Memory

The memory that dreams — cross-session memory for DeepSeek Harness: recalls you and your projects across sessions, consolidates memories while idle (autoDream), freezes conflicting memories for your review, and keeps a replayable audit trail. Memory stays on your machine as SQLite with human-editable Markdown mirrors; four-way recall (keyword, vector, BM25, entity graph) and an interactive memory panel ship with it, plus 10 model tools, an MCP server, an external API and a CLI. Summarization and consolidation run on the host model you already configured; with a local embedder, semantic search runs fully offline.

Cross-session memory plugin for DeepSeek Harness with autoDream consolidation: SQLite store, Markdown mirrors, 10 model tools, automatic injection, session summarization, user profile/rules, custom slash commands, vector (semantic) search, and a Web GUI p

Long-term memory for DeepSeek Harness kept as plain markdown, one fact per file. Every step the `MEMORY.md` index (the project store if there is one, plus a global store under `$DSH_HOME`) goes into the runtime context, so recall does not wait for a file read. The index has a hard cap, 200 lines / 25 KB by default, enforced by `ctx.tools.guard()`: a write that grows an over-cap index is denied, a rewrite that shrinks it passes. A read-only sidebar Memory page lists the notes by type. The plugin never writes memories on its own. An experimental companion mode adds note types for a persona's own life. The same store also works with Claude Code, Codex, Kiro and OpenClaw.

Proactive associative memory for DSH: zero-prompt recall injected at a fixed boundary, three-layer auto-consolidation, skill crystallization, and Astra-style context management - handoff ledgers and a PLAN whiteboard that survive context-window switches, water-level sensing with an auto-detected model window. Local Markdown storage, model-agnostic, zero deps; lexical 0GB floor with optional semantic tiers.

🌌 Mebular · shared memory and task collaboration for agents. Through a DSH-native plugin, it provides cross-device, cross-agent memory sharing and task-graph capabilities — so physical devices are no longer the boundary of your agents. Secure, controllable, and decentralized! The plugin attaches to an existing Mebular app or CLI runtime; when none exists, the panel installs the shared runtime on demand, and it never starts or downloads Mebular silently.

Other memory plugins help your agent remember more. This one decides what is allowed to count: agents propose, a human approves (three-store gate + immutable audit log), and recall runs on SQLite FTS5/BM25 with zero model calls (measured p50 2.3ms). A token ledger shows what recall actually cost. One vault for DSH, Claude Code, Codex, Cursor, OpenClaw, Hermes, MengBot and any MCP client. v0.31 adds five one-click skins (Default, Pop, Light, Resident Evil, Spider-Man) with full-bleed theme banners and per-skin hover contrast.

Local Git-backed long-term memory for DeepSeek Harness with hybrid CJK/English retrieval, cited context, transactional sync, previews, and rollback.

Model-driven context compression (Active Context Pruning) for DeepSeek Harness: the model decides when and what to compress.

Three-tier memory control plane for DeepSeek Harness: persistent runtime context, searchable project documents, pluggable long-term memory, smart routing, supervised agent workflows, WebUI, and headless tools.

Curated file-based long-term memory for DeepSeek Harness — human-readable markdown notes, one plain-file store shared across hosts (git-ignored when it lives inside a project repo), and a deterministic index cap enforced by ctx.tools.guard()

Bounded, layered, approval-gated, auditable cross-session memory: a typed `ctx.memory` seam with a zero-dependency SQLite provider, a `memory` tool, and frozen snapshot injection, plus the dsh-memory-protocol v1 rehearsal with an adapter registry and a distributable conformance suite.

用多彩的人类世界，训练 DSH 的人格：默认积累信笺反思于专用 human-world.md；允许通过 DSH 与外部插件接驳。历史、收藏、点赞与投币独立默认关闭；本项目不提供评论接口。

Long-term memory for DSH agents — durable, inspectable memories with recall, search, browse and knowledge-graph tools, import from ten other AI coding tools, and a settings page.

边做边压 Live Compact. Compress the finished turn in place and keep the prefix cache.

Claude Code-style auto-memory, natively: typed memory files (user/feedback/project/reference) with a MEMORY.md index auto-injected into the system prompt (zero footprint when empty); memory_write/read/list/delete follow Claude Code write rules (dedupe-and-update, absolute dates, cross-links); workspace-scoped and user-scoped layers, cross-process file locking with orphan-lock recovery, plain Markdown on disk, no external services, no embeddings.

The memory that dreams — cross-session memory for DeepSeek Harness: recalls you across sessions, auto-consolidates in its sleep (autoDream), freezes conflicting memories for your review, and keeps a replayable audit trail. Offline-first local semantic search over SQLite with human-editable Markdown mirrors, an entity graph, an interactive memory panel, plus an external API and CLI.

Recent conversations stay vivid. Older ones fade into summaries, not oblivion. StrataGate gives DeepSeek Harness six-layer, time-decaying memory, while lasting events and relationships settle into a knowledge graph. Bring your memories from other AIs with you—no need to start over.

The memory that dreams — cross-session memory for DeepSeek Harness: recalls you across sessions, auto-consolidates in its sleep (autoDream), freezes conflicting memories for your review, and keeps a replayable audit trail. Offline-first local semantic search over SQLite with human-editable Markdown mirrors, an entity graph, an interactive memory panel, plus an external API and CLI.

Causal memory for dsh: a zero-dependency MCP stdio bridge that mounts the 17 tools of the causal-memory server under clean names (no mcp__ prefix) — decision → outcome edges with typed relations (caused / enabled / prevented) in a local SQLite store that survives compaction — plus a pinned system-prompt section. Requires the causal-memory server binary on PATH (pip install causal-memory, or a prebuilt release).

Knowledge base for DeepSeek Harness: assembles ContextWindow evidence at query time within heading boundaries and token budgets, with follow-up reading around each search anchor; combines BM25/vector search via weighted RRF, MMR and optional local/remote reranking; provides automatic evidence injection, a browser panel for local embedding/rerank/OCR model downloads and health checks, keyword search without model downloads, and in-place rescans of imported directories.

给 DeepSeek Harness 的本地记忆层：养大肥鱼的可以下载来玩，经过测试下载之后比单纯用RAG和外部记忆库更有人情味更自然了。

Records recurring task corrections and tool failures locally, then compiles them into changes to eight harness components through explicitly started evolution, paired baseline/candidate checks, trial activation and rollback. Includes a budget and audit ledger; requires Node.js 24+ and a compatible DSH 0.2.1-rc.2 or later 0.2.x host.

Reversible context slimming for DeepSeek Harness: TOON-style lossless tabular re-encoding of uniform JSON arrays, stride-sampled table windows with line numbers, and cross-turn dedup for repeated tool output; every replacement passes a byte-plus-token gate (≤72% bytes, strictly fewer estimated tokens) and the original is spilled to disk behind a `[save-token #id]` notice retrievable in one call via the `save_token_expand` tool, with billed and avoided token metering on a settings dashboard.

Offline meme and slang dictionary: 6,792 built-in entries are looked up before a turn and injected only when a message looks like a meme question. Ships a lookup tool, a settings page for adding/editing/deleting entries and aliases, an adjustable tone slider for how far it plays along, and a built-in version check.