AI Agent Prompt Best Practices
Plug-and-play description skeletons and hierarchical router prompts to boost multi-agent system hit rates above 95%.
Core Research & Manuals
《Too Many Agent Skills Making It Dumb? 4 Steps to Bring Your Hit Rate Back!》
Struggling with Agent choosing wrong skills as list grows? Learn to fix it with descriptions, hierarchical routing, negative samples, and reranking.
《How I Built My Own Xiaohongshu Workflow with Codex》
Tired of manual RED content production? Learn how to use Codex to maintain your topic pool, title library, copywriting templates, and data analytics, converting repetitive tasks into a standardized project workflow.
《Speak These 4 Sentences to AI, and You Can Efficiently Learn Any Field!》
Just saying 'Teach me Python' results in flat general answers? Learn to construct the 'Role→Method→Situation→Requirements' framework to turn AI into a deliberate practice coach.
《Codex Long-term Workflow Maximization - How Codex Keeps Work Advancing Beyond Single Prompts》
An in-depth analysis on building adaptive context and memory inheritance with Codex, enabling complex agent development to continuously evolve beyond single prompts.
Recommended Reading List
Understanding recall, orchestration, and hierarchical decision-making in multi-agent systems.
《Design Patterns for LLM Agents》
Analyzing the core pathway and data structures from single agent systems to multi-agent collaboration and recall trees.
《Systematic Prompt Engineering Handbook》
Exploring system prompts, role control, and negative constraints refinement.
AI Agent & Prompt Engineering Best Practices
A collection of cutting-edge guides, operational manuals, and optimization formulas for LLM Agents and multi-skill routing accuracy.