A toolkit for low-level operations in DSH, designed to reduce token usage and task execution time / DSH 底层操作工具插件，旨在减少 Token 消耗与任务耗时
- dsh
- dsh-plugin
- dsh-plugins
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Anti-laziness skill for AI agents. Core: the Depth Tree method, which splits a task N layers deep and gives every leaf the full time budget of the whole task, so effort multiplies with depth. Grounded in 2025-2026 research on model laziness, underthinking and premature completion.
把 DeepSeek Harness 装进你的口袋：电脑上跑 dsh web，手机扫码即同步访问（局域网 + 公网，实时同屏）Put DeepSeek Harness in your pocket: run dsh web on your computer and access it synchronously by scanning a QR code on your phone (LAN + public network, real‑time screen mirroring)
Scene-aware storyboard for DeepSeek Harness: 9-16 numbered cells with timestamps + transcript + an audio envelope, packed into ONE image (384 tokens). Two tools: video_storyboard and video_zoom.
- asr
- contact-sheet
- deepseek-harness
- dsh-plugin
Turn a scene prompt into a shot sheet, then have a coding agent draw the film in HTML. No video model.
- animation
- anime
- claude-code
- generative-art
麦门全能管家：基于麦当劳中国官方 MCP 的一站式助手——自动领券、权威比价、点餐推荐、每日巡检、巨无霸指数。2026 麦当劳程序员节创意开发大赛参赛作品。
- mcdonalds
- mcp
- mcp-skill
- model-context-protocol