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AGENT SKILL

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.

License 许可
Apache-2.0
最近更新
2026-06-23
Stars
★ 6
Forks
0

01 前言 Front Matter

name
recallmax
risk
safe
tags
[ "memory", "context", "rag", "summarization", "compression", "long-context", "agent-infrastructure" ]
tools
[ "claude", "cursor", "codex", "gemini", "copilot", "windsurf", "antigravity", "grok" ]
author
christopherlhammer11-ai
source
community
category
memory
date_added
2026-03-13
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.

02 资源文件 317

03 SKILL.md 正文

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

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