enhance-claude-memory

To optimize CLAUDE.md memory files and reduce token usage, analyze project root and subdirectory files to identify redundancy, outdated content, and excessive verbosity, then apply concise, memory-efficient rewrites that preserve essential context for faster AI recall.

The best way to streamline AGENTS.md content for better AI retrieval is to analyze the file for duplication and structural inefficiencies, then reorganize the memory content into a flattened, prioritized plan that improves retrieval performance and token efficiency.

Claude Code workflows support automated memory optimization by analyzing CLAUDE.md and AGENTS.md files to yield a structured report containing token impact estimates, recommended edits, and a mapping of changes to memory load and retrieval performance.

To fix bloated AI prompt memory in OpenCode workflows, analyze CLAUDE.md and AGENTS.md files to identify opportunities to reduce redundancy and improve prompt-relevant memory, generating actionable memory-optimization guidance to flatten content structure.

You should restructure AI agent memory files to improve retrieval performance when redundant or outdated content increases token budgets, requiring a structural adjustment and prioritized plan to yield better recall and memory efficiency.

You can estimate the token impact of editing CLAUDE.md and AGENTS.md files by generating a structured optimization report that maps recommended edits directly to memory load reductions and retrieval performance improvements.