Agent skill · operations · sickn33
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.
Why this skill is useful
Adds a powerful memory management system that allows agents to handle long conversations and external context efficiently with advanced summarization and compression techniques.
What it needs
Requires npx installed locally. About 2k tokens when loaded. Last updated 2026-08-07. 44,571 stars on the source repository.
What this skill does
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 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. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills sickn33/recallmax