Rlm Agent Skill

Process large codebases (>100 files) using the Recursive Language Model pattern. Orchestrates parallel sub-agents to map-reduce across files without context rot. Use when: analyzing large repositories; auditing security or auth across many files; finding patterns across 50+ files; processing large log files or data dumps

635 tokens

context cost

the whole folder, loaded on every use

files

instructions only

copies elsewhere

how many repositories repackaged it

145

stars on the repo

on the repository, not the skill itself

Install

one command, takes just this skill from the repository

npx skills add https://github.com/guia-matthieu/clawfu-skills --skill rlm

The instruction itself

9 sections, as written by the author

Recursive Language Model (RLM)

"Context is an external resource, not a local variable."

You are the Root Node. Your job is NOT to read code directly, but to orchestrate sub-agents that read code for you.

The RLM Loop

Phase 1: Index & Filter

Identify relevant files without loading them into context.

# Find candidate files
grep -rl "pattern" src/ --include="*.ts"
find . -name "*.py" -newer last_check

Phase 2: Parallel Map

Split work into atomic units, spawn parallel agents.

Launch 3-5+ agents in parallel for broad tasks
Give each agent ONE specific file or chunk
Each agent returns a structured summary

Example spawn:

Agent 1: "Read src/api/routes.ts. List all endpoints with their auth decorators."
Agent 2: "Read src/api/users.ts. List all endpoints with their auth decorators."
...

Phase 3: Reduce & Synthesize

Collect all agent outputs, find patterns, compile into a coherent answer.

If incomplete, recurse: run a second RLM pass on the specific gaps.

Critical Rules

NEVER read more than 3-5 files into your main context
ALWAYS use parallel agents when file count > 5
Write Python scripts for state tracking across 50+ files — let the script scan and summarize
If parallel agents are unavailable, fall back to iterative Python scripting

Example: "Find all API endpoints, check for Auth"

Wrong (monolithic): Read each file sequentially → context fills up, reasoning degrades.

RLM Way:

grep -l "@Controller" src/**/*.ts → 20 files
Spawn 20 agents, each extracts endpoints + auth status
Collect outputs, compile table, identify missing auth

Output Format

Return a structured summary:

Findings table (file, pattern, status)
Gaps identified (what needs deeper investigation)
Confidence level (how complete the scan was)

Skill Boundaries

Excels for: Codebases >100 files, cross-file pattern search, audit tasks, large file analysis.

Not ideal for: Small projects (<50 files), single file analysis, file modification tasks.

Other skills for the same job

different authors, same section of the catalogue

Hook Development

by anthropics

vendor ×2

This skill should be used when the user asks to "create a hook", "add a PreToolUse/PostToolUse/Stop hook", "validate tool use", "implement prompt-based hooks", "use ${CLAUDE_PLUGIN_ROOT}", "set up event-driven automation", "block dangerous commands", or mentions hook events (PreToolUse, PostToolUse, Stop, SubagentStop, SessionStart, SessionEnd, UserPromptSubmit, PreCompact, Notification). Provides comprehensive guidance for creating and implementing Claude Code plugin hooks with focus on advanced prompt-based hooks API.

Build agentic applications with GitHub Copilot SDK. Use when embedding AI agents in apps, creating custom tools, implementing streaming responses, managing sessions, connecting to MCP servers, or creating custom agents. Triggers on Copilot SDK, GitHub SDK, agentic app, embed Copilot, programmable agent, MCP server, custom agent.

Coding Agent Session Search - unified CLI/TUI to index and search local coding agent history from Claude Code, Codex, Gemini, Cursor, Aider, ChatGPT, Pi-Agent, Factory, and more. Purpose-built for AI agent consumption with robot mode.

Destructive Command Guard - High-performance Rust hook for Claude Code that blocks dangerous commands before execution. SIMD-accelerated, modular pack system, whitelist-first architecture. Essential safety layer for agent workflows.

Makepad UI development skills for Rust apps: setup, patterns, shaders, packaging, and troubleshooting.

Secure environment variable management ensuring secrets are never exposed in Claude sessions, terminals, logs, or git commits

Prompt for generating an AGENTS.md file for a repository

2k tokens

How to use it

Copy the folder

Take guia-matthieu/rlm from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.