Acontext

What is Acontext?

Agent Skills as a Memory Layer — learns from runs, writes Markdown skill files, reuses them on the next run

Acontext is an open-source Agent Skills as a Memory Layer: skill memory that automatically captures learnings from agent runs and stores knowledge as Markdown files. You can read, edit, and share those files across agents, LLMs and frameworks.

Acontext — Session Storage, Task Tracking, Skill Memory

Why Skill Memory?

Other memory (e.g. Mem0, Zep, vector stores, RAG) stores or retrieves from conversations or static docs. If you need a layer that learns from what the agent did (task outcomes) and turns that into reusable SOPs and warnings, that's Agent Skills as a memory layer.

Skill memory (Agent Skills layer)Other memory (e.g. Mem0 / Zep)Vector store / RAG
CapturesWhat the agent did + outcome → procedures, preferences, warningsWhat was said → facts, preferencesWhat you ingested → chunks
Stored asMarkdown files (human-readable, portable)Embeddings / graphEmbeddings
RetrievalAgent calls tools, gets full units (e.g. whole files)Semantic or chat recallSimilarity search over chunks

In short: Other memory stores and retrieves chat or ingested docs as-is. Acontext also takes session messages (and execution) as input, but distills from them what the agent did and how it turned out — then writes that as structured skill files that grow with every run.

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