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Reasoning models return content as a list of typed blocks (thinking, text) instead of a plain string. The summarize_run function used str(content) which serialized the entire list including thinking blocks as a Python repr string — the user saw raw JSON with the LLM's internal reasoning instead of the summary text. If content is a list, extract only items with type "text" and join them. If content is a string, return it as-is.
Add verification rules to both planner and generator prompts covering both local and external facts. If there is even 1% doubt about any local project fact, command, script, or configuration, set needs_analysis=True and ask the analyzer. If there is even 1% doubt about any external fact, version, syntax, or best practice, set needs_web_research=True and ask the researcher. Always verify rather than guess.
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