dsh-md-notes
A note-taking plugin for DeepSeek Harness (DSH). It provides a full MD notes manager and MD notes editor, letting you quickly capture conversation content into notes. Notes can be maintained by syncing to a Git repository.
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A note-taking plugin for DeepSeek Harness (DSH). It provides a full MD notes manager and MD notes editor, letting you quickly capture conversation content into notes. Notes can be maintained by syncing to a Git repository.
DeepSeek Harness (dsh) browser companion: a Chrome side panel that embeds the full dsh web UI and lets the dsh agent read the current page, capture HTTP traffic, and drive the browser.
AI 输入框粘贴大段文本自动缩略为 [Paste #N +M lines] 小序号标签(编号不可改);👁 点击预览全文(点外关闭)、✎ 编辑名称、↺ 恢复纯原文;无删除按钮,删输入框标签文本即消失;发送时自动展开原文并加固定方括号纯标识块分隔(编号与输入框一致);slash 命令参数展开不加装饰;代理可用 myds_read_captured 工具按编号读取标签对应文本。
Unofficial, high-fidelity Claude Code-style TUI for DeepSeek Harness, verified against real PTY captures
OpenTelemetry and Langfuse observability exporter for DeepSeek Harness: turn/step/tool/LLM spans, token and cost metrics, and sanitized LLM prompt/completion capture from the session/event stream, with async batching, bounded offline buffering, and retry with backoff.
dsh bundle: register ywleeo/browser-mcp (a local MCP server driving a real Chrome to search, capture, and automate any logged-in site) as native dsh MCP tools (mcp__browser__*).
Cross-session node reference (cue) for DeepSeek Harness: pick another session's user nodes and inject their captured context as a wrapped reference
dsh-plugin-appshot — a DeepSeek Harness plugin for macOS and Windows context screenshot capture.
One memory layer for every AI tool and agent, packaged for DeepSeek Harness with startup context, prompt-time recall, Mem MCP tools, and DSH thread capture.
agentmemory for DeepSeek Harness (dsh): full memory_* tools, capture hooks, and context injection over the local REST server
Standalone screen capture for DeepSeek Harness (dsh): browser hotkeys plus an agent-facing capture+read tool. Forked out of @liustack/modlens#48 (upstream declined the feature).
Desktop computer use for DeepSeek Harness (DSH): macOS app listing, accessibility-tree window capture, screenshots, and synthesized input — the seam, the local Swift-daemon provider, the computer_use_* tools, the approval policy, and a standalone MCP server in one installable plugin package
Track Bridge: embedded task-management engine for DeepSeek Harness — decision-point protocol, capture wall, and Linear-shaped issue store over session events + storage KV
Model-bound custom HTTP headers for LLM requests: llm/stream capture + ALS + fetch injection (soft-replacement: host half + settings.section UI)
dsh-doctor: self-healing watchdog for the DeepSeek Harness web profile. Recovers from plugin-induced boot failures within 60s, captures every tool error, and watches all live sessions for stuck turns.
Native DeepSeek conversation capture, requirement analysis, and DSH Desktop handoff.
The LLM debug console inside DeepSeek Harness — capture every model call, see everything, replay anything.
失败账本 — DeepSeek Harness 工具失败记录、签名聚类与失败感知重试拦截(含 Web UI 面板)。Failure ledger for DeepSeek Harness: capture, cluster, persist and learn from failed tool calls, with a failure-aware retry guard and a Web UI panel.
Capture AI web conversations to local JSON + SQLite, and port selected messages into agent harnesses as live, continuable sessions.
macOS Vision OCR tool plugin for DeepSeek Harness: read text from screen capture, clipboard images, or image files (zh-Hans + en-US). Unofficial community project.
Local vision 'eyes' for DeepSeek Harness (DSH): screen tool (capture screen or image -> local OpenAI-compatible VLM description) and ocr tool (Windows built-in OCR, zero model / GPU / cloud).
OmniVision for DeepSeek Harness: an OmniParser-powered GUI agent plugin — screen capture, element recognition, click/type automation and a browser vision dock with recognition history, diffing and summary
Token usage statistics for the DeepSeek Harness Web UI: captures per-request LLM usage from the llm/stream waterfall, persists it, and renders animated charts grouped by API (provider), model, and date.
Auto-capture key decisions from dsh sessions into a versionable DECISIONS.md and inject them into future sessions