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 complex memory management system that allows AI agents to handle long-context conversations and external documents effectively, which is not commonly available in standard AI capabilities.
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--2e109b