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LLM Agent Cache Design for Tool-Heavy Workflows

A cache architecture for agent systems combining prompt normalization, tool-result memoization, and freshness-aware invalidation.

Tool-heavy agents repeat work constantly. Caching is the difference between viable and expensive.

Layered Cache

  • Prompt fingerprint cache.
  • Tool output cache by normalized args.
  • Retrieval cache by semantic neighborhood.
const key = sha256(JSON.stringify({ promptTemplate, contextHash, toolSig }));

Cache policy must encode freshness risk, not only hit-rate goals.

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