Plugins

Runs local CLI agents (Claude Code, Codex, Antigravity and Pi by default, auto-detected) as panels inside DSH, reusing the official subprocess.spawnTerminal with an embedded xterm.js. Names, commands, colours and order are configurable. Requires DSH 0.2.2-rc.1 or newer. The CLI agents must already be installed and run with your own user permissions.

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. Within a turn it supports skeletonized information compression with a low original-text retrieval rate; at the tail of a turn it supports a turn-tail intent summary implemented purely by content substitution; context content stays safe, and the whole process runs inside the official JSONL compression.

Connects your GitHub account to DSH agents from the composer GitHub button (OAuth device flow or personal access token) and lets them call the GitHub API through the github_api tool.

Continual self-refinement loop: persistent memory, periodic review-and-refine, cross-session shared knowledge, and automatic rollback through a model-callable harness_refine tool.

Edit the global ~/.dsh/AGENTS.md rules from the web settings panel, live on save.

Barrage-meme skill distilled from 22,771 real messages in the 6657 live room: wanjiqi-style banter, CS and DOTA cross-memes, player roasting and casting commentary.

Wenyuan Pavilion: an AI Team workbench for DSH with owned tasks, independent acceptance, an append-only ledger and concurrent projects. Install it into its own profile (dsh plugin --profile ai-team add @suifei/dsh-ai-team), not web or desktop: its patch sets that profile's sandbox to danger-full-access and approvals to never, and the member agents run with full access. The project's PMO acts automatically by default (every 60 s it resolves pending decisions and wakes owners to dispatch the next tasks); turn off PMO auto to send decisions to your inbox.

Aggregated multi-upstream web search for DeepSeek Harness: replaces native web_search with model-native grounding and agent search APIs, source attribution, and rich citation cards.

Infinite-canvas e-commerce visual workspace for product photography, virtual try-on, background edits, and video, synced live with the Harness conversation.

Third-party DSH bundle carrying the original deterministic-pixel-art Skill for editable JSON/PNG pixel art, Python rendering and recoloring within declared regions. Needs DSH 0.2.2-rc.1 (other DSH versions are not claimed compatible) and Python 3.10+ with Pillow.

Ships a set of /logi commands for project housekeeping: dispatches security, logic-correctness, maintainability, reliability and performance experts to inspect the whole project, then produces one consolidated improvement report.

Connects DSH to a local anet node through a stdio MCP client, with three skills and 14 tools to discover agents on the AgentNetwork, send, track and answer end-to-end encrypted A2A tasks, pay or decline priced skills within the operator's limits, read the local evidence chain and report the node state. Linux/macOS only; requires an anet 0.3.0+ node running locally.

Always-on-top notch for Windows that shows which sessions are working, which need you, and which are done or failed: one bot per session, never takes focus, hides under full-screen apps, with its own settings page.

AI-for-Science research workflow skill for DeepSeek Harness, aimed at researchers and grad students using agentic AI: multi-angle literature review with per-angle files, experiment design with a caveat list, figures and paper reading; each job returns files plus a cross-verification brief for a second model. Zero deps, MIT.

Projection-driven live DAG for a Session's subagents and durable workflows: status and navigation, deterministic deep-chain layout, fit/pan canvas controls, and current-session node rearrangement.

Reverse-engineering preset for DeepSeek Harness: domain skills live inside one "reverse mode" and the model routes by target type (web/JS, Android, iOS). The JS domain ships three skills (AST deobfuscation, controlled iv8 execution, JSVMP recovery) and mounts the js-reverse-mcp browser forensics server as mcp__js-reverse__* tools.

Experience memory and reflection for DSH agents: automatically extracts candidate lessons after tasks and recalls user-reviewed lessons in relevant later tasks. Supports source provenance, project-scoped retrieval, conflict handling, usage feedback and expiry review; capture and recall have separate controls, and writing lessons to AGENTS.md requires preview and explicit application. A step-by-step first-run guide (4 steps) now opens inside its settings panel.

Agent2Agent protocol v1.0 for DSH: run a standard A2A server to let other agents call this instance, connect to remote A2A agents as clients, and manage both from a visual settings page.

Exports the session event stream to OpenTelemetry OTLP and Langfuse as sanitized, buffered traces and metrics, off by default.

Dedicated model routes, tools, and system guidance for vision, compaction, reviews, subagents, titles, and image generation.

Expert-mode agent preset for DeepSeek Harness (v0.9.2, npm dsh-expert-mode, bilingual EN/ZH): a chief coordinator plus 17 domain-expert subagents with automatic task delegation. Features: taskboard scheduler (file-system task state machine pending/ready/running/done/failed, dependency DAG, atomic claim, retry, crash recovery), quality gates (5-stage pipeline for high-risk tasks: requirement clarity, implementation, verification, independent review, integration, with 2-round rework limit), Five-Anchor constraint (review/convergence/anti-drift/collaboration-check/resource-awareness per turn), Near-distance Guidance (identity/task/output template per expert), progressive disclosure (~28% token savings), expert persistence, inter-expert file message bus (direct P2P comm, zero coordinator relay), cross review, experience pool, fast-track for simple tasks, fault recovery with auto-retry. Experts: data analyst, copywriter, legal review, product manager, frontend, UI/UX, architect, social media ops, growth hacker, quant finance, finance, backend, DevOps, database, QA, security.

Browse every message you sent in the current session: full-history listing with newest-first sort, text filter, one-click copy, and jump to a message (auto-loads earlier history when the target is not yet loaded).

Claude Code-style terminal UI for DeepSeek Harness agents, as an out-of-tree dsh plugin bundle