全部能力

Analyse workflow trends: session ratings, recurring mistakes, and learnings over a period. Use for weekly or monthly reflection.

Markets orchestration — connects ESPN live schedules with Kalshi and Polymarket prediction markets. Unified dashboards, odds comparison, entity search, and bet evaluation across platforms. Use when: user wants to see prediction market odds alongside ESPN game schedules, compare odds across platforms, search for a team/player on Kalshi or Polymarket, check for arbitrage between ESPN odds and prediction markets, or evaluate a specific game's market value. Don't use when: user wants raw prediction market data without ESPN context — use polymarket or kalshi directly. For pure odds math (conversion, de-vigging, Kelly) — use betting. For live scores without market data — use the sport-specific skill.

基于规范目录结构的学术论文排版助手。支持 PDF / .doc / .docx / .md 多种输入格式，自动选择 OCR 管道、重排版管道或 MD 直转管道。包含环境清理确认、断点恢复、智能配图裁剪、逐单元增量生成 DOCX、双单元质量核查、中间状态保存和 BibTeX 参考文献管理。所有中间文件放…

Publish a workflow learning to the groovebook shared commons as a GitHub PR. Use after groove-work-compound when a learning is worth sharing.

Search and extract contact information for people or companies including names, phone numbers, emails, job titles, and LinkedIn profiles. Aggregates data from…

State-of-the-art text-to-image generation with Stable Diffusion models via HuggingFace Diffusers. Use when generating images from text prompts, performing…

6-phase investigation workflow for understanding existing systems. Auto-activates for research tasks. Optimized for exploration and understanding, not implementation. Includes parallel agent deployment for efficient deep dives and automatic knowledge capture to prevent repeat investigations.

使用 OpenAPI/Swagger 规范生成 API 文档，包含交互式文档、代码示例和 SDK 生成。当用户请求"API…时使用。

Framework for building LLM-powered applications with agents, chains, and RAG. Supports multiple providers (OpenAI, Anthropic, Google), 500+ integrations, ReAct…

使用《Scientific…》中的论文架构与写作策略原则，润色、重构学术文本，或将其翻译为符合《Nature》风格的英文。

Data framework for building LLM applications with RAG. Specializes in document ingestion (300+ connectors), indexing, and querying. Features vector indices,…

Guide to selecting and optimizing embedding models for vector search applications.

Persistent cross-session memory using Memento MCP knowledge graph (mcp__memento__* tools). Recall-before-acting: search memory before starting tasks, on errors, and when receiving corrections. Multi-dimensional search: two queries per recall event (technical topic + process/workflow learnings). Store-after-discovery: persist solutions, conventions, and corrections immediately. Three-step recall: search, open_nodes, traverse relations. WORKING_STATE.md for crash recovery. Self-reminder protocol every 5-10 messages. Activate on task start, errors, corrections, session boundaries, or explicit memory requests. See references/agents-md-setup.md for AGENTS.md integration.

Use when writing or reviewing k6 documentation across TypeScript types, user docs, and release notes.

Build complex AI systems with declarative programming, optimize prompts automatically, create modular RAG systems and agents with DSPy - Stanford NLP's…

Expert guidance for GRPO/RL fine-tuning with TRL for reasoning and task-specific model training

创建、审阅、更新和搜索 ADK 文档的指南 - 当用户询问编写、维护或审计 ADK 机器人文档时使用

Control LLM output with regex and grammars, guarantee valid JSON/XML/code generation, enforce structured formats, and build multi-step workflows with Guidance…

Provides guidance for LLM post-training with RL using slime, a Megatron+SGLang framework. Use when training GLM models, implementing custom data generation…

OpenAI's model connecting vision and language. Enables zero-shot image classification, image-text matching, and cross-modal retrieval. Trained on 400M…