Caching Model Calls Instead of Prompts to Save Free-Tier Tokens in Agent Loops

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A solo developer's example illustrates how iterative edits to an agent loop can re-trigger dozens of identical model requests and exhaust a free token allowance quickly. The article proposes a replay layer that stores each response on disk under a hash of its request, so repeated identical calls never reach the model. The hash excludes volatile metadata such as request IDs and timestamps, and writes are made atomic to avoid corrupted files if a process is killed. The author cautions that sampling parameters must be fixed, such as temperature zero or an explicit seed, or the cache will hide real output variance. The disclosure notes the piece was prepared as part of MonkeyCode's outreach, and readers are advised to verify the current free-tier limits independently.

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