A Claude Code integration for processing documents that are too large to fit in one model conversation. It splits documents into parts and uses repeated model calls to work through them.

Use it when analysing or processing documents whose size exceeds the agent’s normal conversation limit.

It lets the coding agent handle very large documents without requiring the whole document to fit in its context window.

rlm-rs — Plugin for Claude Code by zircote-plugins/rlm-rs-plugin

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Clone the repo

git clone --depth 1 https://github.com/zircote-plugins/rlm-rs-plugin

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/plugins/zircote-plugins/rlm-rs-plugin/rlm-rs-plugin/github.svg)](https://agentmods.dev/plugins/zircote-plugins/rlm-rs-plugin/rlm-rs-plugin)

Your own site

<a href="https://agentmods.dev/plugins/zircote-plugins/rlm-rs-plugin/rlm-rs-plugin"><img src="https://agentmods.dev/badge/plugins/zircote-plugins/rlm-rs-plugin/rlm-rs-plugin/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/plugins/zircote-plugins/rlm-rs-plugin/rlm-rs-plugin"><img src="https://agentmods.dev/badge/plugins/zircote-plugins/rlm-rs-plugin/rlm-rs-plugin.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session not measured What this adds to a session before it is invoked.

When invoked not measured The manifest loads nothing itself; its 2 skills, 4 commands, 2 agents cost 279 tokens a session between them.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin unknown No closer match found in the catalogue.

Security

Grade A, and why

rlm-rs scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.claude-plugin/plugin.json · 18 lines

The source is not reproduced here

No licence file

Read it on GitHub

Contents

What it installs

The manifest is a name and a version. 2 skills, 4 commands, 2 agents travel with it, and installing the plugin installs all of them — 279 tokens a session between them. Each is measured on its own page, and each can be installed alone.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

1mo ago First seen · 18 lines scan A cf8bd230f018

Subscribe to this mod's changes

rlm-rs is a plugin published in the GitHub repository zircote-plugins/rlm-rs-plugin (4 stars, last pushed 5d ago), with no licence file. Its token cost is not measured: this kind of file is read by the harness, not the model. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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llm-wiki

LLM-maintained personal wiki. Claude actively ingests, synthesizes, and cross-links knowledge across all your projects. Based on Karpathy's LLM Wiki pattern.

deepfounder-ai/llm-wiki · not measured

tencentdb-agent-memory

Four-layer long-term memory (L0→L1→L2→L3 Persona) with hybrid FTS5+vector recall + L2 scene-navigation. CLI: tmem (status, search, projects, migrate-fragments, recall, scene, scenes, changelog, persona, sync, config, daemon, atoms, sessions, write-l1, write-scene, write-persona, mark-done, init). Run /memory-init…

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