Plugins

Automated data masking tool based on national standards, automatically identifying sensitive fields like ID cards and phone numbers.

Data lineage tracking tool, mapping the full lifecycle of data to meet source legality requirements.

Quantitative data quality scoring based on GB/T 36344-2018, providing auditable quality reports for data asset capitalization.

Tidy the model list of DeepSeek Harness: hide any model from the selector, rename models and channels while keeping the provider billing rate, and arrange both with arrows. Search, per-provider batch toggles, back to top, one-click restore. Display only — no provider configuration is rewritten.

Local-first hands-free AI voice assistant plugin for DeepSeek Harness (DSH), with speech-to-text, text-to-speech, voice commands, and local speech engines.

Lifecycle notification layer for AI coding agents — DeepSeek Harness 0.2 plugin: OS notification, in-page toast, and optional sound when a turn, background job, review, or failure needs you.

Multi-threaded downloader plugin for DeepSeek Harness with bundled aria2: probes the target for Range support, then picks aria2 (4 or 8 connections by file size) or falls back to curl.

Drive your local DSH from WeChat: a self-hosted iLink bridge over a persistent ACP session (context lives in DSH and is resumable), phone conversations grouped into the desktop workspace, with image recognition, file messages (Excel/Word/PDF, parsed by the agent itself) and voice transcripts. Tool approvals are answered inside WeChat itself (numbered card; ask/allow/reject policy; 120s timeout means reject), and any process can push a message to your phone through the outbox helper. Access defaults to strict (only registered devices are served); the phone channel's permission preset is configurable - see the README security section before sharing the bot.

OpenCode Go subscription models as a DeepSeek Harness provider: re-resolves the live gateway catalog every few minutes, auto-adapts models the built-in table has not seen, and covers streaming, tool calls, image input and subscription usage. A maintained fork of dsh-opencode-go: a clash with the upstream package over the llm-opencode-go settings namespace makes it withdraw quietly instead of failing the whole plugin tree, and an already-claimed opencode-go route makes it serve on opencode-go-plus.

Website cloning methodology skill: a real-source-first decision tree covering static sites, React/Vue/Next content sites and WebGL/Canvas-heavy fronts, mandatory verification of executable code quoted from second-hand AI analyses, and 13 zero-dependency Node scripts for CDP browser recon, asset/font harvesting, route crawling, sourcemap hunting and pixel-diff auditing.

ICVO coding-standards kit for DeepSeek Harness (formerly dsh-coding-kit): a bundle plugin that registers tools on load and injects the standards only when apply_coding_standards is called, plus a P0 gate CLI (npx spec-wave) with G1-G7 process commands, skills install, host apply, and IDE-block refresh.

TypeScript and JavaScript LSP configuration plugin for DeepSeek Harness using typescript-language-server.

Swift LSP configuration plugin for DeepSeek Harness using sourcekit-lsp.

Rust LSP configuration plugin for DeepSeek Harness using rust-analyzer.

Ruby LSP configuration plugin for DeepSeek Harness using ruby-lsp.

Python LSP configuration plugin for DeepSeek Harness using Pyright.

PHP LSP configuration plugin for DeepSeek Harness using Intelephense.

Lua LSP configuration plugin for DeepSeek Harness using lua-language-server.

Kotlin LSP configuration plugin for DeepSeek Harness using kotlin-language-server.

Java LSP configuration plugin for DeepSeek Harness using the Eclipse JDT language server.

Go LSP configuration plugin for DeepSeek Harness using gopls.

C# LSP configuration plugin for DeepSeek Harness using OmniSharp.

C/C++ LSP configuration plugin for DeepSeek Harness using clangd.

Prompt enhancement for the composer: an "✨ Enhance" button rewrites your draft prompt into a clearer, more structured version with first-principles thinking, grounded in session context, memory and recent conversation; asks clarifying questions in a card when key info is missing, then previews the result before applying it to the input.