Plugins

Exportação de sessões e arquivamento de conformidade para o DeepSeek Harness: redação determinística, saídas em Markdown/JSONL/PDF, gerenciamento de arquivo em disco e uma visão de tendência/auditoria.

Seletor de contexto de UI do desktop Windows para Codex, DeepSeek Harness e clientes MCP: seleciona janelas, elementos de UI ou regiões da tela com destaque ao passar o mouse, UI Automation, capturas de tela e OCR local, e depois revisa e aprova o contexto Markdown/JSON antes da saída.

Cartão de custo diário para seu gateway LLM local: /usage lê gateway_usage.jsonl e detalha gastos por modelo e por hora, cobrindo conexão oficial direta, relay do OpenRouter e pools medidos dentro do plano.

Operações do Kubernetes para o agente: obter recursos com saída JSON estruturada, descrever, logs, exec, aplicar/excluir (confirmado pelo usuário) e encaminhamento de porta.

Servidor A2A (Agent-to-Agent) nativo para dsh: expõe este dsh como um agente chamável via HTTP com tarefas JSON-RPC.

Conecta o Multica ao DeepSeek Harness por meio de um protocolo de processo JSONL versionado.

30 paletas de temas clássicos de código aberto (Catppuccin, Nord, Tokyo Night, Gruvbox, Solarized etc.) mapeadas para os tokens oficiais do ThemeService do DeepSeek Harness, com um painel de Style Settings para ajustes ao vivo de cor/fonte/raio e exportação/importação JSON para compartilhar pacotes de configuração.

Ferramentas HTTP de busca anti-bot endurecidas pela pilha de scraping em produção da SXS (milhões de requisições por dia): rotação de pool de UA, nova tentativa com backoff exponencial, detecção de muro anti-bot (captcha / desafios de verificação) e limitação de taxa adaptativa — ferramentas: `sxs_fetch` / `sxs_fetch_json` / `sxs_rate_status`.

Testes de aceitação independentes no navegador para entregáveis de agentes: entra uma especificação JSON e sai um veredito em Chromium real.

Memória nativa por workspace sobre as próprias costuras do harness: fatos e um perfil sempre ativo, porém limitado, na unidade JSON do domínio de armazenamento, gravações com aprovação e citações `(sessionId, seq)`, recuperação determinística e FTS de session-query sobre sessões passadas — sem servidor externo, sem SQLite personalizado.

Hooks de ciclo de vida no estilo Claude Code: comandos de shell configurados são executados antes/depois das chamadas de ferramenta do modelo, com um payload JSON via stdin; uma saída diferente de zero no pre-tool bloqueia a chamada

Terminal-style music video player for DeepSeek Harness Desktop: canvas MVs synced to your own audio file, MV packs (mv.json) for any song, sandboxed scene scripts and a GitHub-hosted workshop (创意工坊) — the world.execute(me) ASCII scenes and the dsh PV are

只填 Key 的服务商预设：50 家渠道为 DSH 一键写入官方 llm-pi-ai 路由与凭据（插件），并可写入腾讯 WorkBuddy、OpenCode（Key 走其 auth.json）与 cc-switch 的配置（CLI）；核心为纯 JS，可被更多应用的外壳复用。

独立本地记忆插件：JSONL 记忆条目、每轮 runtime-context 注入、local_memory_search/local_memory_remember 工具、设置面板管理页。不依赖 Mnemon。

Deterministic project actions shared by people and agents: one actions.json, a right-sidebar run panel, and agent tools.

A chemistry workbench panel in the DSH web UI. Draw structures on a Ketcher canvas (a script downloads the build; it renders locally in the browser with no backend), then compute on the current molecule with RDKit without calling a model — formula, molecular weight, exact mass, logP, TPSA, hydrogen-bond donors and acceptors, ring counts, Fsp3, stereocentres, Lipinski and Veber rule-by-rule checks, QED, PAINS/BRENK structural alerts and the Murcko scaffold, plus SMARTS substructure matching, fingerprint similarity, format conversion, standardisation and batch clean-up. A retrosynthesis tab talks to a pluggable backend (Retro* by default) over a single JSON-in/JSON-out process, and states what is missing when the backend is not installed instead of inventing a route. The calculations run in this repository's Python package (rdkit), which is installed with pip separately.

SMS forwarding webhook for DeepSeek Harness. Phone apps (SMS Forwarder, Tasker, or any HTTP POST) push messages to a local HTTP endpoint; the plugin stores them as JSONL and exposes sms_recent / sms_search tools so the agent can read SMS verification codes during tasks. Auto-extracts the first 4-8 digit OTP from each message, supports keyword filtering, and works over LAN or Tailscale.

Mounts the mcptoon MCP gateway as one stdio server, so the agent discovers the tools of every MCP server you have configured through mcptoon's compressed view instead of full JSON schemas on each turn. Ships a doctor CLI that checks the mcptoon executable resolves and prints the exact command/args override when it does not.

Reads .mcp.json from the .dsh home and from the agent workspace, mounts every mcpServers entry into DSH, and adds an MCP tab in the Web UI for listing, adding and unloading servers.

Per-project memory for DeepSeek Harness. Three Markdown files per workspace — PROJECT.md, DECISIONS.md and SESSIONS.md — are auto-created on the first step of any session in that workspace, re-read from disk and re-injected only when they change (and re-injected if compaction dropped them), and written back by classification through a memory_checkpoint tool, with a bounded end-of-turn nudge when a turn did work but recorded nothing. memory_read and memory_search read the live log and the archive, the latter over a zero-dependency BM25 index. The session log is capped at 200 entries with the overflow moved to SESSIONS-archive.md — never injected, but visible, readable and searchable, and restorable one entry at a time. Settings page: a workspace list with a path filter, read-only tabs for the three memory files plus the archive, reload, export/import of one workspace's memory as a JSON bundle, a two-step clear, a panel that rewrites or removes the AGENTS.md instruction block, and a PROJECT.md staleness reminder. A composer status chip shows that workspace's sync state and creates the files on click. Zero dependencies — no vector store, no embeddings, and no model calls.

Same-origin in mechanism with the two loudest lines in context compression. The code-skeleton gate follows the skeletonization approach of Headroom (Apache-2.0), whose published headline is 20% fewer tokens for coding agents and 60–95% fewer tokens for JSON, same answers. The estimator channel follows TokenPilot (arXiv:2606.17016), which reports up to 60% lower cost for long-session agents. Both figures are theirs, quoted as-is; this plugin ships no benchmark of its own and claims no reduction of its own. What it adds for DeepSeek Harness: choose a compression profile, set the Auto Compact trigger level and toggle code-skeleton compression from one settings section, with exact DeepSeek V4 tokenizer measurement, same-revision count verification, and fail-open behaviour that keeps the original tool results on unsupported models.

Intent fitting for DSH: the agent predicts several directions first, asks a batch of clarifying questions each round, narrows the distribution until one converges, then proposes it for your confirmation. Bottom-right floating panel, local JSONL archive, a

DeepSeek Harness Desktop 专属右键实用工具菜单：编辑、网页/Agent 搜索、Agent 快捷动作、文本工具、翻译与站内搜索、复制整条消息、导出对话（Markdown/JSON/PDF）。纯客户端 DOM 实现，并内嵌 host-patch（导航策略 + 剪贴板权限）宿主自愈，随应用更新不丢失。

Skill usage scoreboard for DSH: counts both per-session deduplicated and per-load usage, scores `skill` tool calls and direct `read` of skill files, and shows the tally in a three-tab settings page (skill ranking, session board, management) with paging and JSON import/export.