Overview
Knowledge compression replaces repeated workspace scans with a high-information-density project map.
Instead of reopening every file to understand a codebase or operating folder, the agent receives a concise description of what the project does, where important artifacts live, which commands are used, which dependencies matter, and how the main components relate.
Compression deliberately sacrifices total comprehensiveness. The goal is a bird's-eye view that lets the agent decide where to look next. A short statement such as "the application is implemented in one main component containing navigation, content sections, and footer logic" can eliminate the need to read a much larger file merely to discover the same structural fact.
Preference storage captures conventions that are not reliably built into the harness. Examples include how to return file paths, how much explanation to provide, whether to open an application after starting it, which programming style to favor, or whether to read platform documentation before attempting a non-trivial integration.
Capability declarations tell the agent what it can already do in the current environment. Without these declarations, an agent may behave as though a tool, workflow, database, browser, or autonomous execution path does not exist. A short capability inventory prevents unnecessary clarification loops and reduces the tendency to hand work back to the user.
Failure and success records preserve hard-won operational knowledge. Every failed attempt eliminates part of the solution space. Every successful shortcut identifies a more efficient path. Recording both lets future runs avoid repeating the same search.
The global and local layers should contain different material: