Plugins

Talk to DeepSeek Harness from Feishu / Lark. A chat maps to a DSH session, messages become turns and answers are pushed back as cards; questions, permission requests, model switches and conversation switches are interactive cards, and inbound files and images are downloaded into the workspace.

Fork of amlyczz/dsh-lark-link (MIT), maintained by Very12345. Per-conversation reasoning-effort controls, multi-app isolation, and streamed task-status cards.

Pushes DSH session events to phone IM and lets you reply straight under that message, injecting the text back into the right session. Covers nine event kinds: task completion, execution error, execution blocked, manual abort, token limit reached, abnormal interruption, waiting for your answer, permission request, and waiting for plan confirmation. Channels are QQ single-chat bots and Feishu custom apps, both over WebSocket long connections — no public IP, domain or tunneling needed. Several bots can be configured at once, each subscribing to the sessions it cares about. Approvals and questions arrive with tappable buttons, and replies route home through three layers (button, quoted reply, explicit short-id prefix), falling back to the most recent intervention-needed notification and echoing which session it went to.

DingTalk alerts when the agent needs your choice or approval, or finishes a turn; it stays quiet while you are watching the DSH page.

Bridges DeepSeek Harness sessions to Feishu/Lark, Telegram and DingTalk: each chat is bound to a resumable DSH session, replies stream back as cards, and a task-end card reports the model, token usage, step count and duration. Question and permission-approval cards are answerable from the chat, and a web settings pane configures the per-channel credentials.

Five task-state reminders for DeepSeek Harness (completion, approval, question, block, error) with four synthesized browser sound presets, system notifications that open the right session, and a terminal-BEL fallback when no browser is ready.

A /review command that hands the current change set to a reviewer subagent pinned to the model you choose, with one continuing reviewer session per chat.

Source Control panel in the DSH Web left rail: search, switch and create branches with ahead/behind counts, a topo-order commit graph, and a click-to-expand preview of any commit showing its files (A/M/D), insertions and deletions, message, author and timestamp. An always-on footer dock above Settings carries the branch dropdown and recent commits and follows the open session; fetch and fast-forward pull are one button, and a git_worktree agent tool creates, lists and removes worktrees.

A code review workflow that reviews uncommitted changes, changes against a base branch, a single commit, a GitHub pull request, or a file.

Task workspace convention: one folder per session, one PROGRESS.md per task overwritten on each update, and per-task git once the task runs long.

Gated four-stage video pipeline: brief, script, assets and compose, turning one sentence into a narrated explainer with ComfyUI workflows or image/video APIs and FFmpeg assembly.

Session-scoped research evidence ledger with sources, linked claims, open questions, and explicit user review; provides a tool, slash command, and conversation panel, with selected-claim Markdown export that omits excerpts, review notes, and local paths by default; does not fetch sources or verify their truth.

Session-scoped delivery receipts for local artifacts: compare current file hashes with a recorded baseline, keep agent claims separate from explicit user acceptance, flag changed or unavailable files, and export a Markdown receipt through a tool, slash command, and conversation panel.

Alpha Agent Teams plugin for DSH 0.2.0-rc.2 and newer that lets same-session user Steer end the Lead’s current wait_agent call while teammates continue, with native message delivery and Node PTC continuation.

Ports jcode's auto-poke so an idle agent keeps working while its session still has incomplete todos.

Provide a LeLogin skill for credential injection and authenticated business applications without exposing plaintext secrets.

Skill browser and switchboard for the DSH web GUI: a sidebar entry lists skills from configurable source directories as cards, clicking a card opens the full SKILL.md, and the per-card switch writes disable-model-invocation and registers or removes that skill in the agent skill catalog, so the model can load exactly the skills that are switched on. It also recognises WorkBuddy expert-team folders and shows avatar, tags, quick prompts and members, registering its lead prompt as a skill when switched on. Source directories are editable in the panel.

Skill center: browse and manage local Agent Skills, and search, preview and install skills from the ClawHub, ModelScope and QwenPaw marketplaces in one merged view with source and category filters; ships a `skill_hub` tool so the agent can install skills itself.

Agent skill and tool for querying multi-platform model account balances: DeepSeek, Doubao / Volcengine, Qwen / Alibaba Cloud, Hunyuan / Tencent Cloud, and custom HTTP endpoints. Read-only, with 60s cache.

Knowledge-point notebook for DeepSeek Harness: turns a Markdown notes folder into a card canvas — folder = chapter, file = section, body = knowledge points — with masked-answer questions for self-testing, KaTeX formulas, Mermaid flowcharts, a mind map view and in-panel editing.

Speaker button left of the model selector in the composer tool row — one click scrolls to the start of your newest question, marks it with a blinking caret and reads from there through the newest agent reply (dsh-tts, browser voice as fallback); press-and-hold the icon and then click anywhere on the page to pick another reading start position; press-and-drag-up opens a vertical mixer for in-page media volume and system output volume.

Local OCR with nothing sent to a cloud: mounts the PP-OCRv6 Medium stdio MCP server (PaddleOCR on ONNX Runtime, CPU) as mcp__ppocr__ocr_image and mcp__ppocr__ocr_pdf for images and multi-page PDFs.

Vision through NVIDIA NIM: mounts the bundled stdio MCP server as mcp__opencode_eyes_nvidia__describe_image, which describes an image with any of seven hosted vision models (MiniMax-M3 by default) and rotates several API keys.

Eyes for text-only models: mounts the bundled stdio MCP server as mcp__opencode_eyes__describe_image, which sends an image file to StepFun step-3.7-flash and returns a detailed description.