Plugins

Per-round reasoning_effort optimizer for dsh — auto-downgrades reasoning for simple tool calls and lifts back for heavy work, cutting thinking time between tool calls.

On-demand second opinions through ask_advisor, with editable requests, per-call human approval, and text advice from a model configured in DSH.

An opencode-inspired terminal UI for DeepSeek Harness that boots as a dsh profile app plugin, with a session sidebar, streaming chat, markdown tool cards, todo lists, slash-command suggestions, a telemetry footer with a context meter and inline approval prompts.

Scheduled tasks: run a prompt on cron schedules, each run opens a new agent session to do the work, with workspace binding, manual run, session auto-naming, and a fullscreen task management page.

Xueqiu (Snowball) market panel docked above the composer: A-share/HK/US quotes and indices, watchlist, candlestick K-line with volume, MAs and crosshair tooltip, hot list, search, 7x24 news, plus a draggable mini index badge — no login needed.

Compliantly use your own Antigravity quota in dsh: bridges your local logged-in official Antigravity CLI (agy) session as the chat and subagent model provider.

Qingxiao (Wuthering Waves) themed skin for the DSH web GUI, with ice-blue/jade/moon-white palette, sword-light motes and user-swappable backgrounds.

Visual node-based workflow canvas for DSH with sub-agent calls, code execution, branching, loops, scheduling, and workflow import/export.

Visual round-table meetings for DeepSeek Harness — expert nodes on a ring with directed edges, an aggregation gateway, proxy thinking for black-box worker models, and adversarial review (red-team) of settled plans with per-viewpoint endorse/reject.

One-shot mcp-unity integration for DeepSeek Harness: bundled MCP server with zero manual config lets the agent drive the Unity editor through 34 tools - scenes, game objects, transforms, materials, prefabs, menu items, play mode, tests and console logs - with auto-reconnect.

Reversible context slimming for DeepSeek Harness: TOON-style lossless tabular re-encoding of uniform JSON arrays, stride-sampled table windows with line numbers, and cross-turn dedup for repeated tool output; every replacement passes a byte-plus-token gate (≤72% bytes, strictly fewer estimated tokens) and the original is spilled to disk behind a `[save-token #id]` notice retrievable in one call via the `save_token_expand` tool, with billed and avoided token metering on a settings dashboard.

Exports the agent loop to GreptimeDB as OpenTelemetry traces, metrics and logs, with seven Grafana dashboards covering token usage, cost, session outcomes and per-turn latency.

Records every agent write, edit and shell `rm` into a shadow git repository, then reviews them hunk by hunk in VS Code — accept or revert each one. Needs the companion dsh-review-vscode extension; the panel only appears inside VS Code's webview.

eDEX-UI-style shell over the DSH web GUI: system-telemetry left bar with per-core CPU sparklines, encom-globe world-map right bar with up/down traffic chart, filesystem browser with file preview, and a terminal-styled composer that follows the active workspace.

Modular AI research/engineering skill pack, installable via dsh plugin add — registers 27 skills (security audit, paper reading/writing, figure drawing, dev workflow, storage analysis) on ctx.skills.

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+.

Cordis /hongtou command: two-phase pipeline (LLM structured JSON + deterministic Word 2003 XML template rendering)

VSCode-style workbench shell for the DSH Web UI: activity bar, side bar, editor area, panel and status bar, with a registry service (ctx.workbench) for mounting panels, views and commands.

Connect a ChatGPT account to Codex models in DeepSeek Harness through browser PKCE or device-code OAuth, with automatic token refresh and Web or headless login.

Side-panel Xiangqi board for DSH: play as red while the current DSH model chooses black moves, with Host-side rule and revision checks.

Security scanner for DSH plugins: static and semantic passes over plugin source, DSH-specific attack-surface rules, npm audit, batch scanning, and an HTML report with per-finding severity and evidence.

Analyze usage across models, providers, workspaces, and time ranges — including custom start/end dates over the full retained history — with live cache-hit visibility and separate model and provider breakdowns. Includes hourly single-day trends, daily cross-day trends, a 53-week GitHub-style heatmap, usage streaks, model and workspace Token-share donut charts with Token, cost, and percentage details, independent combinable filters, cache-efficiency trends, DeepSeek account balance, workspace aliases, CSV export, and a durable ledger that preserves successfully flushed usage after session deletion — and after a workspace is deleted, where its recorded usage is summed into one Deleted row — and rebuilds incrementally — on restart, unchanged sessions are applied from the ledger without re-reading their logs (a per-session log revision is the change signal), and only changed/new events are folded. The workspace registry is kept fresh automatically through the DSH domain/changed probe: only added/removed workspaces are reprocessed incrementally, unchanged workspaces reuse their computed aggregates and ledger with zero rescan, and usage is strictly limited to DSH-registered workspaces (unregistered cwds are ignored). After a scan, lightweight revision status fetches full history only when the Host/data state changes and exposes non-sensitive sync health (revision reuse, rereads, ledger recovery, and failures). Token accounting is explicit: input is fresh (cache read/write and reasoning are separate buckets) and zero-usage replays never overwrite recorded usage. Chinese uses local time, English uses UTC; API access is loopback-only.

Deterministic context compression for dsh — zero LLM calls, rule-based pruning that preserves paths, commands, error traces, and open todos verbatim. Compresses ~80k tokens to a few hundred.

Multi-engine text-to-image generation (OpenAI Images and Zhipu CogView presets) with per-session quota tracking, engine failover, credential-safe config, and a result card with regenerate.