Memory

Expose a second-opinion tool: when the main agent is stuck it hands the problem to an independent session, receives a plan back, and continues — without waking or impersonating the user.

DeepSeek Harness native adapter for tabellio: budgeted auto-recall, native memory tools, and explicit-clue candidates. The memory core stays in tabellio.

Neuron-inspired memory for dsh: turns buffer into a hippocampus, a nightly patrol classifies fragments into pools, and each turn injects a minimal auto-compacted handoff, the live mood (via dsh-feiyu-mood), and only relevance-filtered memories (Ebbinghaus half-life decay; recalled memories are reinforced like spaced repetition). Hard caps bound storage; past-session original text is searchable over multi-frame zstd; dsh-fish-memory stores can be imported. Optional vector retrieval (off by default, keyword fallback). The 3D panel offers four themes and pulses a signal from the center to each recalled memory.

dsh plugin: cross-session fact notepad — save tagged one-liners, find them back in any session via /fact and the fact_find tool.

MemoryBear long-term memory for DeepSeek Harness: per-turn recall, end-of-turn write, and a memory_search tool

分层记忆与混合召回知识库插件：把「记得住人、能召回可靠信息」的记忆系统接进 DeepSeek Harness，附带来源标注、置信度兜底与画像管理

Learning-mode agent preset for DSH with a topic knowledge base: answers retrieve from your own stored cards and cite the card they came from, mark anything not found as unverified, and only go online when verification is required. The sidebar panel browses topics, searches and edits cards, and every card can be AI-reviewed, verified, rolled back and versioned. Cards can reference each other with `[[title]]` links; the panel shows both outgoing links and which cards reference the one you are reading. New cards arrive as a preview you confirm before they enter the library; topic and card names are editable in the UI. The knowledge base is plain local files, not an automatic scraper.

Project-scoped SQLite memory with progressive retrieval, bounded context, a composer button and visual review. Install the repository-root DSH bundle, then run /learning-init with an absolute project path using local Python 3.10+.

Local-first knowledge base for DeepSeek Harness: each base is a folder of UTF-8 text, text PDFs and OCR-read images; the plugin retrieves from the session's selected bases before every turn with Chinese n-gram and BM25, answers carry citations that open in a right-sidebar reader, and the agent gets five kb_* tools (list, search, read, stats, propose text) plus /kb commands for create, use, files, search and rescan.

Long-conversation memory for DeepSeek Harness (DSH): keeps settled decisions, user corrections and exact numbers, with their conditions and sources, available across compaction and restarts in 100-1000+ turn sessions; one small budgeted evidence block per model step, with enabled skill rules re-applied in the same block.

Layered long-term memory for DeepSeek Harness: append-only event log, rebuildable tag index, day diaries, semantic layer, trend quarantine, and an offline knowledge-graph panel.

Prepares a workspace management protocol for an agent — three libraries (cognition, tools, external information), an optional preloaded session that has already read the workspace, and a re-read card when the workspace has changed enough.

Long-term memory kept as plain Markdown plus git: each session opens with a generated memory-context block assembled from a global store and per-project books (role card, user profile, current focus, routing table, recent logs), the plugin records which memory files the agent read and reminds it to extract conclusions while the day's log is unextracted, personas live in roles/<role>/SOUL.md role cards, and it ships a seven-tab settings page in the sidebar plus four skills. Requires Python 3.10+.

Static-context audit for a DSH home: a six-layer baseline (rules, memory, skills, tool surface, sessions, KB), broken-path checks for a markdown capability map, memory duplicate/stale/over-limit reports, SKILL.md description compression, and tool-surface plus cold-start static-context estimates recovered from session logs. Four read-only DSH tools; writes require --apply and are backed up first. Requires Python 3.10+ on the host (stdlib only; all four tools shell out to the bundled CLI).

Replaces the summarizing context compactor with a handoff note the model writes itself and a fresh window that keeps only the system prompt, the note, and the current turn.

Native generation-time Mixture-of-Agents: every turn, reference models run the same session context in parallel as pre-run drafts and one aggregator executes with full tooling; config-as-model recipes, F mirror / R trimmed views, enforced subagent gating (dual-shape session indexing), derived per-recipe vision (vision refs relay image reads to text-only aggregators), tiered cadence with separate steering and patrol rosters plus frozen reuse between beats, degeneration guard dropping degenerate reference output, anonymized model face (failure notices carry no provider identity), and cache-friendly guidance placement (the rehearsal record is pinned where it was produced instead of appended to every request, so the cached prefix covers it and each step pays only for what was added since - on by default across every cadence).

Ships a minimal lesson ledger: brief.ps1 to look up past pitfalls, add-lesson.ps1 to record new ones, deployed into the skills directory and wired into AGENTS.md by the installer. The model checks it before working and turns what it hits into rules, so the same mistake is not made twice. This plugin watches whether that actually happens and shows the result in a tab and under the composer.

A memory panel for DeepSeek Harness with one store per workspace: persona traits, notes about you, dated events, and a first-person diary the model writes and cannot edit. Every entry keeps the quote it came from and can be retracted; workspaces can share one memory and be split apart again; optional per-person profiles for group chats; a capped event list with ★ marks. Local only, no network, zero dependencies.

DeepSeek Harness (DSH) plugin: injects a bounded, timestamped snapshot of your local Second Brain (identity + state fingerprint + pointers) into every new session's prompt. Read-only, zero-write, fail-loud, zero dependencies. 第二大脑载入器：让每个新会话开局自带记忆快照。

Local-only cross-session memory for DSH with tools, system-prompt injection, and a Settings page.

Elephant Memory: your DeepSeek agent never forgets. An endless memory for the DeepSeek harness: the agent keeps every chat it has in a project and reads all of it at every turn through a fixed-size set of summary lines (after Victor Taelin's OptChat speci

Jev-scored context compaction for DeepSeek Harness -- keep the messages that matter, compact the ones that do not

A soul for DeepSeek Harness: an in-character Whale Chan agent preset with layered long-term memory and dream-like consolidation.

Partitioned long-term memory for agents, with folders as memory zones, a one-line index first, and a forgetting curve.