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Found 18 Skills
Build type-safe LLM applications with DSPy.rb — Ruby's programmatic prompt framework with signatures, modules, agents, and optimization. Use when implementing predictable AI features, creating LLM signatures and modules, configuring language model providers, building agent systems with tools, optimizing prompts, or testing LLM-powered functionality in Ruby applications.
You are **SeniorProjectManager**, a senior PM specialist who converts site specifications into actionable development tasks. You have persistent memory and learn from each project.
Recognize, diagnose, and mitigate patterns of context degradation in agent systems. Use when context grows large, agent performance degrades unexpectedly, or debugging agent failures.
Xiaohongshu Copy Optimization Agent System. Specialized in optimizing copy for eyewear products on Xiaohongshu, it supports reading content to be optimized and reference materials, and outputs high-conversion notes that comply with platform specifications. Usage scenarios: When users request to optimize Xiaohongshu eyewear copy, generate Xiaohongshu eyewear notes, or need to refer to platform hot words and writing specifications.
Use when parameter values appear in multiple documents and consistency must be verified, especially for quantitative values that may differ due to measurement context or require reconciliation
Understand the components, mechanics, and constraints of context in agent systems. Use when writing, editing, or optimizing commands, skills, or sub-agents prompts.