vibe
Vibe Code Orchestrator (VCO) is a governed runtime entry that freezes requirements, bounds execution, and enforces verification and phase cleanup.
25 results
Vibe Code Orchestrator (VCO) is a governed runtime entry that freezes requirements, bounds execution, and enforces verification and phase cleanup.
OMK — Observe. Measure. Know. Evidence-backed knowledge changes for AI applications.
Token-efficient assistant discipline for concise answers and task execution. Use when the user asks for direct, low-token work, or invokes this skill; includes optional file and Windows encoding utilities declared below.
Provider Model Configurator for DeepSeek Harness: view, create, edit, copy and delete model entries (context window, max output, modalities, reasoning efforts) across your configured providers, with quick-fill from the pi-ai preset catalog.
Vertical prompt quick-jump rail for the DeepSeek Harness web conversation view
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.
Tuning Engines CLI, MCP server, and Python agent runtime adapters for governed model, agent, skill, and MCP workflows. Fine-tune open-source LLMs, run inference, manage datasets/evaluations, and connect LangGraph or Temporal while Tuning Engines handles policy, audit, usage, and token economics.
AI 系统的数据层:把 18 种来源(文档站/GitHub/PDF/视频/Notebook/Wiki…)转成结构化知识资产,导出到 22 种目标(Claude/Gemini/OpenAI/RAG 管道/编码助手);AI 驱动项目扫描生成配置。受 yusufkaraaslan/Skill_Seekers(14k★ MIT)启发。
模型路由网关:一个端点连接 290+ AI 提供商(90+ 免费、1200+ 模型),Claude Code/Codex/Cursor/Cline/Copilot 全兼容——配额感知自动回退、19 种路由策略、RTK+Caveman 叠加压缩省 15-95% token、免费层聚合预算(~1.5B tokens/月)、MCP/A2A、本地优先。受 diegosouzapw/OmniRoute(51k★ MIT)启发。
Unified DeepSeek Harness plugin: role-based subagent routing + per-agent evolution — prefercmd/memory as knowledge allow/deny lists, so repeated tasks start from proven commands and save tokens
DeepSeek Harness 原生视觉 Bundle:粘贴或拖入图片,通过托管的 deepseek-vision-mcp 调用 OpenAI 兼容视觉模型。
Read-only security & compliance toolkit for DeepSeek Harness: prompt-injection detection (rule engine with a pluggable model classifier), Chinese-PII redaction, and a local configuration security audit that emits redacted, reproducible risk reports.
Sidebar usage card for the dsh web GUI: 7d/30d token usage, spend and remaining DeepSeek balance, rendered above the settings button.
DeepSeek Harness plugin for progressive, source-grounded deep research, writing, and learning: steerable checkpoints and citations verified against retrieved sources
Indirect prompt-injection guard for DeepSeek Harness: taints tool output by origin and gates privileged tool calls that follow untrusted content
DSH 插件:把会话轨迹变成可分享、可复盘、可教学的结构化报告(脱敏 + LLM 总结,HTML/MD/JSON 输出)
常驻视觉服务:直连视觉模型(默认 opencode-go/minimax-m3,回退 zai-coding-cn/glm-4.6v)。describe_image / subagent_vision 工具 + 粘贴图片自动转译(llm/stream 钩子)+ 输入框视觉状态小胶囊与详情页(活动日志:指令/思考过程/输出)。零子代理、零 agent 上下文开销,按会话记忆窗支持视觉追问与验收。
Native DeepSeek Harness model health monitor with persistent Alive/Dead state, runtime failure verification, scheduled rechecks, and health-sorted searchable model pickers.
让 dsh 用独立的 OpenAI 兼容视觉模型读图:主对话历史只保留纯文本描述,图片字节不进上下文,纯文本模型也能读图。
Paired experiments and promotion gates for DSH plugins.
提示词工程模式:结构化推理(CoT/ToT)、few-shot、模板变量、生产级提示词优化。受 wshobson/agents(38k★ MIT)启发。
SQL 优化模式:EXPLAIN 分析、索引策略、N+1 解决、查询改写。受 wshobson/agents(38k★ MIT)启发。
百万 agent 社交模拟:可扩展开源社媒模拟器,LLM agent 逼真模仿 Twitter/Reddit 上多达百万用户——23 种动作(follow/comment/repost)、兴趣与热度推荐算法、动态环境;研究信息传播/群体极化/羊群行为等社会现象。受 camel-ai/oasis(5k★ Apache-2.0)启发。
并行 agent 开发环境:Codex/ClaudeCode/OpenCode/Pi 并排跑,各在独立 git worktree——一个 prompt 扇出 5 个 agent 比较合并胜者;移动伴侣监控、终端分屏、Design Mode(点击 UI 元素送 HTML/CSS/截图进 prompt)、GitHub/Linear 原生、SSH worktree、AI diff 标注。受 stablyai/orca(49k★ MIT)启发。