Developer builds minimal web search agent, then audits whether it earns the label

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A developer built a Perplexity-style search assistant using a Bun backend, React 19 frontend, Tavily for search, and OpenRouter as the model provider. The system allows a language model to autonomously decide when to call a web search tool, loop through results, and stream cited answers to users. Before publishing about the project, the developer paused to honestly assess whether the build qualified as a true 'agent harness' or merely a well-dressed API call. After reviewing the core agent loop code, they confirmed it meets the harness definition: the model controls tool use, the loop iterates until completion, context is trimmed, and output is a structured event stream. The developer acknowledged the build is a single-tool harness with no retries or provider fallback, and noted that a more robust multi-tool version remains a future goal.

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