Develop with
Superpowers

Create and curate evaluation datasets with ground truth for TruLens

Analyzes article structure, identifies positions requiring visual aids, generates illustrations with Type × Style two-dimension approach. Use when user asks to "illustrate article", "add images", "generate images for article", or "为文章配图".

Generates professional slide deck images from content. Creates outlines with style instructions, then generates individual slide images. Use when user asks to "create slides", "make a presentation", "generate deck", "slide deck", or "PPT".

工具组件指南，涵盖 JWT 安全认证、表达式解析器、线程池循环工具、责任链模式等特定功能的工具类使用。当用户需要实现 JWT 认证、解析表达式、使用线程池或实现责任链时使用。

BK-CI 数据库设计规范与表结构指南，涵盖命名规范、字段类型选择、索引设计、分表策略、数据归档。当用户设计数据库表、优化索引、规划分表策略或进行数据库架构设计时使用。

微服务基础设施指南，涵盖条件配置、事件驱动架构、服务间通信、国际化与日志等微服务架构的核心基础设施。当用户实现服务间调用、配置多环境、实现异步通信、处理国际化或规范日志输出时使用。

Project 项目管理模块架构指南，涵盖项目 CRUD、成员管理、项目配置、标签管理、项目迁移。当用户开发项目管理功能、处理项目成员、配置项目属性或实现项目相关逻辑时使用。

Assists in writing high-quality content by conducting research, adding citations, improving hooks, iterating on outlines, and providing real-time feedback on each section. Transforms your writing process from solo effort to collaborative partnership.

Filters specific errors from Sentry reporting in this OneKey monorepo. Use when needing to ignore/suppress/filter Sentry errors, add error exclusions, or stop certain errors from being reported. Handles platform-specific filtering (desktop/mobile/web/extension).

Comprehensive smart contract development advisor based on Trail of Bits' best practices. Analyzes codebase to generate documentation/specifications, review architecture, check upgradeability patterns, assess implementation quality, identify pitfalls, review dependencies, and evaluate testing. Provides actionable recommendations. (project, gitignored)

Techniques for writing effective fuzzing harnesses across languages. Use when creating new fuzz targets or improving existing harness code.

Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.

Write publication-ready ML/AI papers for NeurIPS, ICML, ICLR, ACL, AAAI, COLM. Use when drafting papers from research repos, structuring arguments, verifying citations, or preparing camera-ready submissions. Includes LaTeX templates, reviewer guidelines, and citation verification workflows.

Provides guidance for mechanistic interpretability research using TransformerLens to inspect and manipulate transformer internals via HookPoints and activation caching. Use when reverse-engineering model algorithms, studying attention patterns, or performing activation patching experiments.

High-level PyTorch framework with Trainer class, automatic distributed training (DDP/FSDP/DeepSpeed), callbacks system, and minimal boilerplate. Scales from laptop to supercomputer with same code. Use when you want clean training loops with built-in best practices.

Optimizes LLM inference with NVIDIA TensorRT for maximum throughput and lowest latency. Use for production deployment on NVIDIA GPUs (A100/H100), when you need 10-100x faster inference than PyTorch, or for serving models with quantization (FP8/INT4), in-flight batching, and multi-GPU scaling.

CLI output formatting standards for worktrunk. Use when writing user-facing messages, error handling, progress output, hints, warnings, or working with the output system.

Create a Product Requirements Document (PRD) for your MVP. Use when the user wants to define product requirements, create a PRD, or says "help me write requirements", "create PRD", or "define my product".

Comprehensive PostgreSQL-specific table design reference covering data types, indexing, constraints, performance patterns, and advanced features

Data engineering skill for building scalable data pipelines, ETL/ELT systems, and data infrastructure. Expertise in Python, SQL, Spark, Airflow, dbt, Kafka, and modern data stack. Includes data modeling, pipeline orchestration, data quality, and DataOps. Use when designing data architectures, building data pipelines, optimizing data workflows, implementing data governance, or troubleshooting data issues.