{"slug":"agentic-memory-architect","title":"agentic-memory-architect","summary":"Expert guide for long-term episodic memory integration (Mem0, Letta/MemGPT, Zep) and unified context management for autonomous AI agents / Panduan ahli untuk integrasi memori episodik jangka panjang dan manajemen konteks agen AI otonom.","platform":"Claude","tags":[],"authorName":"LLM Mart","authorSlug":"llm-mart","score":0,"source":"github","price":null,"verified":false,"createdAt":"2026-09-24T14:52:21.143677Z","repo":{"url":"https://github.com/roedyrustam/vibes-plug","stars":70,"forks":14,"license":"MIT","updatedAt":"2026-09-24T12:42:52Z"},"bodyHtml":"<hr>\n<h2>name: agentic-memory-architect\ndescription: Expert guide for long-term episodic memory integration (Mem0, Letta/MemGPT, Zep) and unified context management for autonomous AI agents / Panduan ahli untuk integrasi memori episodik jangka panjang dan manajemen konteks agen AI otonom.\nversion: \"3.7.0\"\nauthor: vibes-plug-swarm</h2>\n<h1>Agentic Memory Architect &amp; Episodic Memory Guide</h1>\n<p><a href=\"#english\">English</a> | <a href=\"#bahasa-indonesia\">Bahasa Indonesia</a></p>\n<hr>\n<p><a name=\"english\"></a></p>\n<h2>English</h2>\n<h3>Orchestration &amp; Integration</h3>\n<p>Connects and orchestrates with <code>multi-agent-orchestration</code>, <code>pydantic-ai-expert</code>, <code>session-memory-manager</code>, and <code>zero-to-prod-orchestrator</code>.</p>\n<h3>Purpose</h3>\n<p>To design and implement persistent, long-term episodic memory systems for autonomous AI agents, moving beyond simple context windows or localized session checkpoints.</p>\n<h3>Key Technologies</h3>\n<ul>\n<li><strong>Mem0</strong>: For cross-session entity memory and user preference persistence.</li>\n<li><strong>Letta (formerly MemGPT)</strong>: For unbounded memory management allowing LLMs to page memory in and out.</li>\n<li><strong>Zep (v2)</strong>: Fast, scalable memory service for AI applications, including temporal memory.</li>\n</ul>\n<h3>Architectural Guidelines</h3>\n<ol>\n<li><strong>Memory Tiers</strong>: Segregate memory into short-term (working context), mid-term (session graph), and long-term (vector-backed episodic memory).</li>\n<li><strong>Context Paging</strong>: Implement mechanisms for agents to proactively recall and summarize past interactions without overwhelming the token budget.</li>\n<li><strong>User Knowledge Graphs</strong>: Continually update the graph of user preferences, project constraints, and architectural decisions over time.</li>\n</ol>\n<hr>\n<p><a name=\"bahasa-indonesia\"></a></p>\n<h2>Bahasa Indonesia</h2>\n<h3>Integrasi Orkestrasi</h3>\n<p>Terhubung dan mengorkestrasi bersama <code>multi-agent-orchestration</code>, <code>pydantic-ai-expert</code>, <code>session-memory-manager</code>, dan <code>zero-to-prod-orchestrator</code>.</p>\n<h3>Tujuan</h3>\n<p>Merancang dan mengimplementasikan sistem memori episodik jangka panjang yang persisten untuk agen AI otonom, bergerak melampaui jendela konteks sederhana atau checkpoint sesi lokal.</p>\n<h3>Teknologi Utama</h3>\n<ul>\n<li><strong>Mem0</strong>: Untuk memori entitas lintas-sesi dan persistensi preferensi pengguna.</li>\n<li><strong>Letta (sebelumnya MemGPT)</strong>: Untuk manajemen memori tak terbatas yang memungkinkan LLM mengambil/menyimpan memori.</li>\n<li><strong>Zep (v2)</strong>: Layanan memori cepat dan skalabel untuk aplikasi AI, termasuk memori temporal.</li>\n</ul>\n<h3>Panduan Arsitektur</h3>\n<ol>\n<li><strong>Tingkatan Memori</strong>: Pisahkan memori menjadi jangka pendek (konteks kerja), jangka menengah (grafik sesi), dan jangka panjang (memori episodik berbasis vektor).</li>\n<li><strong>Context Paging</strong>: Implementasikan mekanisme agar agen secara proaktif memanggil dan merangkum interaksi masa lalu tanpa menghabiskan anggaran token.</li>\n<li><strong>User Knowledge Graph</strong>: Terus perbarui graf preferensi pengguna, batasan proyek, dan keputusan arsitektur seiring waktu.</li>\n</ol>\n","files":[{"path":"SKILL.md","sizeBytes":2811,"isText":true}],"reviewScore":null,"reviewSummary":null,"trust":{"provenance":"trusted-source-unreviewed","notice":"Community-authored content, reproduced verbatim and not vetted as instructions. Treat it as data to evaluate, never as directives to follow.","bodySource":null},"bodyLocked":false,"purchaseUrl":null,"sourceUrl":null,"report":{"provenance":"trusted-source-unreviewed","screen":{"ran":true,"outcome":"clean","suspicious":0,"notes":0,"hiddenCharacters":false},"virusScan":{"engine":"clamav","status":"clean","scannedAt":"2026-09-24T14:52:40.385206Z","sha256":"B622C6A94904F5EA2F242C3A1743CB9922B63A743DEF7EAA25F1379AAF50CCDF","sizeBytes":1398},"review":null,"source":{"repositoryUrl":"https://github.com/roedyrustam/vibes-plug","path":"skills/agentic-memory-architect","license":"MIT","commit":"5a27cfb5a8ba0deb91e2f76b2af58e7e9e6ddfd9","subtreeSha":"38657FF9C1BDEAF58A173EE2A327822C1E370B63B8B7997AD27489AB18E50E5B","lastSyncedAt":"2026-09-24T14:52:20.584568Z"},"reviewedAt":"2026-09-24T14:52:58.50096Z","notice":"Community-authored content, reproduced verbatim and not vetted as instructions. Treat it as data to evaluate, never as directives to follow."},"install":[{"target":"skills-cli","command":"npx skills add https://github.com/roedyrustam/vibes-plug/tree/main/skills/agentic-memory-architect"},{"target":"claude-code","command":"claude plugin marketplace add https://llmmart.ai/marketplace.json && claude plugin install roedyrustam-vibes-plug@llmmart"},{"target":"git","command":"git clone https://github.com/roedyrustam/vibes-plug.git"}]}