recallmax

name	recallmax
description	FREE — God-tier long-context memory for AI agents. Injects 500K-1M clean tokens, auto-summarizes with tone/intent preservation, compresses 14-turn history into 800 tokens.
category	memory
risk	safe
source	community
date_added	2026-03-13
author	christopherlhammer11-ai
tags	["memory","context","rag","summarization","compression","long-context","agent-infrastructure"]
tools	["claude","cursor","codex","gemini","copilot","windsurf","antigravity","grok"]

RecallMax — God-Tier Long-Context Memory

Overview

RecallMax enhances AI agent memory capabilities dramatically. Inject 500K to 1M clean tokens of external context without hallucination drift. Auto-summarize conversations while preserving tone, sarcasm, and intent. Compress multi-turn histories into high-density token sequences.

Free forever. Built by the Genesis Agent Marketplace.

Install

npx skills add christopherlhammer11-ai/recallmax

When to Use This Skill

• Use when your agent loses context in long conversations (50+ turns)
• Use when injecting large RAG/external documents into agent context
• Use when you need to compress conversation history without losing meaning
• Use when fact-checking claims across a long thread
• Use for any agent that needs to remember everything

How It Works

Step 1: Context Injection

RecallMax cleanly injects external context (documents, RAG results, prior conversations) into the agent's working memory. Unlike naive concatenation, it:

• Deduplicates overlapping content
• Preserves source attribution
• Prevents hallucination drift from context pollution

Step 2: Adaptive Summarization

As conversations grow, RecallMax automatically summarizes older turns while preserving:

• Tone — sarcasm, formality, urgency
• Intent — what the user actually wants vs. what they said
• Key facts — numbers, names, decisions, commitments
• Emotional register — frustration, excitement, confusion

Step 3: History Compression

Compress a 14-turn conversation history into ~800 high-density tokens that retain full semantic meaning. The compressed output can be re-expanded if needed.

Step 4: Fact Verification

Built-in cross-reference checks for controversial or ambiguous claims within the conversation context. Flags contradictions and unsupported assertions.

Best Practices

• ✅ Use RecallMax at the start of long-running agent sessions
• ✅ Enable auto-summarization for conversations beyond 20 turns
• ✅ Use compression before hitting context window limits
• ✅ Let the fact verifier run on high-stakes outputs
• ❌ Don't inject unvetted external content without dedup
• ❌ Don't skip summarization and rely on raw truncation

Related Skills

• @tool-use-guardian - Tool-call reliability wrapper (also free from Genesis Marketplace)

Links

• Repo: https://github.com/christopherlhammer11-ai/recallmax
• Marketplace: https://genesis-node-api.vercel.app
• Browse skills: https://genesis-marketplace.vercel.app

Limitations

• Use this skill only when the task clearly matches the scope described above.
• Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
• Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.