83 lines
3.3 KiB
Markdown
83 lines
3.3 KiB
Markdown
---
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name: recallmax
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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."
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category: memory
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risk: safe
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source: community
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date_added: "2026-03-13"
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author: christopherlhammer11-ai
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tags: [memory, context, rag, summarization, compression, long-context, agent-infrastructure]
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tools: [claude, cursor, codex, gemini, copilot, windsurf, antigravity, grok]
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---
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# RecallMax — God-Tier Long-Context Memory
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## Overview
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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.
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Free forever. Built by the Genesis Agent Marketplace.
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## Install
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```bash
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npx skills add christopherlhammer11-ai/recallmax
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```
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## When to Use This Skill
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- Use when your agent loses context in long conversations (50+ turns)
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- Use when injecting large RAG/external documents into agent context
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- Use when you need to compress conversation history without losing meaning
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- Use when fact-checking claims across a long thread
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- Use for any agent that needs to remember everything
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## How It Works
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### Step 1: Context Injection
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RecallMax cleanly injects external context (documents, RAG results, prior conversations) into the agent's working memory. Unlike naive concatenation, it:
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- Deduplicates overlapping content
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- Preserves source attribution
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- Prevents hallucination drift from context pollution
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### Step 2: Adaptive Summarization
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As conversations grow, RecallMax automatically summarizes older turns while preserving:
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- **Tone** — sarcasm, formality, urgency
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- **Intent** — what the user actually wants vs. what they said
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- **Key facts** — numbers, names, decisions, commitments
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- **Emotional register** — frustration, excitement, confusion
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### Step 3: History Compression
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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.
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### Step 4: Fact Verification
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Built-in cross-reference checks for controversial or ambiguous claims within the conversation context. Flags contradictions and unsupported assertions.
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## Best Practices
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- ✅ Use RecallMax at the start of long-running agent sessions
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- ✅ Enable auto-summarization for conversations beyond 20 turns
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- ✅ Use compression before hitting context window limits
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- ✅ Let the fact verifier run on high-stakes outputs
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- ❌ Don't inject unvetted external content without dedup
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- ❌ Don't skip summarization and rely on raw truncation
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## Related Skills
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- `@tool-use-guardian` - Tool-call reliability wrapper (also free from Genesis Marketplace)
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## Links
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- **Repo:** https://github.com/christopherlhammer11-ai/recallmax
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- **Marketplace:** https://genesis-node-api.vercel.app
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- **Browse skills:** https://genesis-marketplace.vercel.app
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## Limitations
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- Use this skill only when the task clearly matches the scope described above.
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- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
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- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.
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