Memory

Persistent persona memory for DSH with a unified recent, long-term and archive timeline, bounded context loading, memory retrieval and isolated task delegation.

Codex-style file-based long-term memory for DSH: two-stage LLM extraction, consolidated MEMORY.md handbook, prompt-injected memory summary, and search/read/list/note tools.

The 7-7-7 execution loop for DeepSeek Harness — plan, run, capture, close, compound, with a human gate.

全局记忆：AI 主动写入与读取的记忆文件，每轮对话前自动注入索引，不占上下文，仅按需展开；支持本对话禁用。

Native shodh-memory integration for DeepSeek Harness — persistent cognitive memory without an MCP server in the context window.

Memex for DeepSeek Harness (dsh) — every day it records what dsh did (sessions, prompts, tools, files, commands) as a Markdown diary. · dsh 的起居注：每天自动整理 dsh 当天做了什么，存成日记。

Per-workspace memory library with manual per-chat opt-in, editable rules, three sharing modes, and continuous forgetting; cards stay readable Markdown.

Distills long sessions into background observations and reflections, injects them as a system-prompt section, and renders compaction summaries from prepared memory; includes a Settings page and source-backed recall.

Agent preset with adaptive tool presentation and environment-aware shell routing. Ports modules from yjh051108/dsh-routing-suite and xiaobright/dsh-anchored-standard (the former is listed here), so do not enable it alongside those presets. Requires DSH 0.2.2 or later; high uses PTC with on-demand tool unlocks and max uses PTC with the full available tool catalog.

给 DSH 上的一个会话装上自己的目标、记忆和作息：goal / memory / clock 三个插件

Cross-session memory for DSH: export every session to readable Markdown transcripts, keep one long-term MEMORY.md, and get a wake-up summary in a fresh window.

Port of the V2 memory pipeline from OpenAI Codex to DeepSeek Harness: a background agent extracts each idle session, consolidation folds the extractions into one memory_summary.md behind a git baseline diff, new sessions get that summary injected, and cited memory flows back as usage counts. A Settings page chooses the model, each stage's reasoning effort, and the idle, age, concurrency and timeout limits.

Cross-session development worklog for the agent: worklog_add appends one line (optional tag) to today's file, worklog_list reads a day back or lists the days on record. Entries are plain JSON under $DSH_HOME/worklog, so the next session can pick up where the last one stopped.

Send "Memory unlocked" to let the AI recall conversations it has forgotten.

Three-layer memory for DeepSeek Harness — a small always-on core block plus on-demand topic files (profile, preferences, decisions, lessons), with source-annotated writes and supersede-not-overwrite history, so preferences and project constraints stop drifting between sessions. Local-first: no vector DB, no server, no outbound calls.

Memory that outlives the session, kept as plain daily log files: one markdown file per day plus a generated index the agent greps instead of re-reading. Registers the annals skill, injects the write-it-down rules into the system prompt, and exposes three tools — annals_init builds the log directory, the index generator and a separate Git repository in one call; annals_query full-text searches past entries and returns them with file and line anchors; annals_links resolves which entry cites which. Reminds the agent once per turn when it changed files but wrote no log that day, and once more when the log was updated but the index was not. Adds a settings page for the six switches.

Turns corrections into permanent rules: explicit remember: triggers and auto-detected corrections pass a confirm bar (save globally / per project / edit / skip) and are written into a marked AGENTS.md section. New rules take effect in the current session and load natively in future ones; writes are deduplicated and version-guarded, and secret-looking content is refused.

Long-term memory on top of mem0 and a local Chroma store: user profile and recalled facts injected through the system prompt, capture at session end, a nightly pass that dedupes, merges paraphrases and resolves contradictions, a persistent topic graph written as Markdown cards, periodic export to a git repository, and a full-page memory UI with search, bulk merge, snapshots and undo. Needs a manual Python venv setup plus LLM and embedding API keys before use.

Story Mode preset for DeepSeek Harness: role-play GM persona, three-way choices, .md character cards and world book, context distillation and prompt wrapping.

Checks each claim in a finished answer against the tool output that same turn read: a contradiction whose quote is found in that output steers one correction in the same turn, and claims the output does not back are flagged in the session log and on stderr. A free scan for absolute words and unmatched numbers runs first, and a turn that ran no tool never reaches the model.

Exposes DSH as an MCP server so another agent can watch its thinking, tool calls and file writes in real time, share intent, take a floor lock that denies DSH's write/edit/git tools, inject mid-turn alerts, and delegate reviews.

ReMe-shaped long-term memory for DSH: Markdown workspace, BM25 recall, turn capture, scheduled consolidation

Durable cross-session memory plus a fetch ladder that survives hostname-keyed blocking. Four tools: memory_recall, memory_save and memory_stats over a plain-JSON fact store at $DSH_HOME/memory/facts.json, plus resilient_fetch which tries plain fetch, then a same-service alias host (Wikipedia only for now), then curl over IPv6 and IPv4 (needs curl on PATH). No daemon, no npm dependency, no network at import time. (1.3.0 shipped a fifth tool, memory_prune; it was withdrawn in 1.4.0 because adding a tool to a running plugin breaks sessions that were opened before it.)

A long-term graph memory plugin for DeepSeek Harness (DSH), powered by Neo4j.