Context Engineering FAQs

Question 1

What is the 'Lost in the Middle' phenomenon?

Accepted Answer

Research shows that LLMs pay the most attention to the beginning and end of their context window. This skill provides templates to ensure critical instructions and current tasks are placed in those high-attention zones.

Question 2

How does this skill reduce token costs?

Accepted Answer

It implements progressive disclosure and intelligent compression strategies, ensuring that the model only receives the specific information it needs for the current task rather than loading massive datasets into every request.

Question 3

What is context engineering vs. prompt engineering?

Accepted Answer

While prompt engineering focuses on the instructions you give the model, context engineering focuses on the entire input state—including system prompts, retrieved documents, history, and tool outputs—to ensure the highest signal-to-noise ratio.

Question 4

How does MCP auto-deferral work?

Accepted Answer

When context usage exceeds 10% of the effective window, the system automatically defers loading Model Context Protocol (MCP) tools, making them available via search on-demand rather than consuming permanent token space.

Question 5

Does it support Claude's 1 million token context window?

Accepted Answer

Yes, the skill includes an auto-scaling budget manager that adjusts character limits for skills and context based on the specific model's maximum window size.

Context Engineering

Context Engineering

主な機能

ユースケース

主な機能

ユースケース