Plugins

Bridges the shared ~/.agentloom store between DeepSeek Harness and Codex: injects the shared memories and the AGENTS.md entries the context budget truncates into the system prompt, and adds six loom_* tools for status, sync, memory search/list/add and skill listing. Requires the agentloom CLI installed and a one-time agentloom init; the seven-tool MCP bridge in the same repo is a separate package for MCP clients.

A cross-workspace Library for DeepSeek Harness: agents record files, tools, environments, knowledge and work records so any later session can index, search and reuse them.

Mirrors other coding agents' sessions into DeepSeek Harness as continuable tasks, one workspace per application, with content-fingerprint deduplication.

Gives the model in DeepSeek Harness a real new_conversation tool: creates a session in the current workspace, delivers a self-contained handoff as its first user message, optionally attaches a read-only dsh-session: reference to the calling conversation, pins the title, and switches the Web UI to the new session.

Intercepts DSH tool results before the model reads them: dedupe cache for repeated calls, a declarative decision graph that replaces large outputs with structured digests, an injection gate, and an honest token ledger that includes a negative-return account for over-compression. Measured 1400-1600 tokens saved per hit; the cumulative ledger is currently negative and the README says why, including that it cannot skip model turns.

Drive locally installed Codex CLI and Claude Code from DeepSeek Harness through a settings page and agent tools, exposing their sessions, configuration and run state.

A five-stage engineering loop for agent-built projects — spec, build, verify, ship, learn — with one artifact and one gate per phase, so an agent always knows the single next action. Role policy, project templates and deployment sit behind explicit ports: swap the implementation without rewriting the loop. Its scaffold generator lays out the internal layers of a project — `init --layout {none,webapp,service,plugin} --stack {python,node,none}` — from nine layers sampled out of three unrelated production projects: entry docs, an OpenSpec plan face, a spec truth layer (INDEX, one file per domain, TESTING, CONSTITUTION), a wiki split into knowledge / progress / runbook, the six `.agents/` slots, server+web, scripts/deploy/config, tests+e2e and a gitignored out/. Non-none layouts also gate the directory contract and compile every source root. Ships a Python CLI (init/next/check/ship/new) plus a local command adapter and an SSH/systemd adapter with release directories, an atomic current/previous switch, a deploy lock, a commit-versioned JSON probe and automatic rollback on a failed probe; bootstrap and teardown provision and remove the unit and the reverse-proxy block idempotently and refuse to delete a root they did not create. Includes a runnable example workspace and a skill that keeps the agent on one phase at a time. Requires Python 3.10+ and PyYAML; remote deploys need SSH access, rsync, systemd and Caddy on the target.

Control tower tools: dispatch a task to a role agent, read its report, verify and accept or send it back. Requires the separate agent-control-tower Python CLI (tower; it is not on PyPI — install it with pip install -e from the same repo) on the DSH process's PATH plus a tower init-ed workspace; without it every tool call fails with ENOENT.

Local media toolbox for DeepSeek Harness: converts files between 27 video, audio and image formats, trims clips, extracts audio or video tracks without re-encoding, exports embedded subtitles to .srt, compresses images with a before/after preview, reads and rewrites metadata, and encodes or decodes Base64 — all through the ffmpeg already installed on the machine, so files never leave it. The same engine is registered as a media_toolbox tool agents can call.

Layered memory for AI agents: five verbs (wake/work/pit/tomb/close), core layer read every time, archive on demand. Plain markdown, four pages created on first run; survives restarts, model swaps and plugin removal.

Runs Hindsight long-term memory on your own machine: after a one-time uvx --from hindsight-embed@latest hindsight-embed profile create server setup (~450 MB of Python dependencies) and with your own LLM key, the plugin manages the local memory server itself (health probe, start, stop, logs), registers ten hindsight_local_* tools for status, page search, page read, recall, remember and reflect, injects a knowledge-page index once per session, writes each finished turn back into the bank, and extracts facts with your own LLM key. Do not enable it alongside the official @vectorize-io/hindsight-coding-agents plugin: both read the same bank and would inject duplicate context. At session end it writes a handoff snapshot that the next session injects as previous progress. The data directory is configurable (dataDir) and scripts/relocate.mjs moves an existing install to another drive, creating directory junctions where the server hard-codes its paths.

Adds lasting bots with their own name, photo, persona, memory, voice and model, a Bots panel in the sidebar, and a hidden helper subagent per bot that follows the conversation, searches ahead and leaves notes the bot reads; voice uses your own ElevenLabs, OpenAI, Groq, Mistral or Deepgram key. Interface and prompts in Brazilian Portuguese.

After user setup, guides native subagents toward model preferences by task type, using native model-selection permissions with no extra routing-model calls.

Left-sidebar panel that views, edits and saves ~/.dsh/AGENTS.md live, with version-guarded saves and atomic writes.

Requirement-to-evidence audit for DSH sessions: maps each requirement to tool calls, files and commands, records per-requirement verification, and sends missing items back to the agent.

Project spaces, group chats, task boards, memory and usage for teams of DSH bots

本插件仅供娱乐使用，非实用性插件，下载前请自行选择。DeepSeek Harness 非官方社区插件（Token-Reducer?）：模拟执行任务，生成 SIMULATED 轨迹与 0 字节产物，不调用真实模型或工具/For entertainment only. Not a practical plugin — download at your own discretion.Unofficial DeepSeek Harness plugin that simulates task execution with SIMULATED traces and zero-byte artifacts.

Unofficial DeepSeek Harness port of the Academic Research Skills plugin (CC-BY-NC-4.0, non-commercial): 5 skills, 16 /ars-* commands, 4 agent roles, write-scope guard, and deterministic Python gates.

Two small macOS features in one plugin. keepAwake stops the display and system from sleeping while dsh runs (caffeinate tied to the host process). taskNotify posts a system notification when a top-level conversation finishes its turn, with the outcome (completed, error, blocked, output cap) and the duration; clicking the notification brings DeepSeek Harness forward. Click-to-focus needs Xcode Command Line Tools to build the notifier; without the toolchain the notification still appears but clicking it opens Script Editor. Subagents and Agent Teams members never notify, and a stop you pressed is silent by default. Both features can be switched off separately.

File-state cache skill for coding agents: one explore call replaces ls+grep+read, reads remember they already happened, and edits return a diff plus the exact changed line range instead of a full re-read. State is a JSON cache on disk, so it survives across tool calls and restarts. Requires Python 3.8+ (standard library only).

Registers the hosted SpecStream MCP server with the harness MCP manager and keeps the API key in the credential store. The server returns live web data as structured rows, each value with its source URL, and a run starts only after the quote's maximum is approved.

Monitor workspace sessions, subagents, todo progress and token usage in a floating panel.

Sends one system notification when a DSH turn ends: per-outcome switches for completed, error and interrupted, a minimum-duration threshold, silent subagents and unfocused-window-only delivery. Works on Windows, macOS and Linux, delivered through a connected page or a native fallback (PowerShell toast, osascript, notify-send; the Linux native fallback needs libnotify). Clicking the notification brings DSH back to the front on the page/Electron channel; PowerShell and notify-send notifications are not clickable.

Turns a stated rule into a checkable intake card and writes it into the right AGENTS.md, and keeps project plans, a rule ledger, project records, handoffs, a change log and a timeline.