How `<important if>` Blocks Improve Instruction Adherence in CLAUDE.md

<important if> XML-style blocks improve instruction adherence in CLAUDE.md by providing Claude Code with explicit conditional relevance signals that prevent the model from deprioritizing critical rules as "may or may not be relevant."

CLAUDE.md serves as the system-prompt file that drives Claude Code's behavior across your codebase. When this file grows lengthy, the model tends to discount sections that appear generically optional, causing it to skip essential instructions during task execution. The improve-claude-md plugin in the humanlayer/skills repository solves this by wrapping domain-specific guidance in <important if> blocks that clearly signal when each rule applies.

Why Claude Code Deprioritizes Generic Instructions

Claude Code operates with a finite token budget for its system prompt—approximately 50,000 tokens are already consumed by the base system instructions. When your CLAUDE.md file contains long, unconditional rule lists, the model's internal parser scans for cues indicating which sections are essential versus optional.

Without explicit relevance markers, Claude Code frames lengthy guidance as "may or may not be relevant," causing it to allocate less attention to critical rules. This behavioral pattern means that generic testing requirements, import conventions, or build commands often get ignored during actual code generation.

The Token Budget Constraint

Every token in the system prompt competes for the model's attention. Unconditional sections describing domain-specific patterns—such as testing frameworks or API conventions—consume valuable context window space even when the current task involves unrelated activities. This bloat increases the probability that Claude Code will discard important constraints to stay within operational limits.

How <important if> Blocks Solve Relevance Weighting

The <important if> XML-style tags mirror the structural patterns used in Claude Code's own system prompt, creating a conditional relevance map that guides the model's attention. When you wrap a section in <important if="condition">…</important> tags, you provide an explicit signal that the enclosed content is conditionally important rather than universally optional.

Conditional Relevance Weighting

Claude's parser treats XML-style tags as structural metadata. By specifying a precise condition—such as you are adding or modifying imports or you need to run commands to build, test, lint, or generate code—you create a clear trigger that the model evaluates against the current task context. When the condition matches, the block receives high-priority attention; when it does not match, the model safely ignores the content without discarding it as noise.

Noise Reduction Through Selective Attention

Moving domain-specific guidance into <important if> blocks isolates only the relevant instructions for each task type. Instead of presenting a monolithic list of all possible rules, the prompt dynamically surfaces only the sections whose conditions are satisfied by the current operation. This selective presentation keeps the active context lean while preserving all rules for future reference.

Implementation Strategy in improve-claude-md

According to the source code in plugins/improve-claude-md/skills/improve-claude-md/SKILL.md, the improve-claude-md plugin implements a three-step transformation strategy to optimize your CLAUDE.md file:

1. Preserve top-level onboarding information as plain text, since project identity and tech stack details are universally required.
2. Wrap every domain-specific rule in an <important if> block with a precise, task-oriented condition.
3. Split long rule lists into individual blocks so the model can match each condition precisely rather than evaluating broad categories.

This architectural approach ensures that Claude Code receives a conditional relevance map rather than an undifferentiated instruction dump.

Source File Structure

The implementation strategy is documented in plugins/improve-claude-md/skills/improve-claude-md/SKILL.md, which defines the transformation logic and lists example conditions such as you are writing or modifying tests. The repository's README.md references this capability, explaining that the plugin rewrites CLAUDE.md using these XML blocks to boost instruction adherence.

Before and After: Practical Examples

The following examples demonstrate how the improve-claude-md plugin transforms generic instruction blocks into conditionally relevant guidance.

Testing Rules Transformation

Before improvement, generic testing instructions lack relevance signaling:

## Testing

- Run `npm test` after every change.
- Use jest for unit tests.
- Ensure coverage > 80%.

After improvement with <important if>:

<important if="you are writing or modifying tests">

## Testing

- Run `npm test` after every change.
- Use jest for unit tests.
- Ensure coverage > 80%.
</important>

Import Handling Transformation

Domain-specific import rules gain explicit triggers:

<important if="you are adding or modifying imports">

## Imports

- Add `import React from 'react'` at the top of each component file.
- Keep import order alphabetical.
</important>

In both cases, the content remains inline in the prompt, but Claude Code now evaluates the condition (you are writing or modifying tests, you are adding or modifying imports) against the current task. If the condition evaluates true, the block is treated as high-priority instruction; otherwise, it is ignored, preventing accidental execution of irrelevant rules.

Summary

• <important if> blocks provide explicit relevance signals that prevent Claude Code from deprioritizing critical instructions in lengthy CLAUDE.md files.
• Conditional wrapping allows the model to evaluate task-specific triggers (you are adding or modifying imports, you need to run commands to build, test, lint, or generate code) and prioritize only matching guidance.
• Noise reduction occurs when domain-specific rules are isolated into conditionally evaluated blocks, keeping the active context lean within the limited token budget.
• The improve-claude-md plugin automates this transformation, leaving universal onboarding information plain while wrapping specific rules in XML-style tags as defined in plugins/improve-claude-md/skills/improve-claude-md/SKILL.md.

Frequently Asked Questions

What is CLAUDE.md and why does it need optimization?

CLAUDE.md is the system-prompt file that configures Claude Code's behavior for a specific codebase. It requires optimization because lengthy, unconditional rule lists cause the model to frame sections as "may or may not be relevant," leading to skipped instructions. The improve-claude-md tool in humanlayer/skills optimizes this file by adding conditional relevance markers.

How does the improve-claude-md tool transform my existing CLAUDE.md?

The tool parses your existing CLAUDE.md and applies a three-step process: it leaves universal context (project identity, tech stack) as plain text, wraps every domain-specific rule in an <important if> block with a precise condition, and splits long lists into discrete conditional blocks. This transformation is documented in plugins/improve-claude-md/skills/improve-claude-md/SKILL.md.

Why use XML-style <important if> tags specifically?

XML-style tags match the structural patterns used in Claude Code's native system prompt, ensuring the model's parser recognizes them as metadata rather than content. This structural similarity guarantees that Claude Code treats the enclosed sections as conditionally important, leveraging the same relevance-weighting mechanisms used by the model's own instruction set.

Do I need to manually maintain these blocks after generation?

While the improve-claude-md plugin performs the initial transformation, you should update the condition attributes when adding new domain-specific rules. Each condition should describe a specific task state (e.g., you are writing or modifying tests) that Claude Code can evaluate against the current operation, ensuring the relevance signals remain accurate as your codebase evolves.

{
  "mcpServers": {
    "instagit": {
      "command": "npx",
      "args": ["-y", "instagit@latest"]
    }
  }
}