplace.

Common Questions / FAQ

Who is Rlm for?

Developers using Claude Code who hit context limits on big files, repos, or research dumps and want RLM-style handling.

When should I use Rlm?

When integrate-phase agent work routinely involves large context that must be processed with token efficiency.

How do I add Rlm to my agent?

Install the XiaoConstantine Rlm-go Claude marketplace and enable the Rlm plugin that loads ./skills/Rlm.

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