From Giant Prompts to On-Demand Skills: Build an Extensible AI Agent With Progressive Disclosure

The useful part

Large agent prompts often begin as a practical shortcut: policies, domain rules, tool descriptions, examples, recovery procedures, and integration notes are placed in one system message so every capability is always available. That approach stops scaling once an agent accumulates dozens of tools and specialized workflows. Tool definitions and instructions consume context on every turn, irrelevant material competes with task-relevant material, and each integration enlarges a shared prompt that becomes harder to test and version.

How it works

• Current platform guidance increasingly converges on a different model: expose compact capability metadata first, load detailed instructions only after relevance is established, and execute specialized logic...
• Anthropic describes this as progressive disclosure for Agent Skills, while OpenAI supports both Skills and deferred tool discovery.