Embed a Copilot-inspired AI chat interface in WPF apps with DevExpress AIChatControl — install DevExpress.AIIntegration.Wpf.Chat, change the project SDK to Microsoft.NET.Sdk.Razor, register an IChatClient (Azure OpenAI / OpenAI / Ollama / Semantic Kernel) with AIExtensionsContainerDesktop.Default, drop the control inside a ThemedWindow, and enable features like response streaming, Markdown rendering, file attachments, prompt suggestions, and chat history persistence. Use when building chat assistants, document Q&A, RAG dashboards, or any in-app conversational UI in WPF. Also use when someone mentions "AIChatControl", "DevExpress.AIIntegration.Wpf.Chat", "AIExtensionsContainerDesktop", "RegisterChatClient", "IChatClient", "dxaichat:", "UseStreaming", "MarkdownConvert", "FileUploadEnabled", "PromptSuggestions", "MessageSending", "MessageSent", "SaveMessages / LoadMessages", "ChatClientServiceKey", or building a "RAG" / "chat with your data" feature. Requires .NET 8+ and the WebView2 runtime.
npx skills add https://github.com/DevExpress/agent-skills --skill devexpress-wpf-ai-chat-control
Automate Benchmark Email tasks via Rube MCP (Composio). Always search tools first for current schemas.
Use when the user asks to "triage our comments, DMs, and mentions", "draft replies to this thread", "can we repost this fan post", or "set up inbox SLAs and an escalation path"; produces a ranked triage queue with register detection (sincere / ironic / performative / parasocial, sentiment-inversion table included — "this is so bad" under a comedy register is praise), a commenter taxonomy (troll monitor-only / rager / misguided / unhappy-customer / advocate) with a response-tier ladder and per-channel SLAs, an escalation matrix ending at the crisis path, a moderation ladder plus house rules for owned spaces, and a UGC curation-and-rights mode whose dated permission entries route to the channel registry — every reply is a ranked DRAFT a human posts; nothing is ever auto-sent. Not for launch-window feedback triage — use launch-feedback-synthesizer. 评论私信提及分诊/语域识别/回复草稿/UGC授权
Apply CIS benchmarks and secure Linux servers. Configure SSH, manage users, implement firewall rules, and enable security features. Use when hardening Linux systems for production or meeting security compliance requirements.
| Benchmark Email integration. Manage data, records, and automate workflows. Use when the user wants to interact with Benchmark Email data.
>- Decision protocol for making side-effectful agent tools idempotent — so when an LLM tool call is retried (timeout, framework resume, user re-run, model duplicate emit), the second it'll call exactly once; the tool must promise the second call is safe. Framework-agnostic — applies to LangGraph node bodies that re-run on resume, MCP tools, OpenAI tool-calling duplicate email sent, charged twice, exactly-once, idempotency key, tool called twice, retry side effect, double-send, at-least-once delivery.
Autonomously research, implement, train and ship ML code using the Hugging Face ecosystem. Port of huggingface/ml-intern as a Claude Code skill. Triggers when the user asks to implement, train, fine-tune, or reproduce an ML model / paper / dataset workflow (e.g. "implement DeepSeek-V3 at 100M", "fine-tune Qwen on dataset X", "reproduce paper Y"). Clarifies ambiguous tasks before starting, runs under an explicit experiment budget, explores multiple viable solution paths in parallel via implementation subagents, and diagnoses + retries failed runs. HF-native: pulls datasets/models/papers from the Hub, pushes trained checkpoints + run logs back to the Hub. Emits Telegram + Slack milestone alerts via scripts/notify.sh.
Automate Benchmark Email tasks via Rube MCP (Composio). Always search tools first for current schemas.
Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.
Take devexpress/devexpress-wpf-ai-chat-control from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.