Plugin

Esportazione delle sessioni e archiviazione per la conformità per DeepSeek Harness: redazione deterministica, output Markdown/JSONL/PDF, gestione degli archivi su disco e una vista di tendenze/audit.

Selettore di contesto UI del desktop Windows per Codex, DeepSeek Harness e client MCP: seleziona finestre, elementi UI o regioni dello schermo con evidenziazione al passaggio del mouse, UI Automation, screenshot e OCR locale, poi rivedi e approva il contesto Markdown/JSON prima dell'output.

Scheda dei costi giornalieri per il tuo gateway LLM locale: /usage legge gateway_usage.jsonl e dettaglia la spesa per modello e per ora, coprendo connessione ufficiale diretta, relay OpenRouter e pool a consumo inclusi nel piano.

Operazioni Kubernetes per l’agente: ottieni risorse con output JSON strutturato, describe, log, exec, apply/delete (con conferma dell’utente) e port-forward.

Server A2A (Agent-to-Agent) nativo per dsh: espone questo dsh come agente richiamabile tramite HTTP con attività JSON-RPC.

Collega Multica a DeepSeek Harness tramite un protocollo di processo JSONL versionato.

30 palette di temi open source classiche (Catppuccin, Nord, Tokyo Night, Gruvbox, Solarized, ecc.) mappate sui token ufficiali del ThemeService per DeepSeek Harness, con un pannello Style Settings per modifiche live di colori/font/raggio ed esportazione/importazione JSON per condividere pacchetti di configurazione.

Strumenti HTTP di recupero anti-bot irrobustiti dallo stack di scraping in produzione di SXS (milioni di richieste al giorno): rotazione del pool UA, nuovo tentativo con backoff esponenziale, rilevamento di muri anti-bot (captcha / sfide di verifica) e rate limiting adattivo — strumenti: `sxs_fetch` / `sxs_fetch_json` / `sxs_rate_status`.

Test di accettazione browser indipendenti per i deliverable degli agenti: in input una specifica JSON, in output un verdetto da Chromium reale.

Memoria nativa per workspace sulle cuciture stesse del harness: fatti e un profilo sempre attivo ma limitato nell’unità JSON del dominio di storage, scritture con approvazione e citazioni `(sessionId, seq)`, richiamo deterministico e FTS session-query sulle sessioni passate — senza server esterno, senza SQLite personalizzato.

Hook del ciclo di vita in stile Claude Code: comandi shell configurati vengono eseguiti prima/dopo le chiamate agli strumenti del modello con un payload JSON su stdin; un codice di uscita diverso da zero nel pre-tool blocca la chiamata

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.