OpenViking
volcengine
Self-evolving Context Database for AI Agents. Unify Agent Memory, Knowledge RAG and Skills.
PROJECT TOPICS
INSTALL REFERENCE
dsh plugin --profile web add github:060625dfy/dsh-prompt-boost
该命令指向仓库当前默认分支;尚无绑定当前 commit 的完整验证结果。
PROJECT README
English | 中文
Trae-style input booster for the DeepSeek Harness (DSH) web GUI. A sparkle (✨) button beside the model selector rewrites your typed draft into a high-quality, faithful, directly executable prompt — and after optimization the same button turns into an undo (↩) icon to restore the original input.
Inspired by Trae CN's "优化输入内容" (optimize input) feature: type a rough idea, click the magic wand, and the composer text is rewritten into a clear, structured instruction that the AI can execute directly. If you don't like the result, click the undo icon to get your original text back — you can loop optimize ⇄ undo as often as you like.
| Feature | Description |
|---|---|
| ✨ Optimize input | One-click rewrite of the current draft into a clear, structured, executable prompt |
| ↩ Undo | After a successful write-back the button becomes an undo icon; click it to restore the original input |
| Task-aware | The optimizer detects the task type (coding, data processing, writing, analysis, research, ops, …) and organizes content accordingly |
| Fidelity-first | Every concrete detail from your input (paths, numbers, names, commands) is kept verbatim; nothing is invented — missing key info becomes a 【请补充:××】 placeholder |
| Natural output | Trae-style natural instruction text with numbered points — no "角色设定:/验收标准:" label headers, no JSON, no template tables |
| Language-locked | Output always follows the input language (Chinese in → Chinese out, English in → English out) |
| Anti-clobber | If you edit the draft while optimizing, the result is not written back and undo is not armed |
| ✨ Optimize input | ⏳ Optimizing | ↩ Undo available |
|---|---|---|
![]() |
![]() |
![]() |
lib/index.js): serves POST /api/prompt-boost/optimize. It streams the optimization call through llm.stream using the deployment's default model (agentDefaultModel), applies the v6 optimizer policy, and returns { text } or { error } (90 s timeout, 8000-char input cap).lib/client.js): registers the conversation.input.right seat (tool row, right beside the model selector, before the send button), POSTs the draft, writes the result back via inputActions.setDraft, and manages the undo state machine.Zero build: the package is plain JavaScript (ESM host + __ModuleLoader__ web bundle).
Add the bundle patch to your web profile roster, e.g. in ~/.dsh/profiles/web/cordis.patch.yml:
- insert:
- id: prompt-boost
name: 'dsh-prompt-boost'
with the package available to the profile's node_modules (npm/link install), then reload the DSH host and refresh the GUI.
帮我写个脚本整理下载文件夹,文件太乱了llm + agentDefaultModel services mounted and a configured default modelMIT
CLASSIFICATION EVIDENCE
系统优先读取 GitHub Topics,再与站内分类词典和词根规则比对。当前命中: ai-prompt、prompt-engineering、prompt-optimization、web-ui。