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Per-wallpaper offset for dsh-dream-skin - nudge the current wallpaper along X and Y in pixels from Settings, remembered separately for each image, URL or gradient.

AI가 당신이 '말한 것'이 아니라 '어떻게 생각하는지'를 기억하게 합니다. 원칙, 레드라인, 업무 습관을 세션 전반에서 능동적으로 수집하며, 기억 용량, 완만한 감쇠, 모든 항목에 대한 사람이 읽을 수 있는 근거를 제공합니다. 0.7.0에서는 근거 추적이 가능한 직관적인 페르소나 초상화를 추가했습니다.

Cross-session memory for your dsh agent: remembered, recalled, and re-verified instead of assumed.

A continuation of simon300000/dsh-auto: the Auto Approve permission preset for the DSH Web UI reviews each approval with one single-shot model call instead of a reviewer subagent, auto-approves only the actions that pass and hands the rest to human approval, and remembers confirmed decisions as project- and global-scope allow/deny lists, with an approval timeline in the right sidebar.

会话归位：把游离（未分组）会话按 canonical cwd 重新归属到匹配的工作区，只修 workspace 归属记录，不动会话文件。

ETeams for DeepSeek Harness: captain-led multi-agent team collaboration with execution chains, task slots, member dialogs and persistent state

Per-wallpaper offset for dsh-dream-skin - nudge the current wallpaper along X and Y in pixels from Settings, remembered separately for each image, URL or gradient.

Session model selector with search: two-stage loose matching (normalised substring first, subsequence as fallback, so glm53 finds GLM-5.3 and ds finds DeepSeek), providers with recent successful calls pinned first, and a reasoning-effort pane that remembers each model's last explicitly chosen effort.

A /remember command that writes facts into the AGENTS.md instruction hierarchy dsh already loads, plus a Memory tab showing which instructions the loader kept within its byte budget.

Use a Kimi Code membership in DeepSeek Harness through a dedicated Kimi subscription model route

Official-grade DeepSeek Harness memory plugin backed by Hindsight (vectorize-io). Add /hindsight commands and model tools that recall, remember, inspect and forget through a Hindsight memory bank.

Control a DeepSeek Harness agent from Feishu/Lark: send a task by DM, an agent runs it with your configured model and replies in the chat, and a feishu_send tool lets the agent push results. Uses lark-cli's WebSocket connection, so no public webhook is needed, and ships a resident launcher. Note: the plugin does not check who sent a message, so anyone who can DM the bot — by default, members of the Feishu tenant the app belongs to — can drive an agent running with the host's own model credentials and file permissions. Setup is not one `dsh plugin add`: `lark-cli` must be installed and authenticated once, and a Feishu self-built app with the permissions the README lists is required.

Open the current registered Workspace from the Session Header or Workspace menu in a detected or configured editor, with hot re-detection and a remembered browser preference.

Connect Trilium notes to the DSH agent via ETAPI with 20 agent tools: durable memory (remember/recall + auto-injected index), note management (CRUD/clone/attributes/revisions), full-text search, weekly-report workflow, attachments, calendar notes, backup/import, and a settings card.

LLM-driven remember/forget memory: after each turn a model decides what to keep (MemoryDirector), injects relevant memories before each step, dedups, and persists cross-session.