/rlm

name: rlm
description: "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"
license: MIT
metadata:
  author: ClawFu
  version: 2.1.0
  mcp-server: "@clawfu/mcp-skills"

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

1. **NEVER** read more than 3-5 files into your main context 2. **ALWAYS** use parallel agents when file count > 5 3. **Write Python scripts** for state tracking across 50+ files — let the script scan and summarize 4. 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**: 1. `grep -l "@Controller" src/**/*.ts` → 20 files 2. Spawn 20 agents, each extracts endpoints + auth status 3. 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.