Plugins

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.

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.

iPolloWork HyperFrames Video Studio and 27 editable video templates as a native DeepSeek Harness conversation view.

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.

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.

Evolve skills, agents, prompts, code and plugins from inside DeepSeek Harness, with AgentDescent.

Continual self-evolution: versioned, auditable, rollback-safe harness state (prompts, memory, skills, subagent specs) refined from session trajectories, with review gates and hot-reloaded skills.

Research agent suite: long-horizon goal control with auditable evidence chains, cron scheduling, multi-agent expert teams, self-evolving research memory (FTS5 + RRF recall), project workspaces, and a custom workspace UI.

Long-term memory & self-evolving plugin for DSH: L0 capture → L1 memory extraction → L2 scene grouping → L3 user persona, auto recall injection, skill synthesis, fully local (SQLite FTS5 + jieba, optional vector recall).

Cross-session memory with zero-token deterministic recall (bigram-Jaccard fused with FTS5 BM25 via RRF, Chinese-aware tokenization), reinforcement that strengthens repeated observations, and procedures crystallized into SKILL.md files refined in place through an active-stale-archived lifecycle with reversible archive and rollback. Ingest and disposal each expose a user-chosen autonomy tier; conflicts and high-importance writes always go to human review, and nothing is ever auto-deleted. Requires Node 22.5+.

Self-evolving team memory as plain Markdown in git: a native Cordis plugin that registers 38 bare-name memory tools plus a prompt-signals section re-evaluated at every assembly, with RPE reinforcement, decay and sleep consolidation; shares one data repo with its Claude Code (MCP) and OpenClaw hosts; verified against DSH 0.1.0-rc.6.

Self-evolving team memory as plain Markdown in git: a native Cordis plugin that registers 38 bare-name memory tools plus a prompt-signals section re-evaluated at every assembly, with RPE reinforcement, decay and sleep consolidation; shares one data repo with its Claude Code (MCP) and OpenClaw hosts; verified against DSH 0.1.0-rc.6.

Evidence-first self-evolution controller: bounded Cordis candidate generation, one-shot real-Loader admission, Harbor evaluation, and a crash-resumable journaled lineage.

Self-evolving agent framework on DeepSeek Harness (dsh): 40 Cordis plugins and 4 presets covering memory, reflection, gates, metrics and an auditable evolution loop. Not a one-command install. Clone the repo and run install/install.sh --profile=web (needs bash, Node 20+, python3, DSH 0.1.7-rc.1 or newer with an initialized profile), then restart.

A self-evolving plugin for DeepSeek Harness: it observes how the agent runs, proposes improvements to its own assets via the LLM, validates each proposal inside a sandboxed trial agent, and applies only verified mutations — with a versioned ledger and automatic rollback on regression.

Self-evolving pitfall immunity for coding agents (Claude Code, Codex, Cursor, ZCode, DSH): capture failed-then-fixed tool episodes as SQLite+FTS5 antibodies and inject them before the agent repeats the mistake. Zero runtime dependencies.

Git and source-control plugin suite for DeepSeek Harness: local git operations plus GitHub, GitLab, Bitbucket, Azure DevOps and Gitea adapters, with self-evolving memory.

Proactive multi-model scheduling plugin: multi-source signal intake with dedup and urgency ranking, a four-way execute/defer/dismiss/ask-user decision engine, DAG plan generation with parallel model execution, quality reflection with automatic retry and model switch, long-term memory for task patterns and lessons, and strategy evolution via genetic algorithms with sandboxed evaluation and canary rollout.

Self-evolving pitfall immunity for DeepSeek Harness: capture every failed-then-fixed tool episode, distil it into a reusable antibody stored in SQLite+FTS5, and inject the relevant ones before the agent repeats the mistake.

Graceful restart + client auto-reconnect + cross-restart goal continuation for DeepSeek Harness (dsh). After a plugin update dsh-phoenix restarts dsh at a safe idle boundary, keeps the browser page connected, and resumes a running goal so a task can keep

anagenesis —— DeepSeek Harness 上的可编程记忆编排层 + 自我进化引擎：自带闭环记忆存储（不依赖任何外部记忆插件）、17 个面向 Agent 的语义记忆工具（召回/提交/提升/降级/拆分/锁定/过期/反事实重思）、运行时可切换的注入策略、带审计与回滚的元策略自调节、全程可逆效应、自动注册 `anagenesis` Agent 预设，以及零依赖可视化层（终端仪表盘 + mermaid/d2/ascii 文本图表 + 可选桌面窗口）。

Self-evolving project-level Agent for DeepSeek Harness: 16 SDD workflow skills (clarification, PRD, issue, coding, locating, acceptance, review) plus project memory and knowledge that compound over time.

Windows computer-use capability for DSH: screenshot → vision model → simulated mouse/keyboard with self-evolving knowledge base. Dual-mode plugin tools + skill-only pwsh fallback.

DSH-native skill intelligence cockpit: task decomposition, cross-domain multi-skill composition, skill authoring, local recommendations and safety scans for DeepSeek Harness.