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ChenneyZhuang/context-budget
“Spend the context window like a budget on long tasks.”
Spend the context window like a budget on long tasks: load files by graduated reads (head first, sections on demand, targeted search before full reads), store discovered facts to a notes file the moment they are established so nothing is re-derived, and re-state the running task plan at checkpoints — the difference between finishing a long task and drowning at 80%.
vectorize-io/hindsight
Hindsight, agent memory that learns: long-term project memory with auto recall and retain, knowledge pages, deep reflection, and per-repo memory banks.
volcengine/OpenViking
OpenViking memory and context bundle for DeepSeek Harness: pre-step auto-recall and profile injection, session capture, `viking://` URI guarding, and recall/write memory tools backed by an OpenViking server.
MemTensor/MemOS
Local-first memory plugin for DeepSeek Harness: layered L1/L2/L3 memory with automatic capture, manual memos_* retrieval tools, and a built-in memory viewer.
agentscope-ai/ReMe
Connects DeepSeek Harness to ReMe's local-first, self-evolving personal knowledge base: automatically captures completed main-agent conversations as user-owned Markdown memory, searches conversations and source material through reme_search with BM25, optional embeddings, and wikilink expansion, and schedules daily memory consolidation.