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Skill · Memory

Recallmax

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.

Agentic Awesome SkillsAdded Sep 5, 2026
Use it in my AI

How to use it

  1. Start your plan and connect your AI once
  2. Add the skill to your AI, one time only: press Copy skill and paste it into your AI's instructions: a project in ChatGPT, Claude or Grok, a Gem in Gemini, an agent in Microsoft 365 Copilot, or a rule in Cursor. It stays there for every new chat. In Kimi, paste it at the start of a new chat.
  3. Ask for the task in your own words, or say it directly:
Use the Recallmax skill to help me with this.
SKILL.md

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.