Optimizing Claude Code Context for Frontier Models

The Shift to Model Judgment

Anthropic has moved away from rigid, defensive prompt engineering for its latest models, finding that excessive instructions often conflict and hinder reasoning. Instead of hard-coding style rules like "never write multi-paragraph docstrings," developers should provide a single directive to "match the surrounding code's comment density, naming, and idioms." This allows the model to infer context directly from the existing codebase rather than relying on brittle, manual constraints.

Refactoring Context and Tooling

To reduce context bloat and improve performance, developers should adopt the following strategies:

• Progressive Disclosure: Move detailed procedural instructions out of the main system prompt and into specific skills that only load when necessary.
• Interface-Driven Design: Replace usage examples with expressive tool interfaces. For instance, using an enum for a status parameter (e.g., pending, in-progress, completed) teaches the model tool usage more effectively than descriptive text.
• Rich References: Replace vague markdown instructions with concrete artifacts such as HTML mockups, test suites, rubrics, and code-based specifications.
• Eliminate Redundancy: Remove repeated instructions across system prompts, tool definitions, and CLAUDE.md files. State information exactly once in the most relevant location.

Auditing Existing Setups

Developers should audit their CLAUDE.md files to remove obvious information that the model can infer, such as language or framework choices (e.g., "this is a React project"). Files should be restricted to repository purpose, genuine architectural gotchas, and non-obvious conventions. Anthropic has introduced a /doctor command within Claude Code to automatically audit and flag bloat in existing skill and CLAUDE.md configurations.