GPT-6 Astra 的 Programmatic Tool Calling 用法

beamnxw ./ @beamnxw原推发布于 2026.10.05

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OpenAI’s most underrated GPT-6 builder feature: let the model write the tool loop GPT-6 Astra can write JavaScript that calls your tools, joins their results and returns a compact output it’s called Programmatic Tool Calling read multiple sources → group → filter → rank → return the useful result a concrete build: feature requests + product usage + effort estimates → five feature candidates with the evidence attached the repeatable data work runs in code the model uses the result to explain what deserves attention enable it in the Responses API: {"type":"programmatic_tool_calling"} opt eligible functions in: "allowed_callers": ["programmatic"] give every function a clear input schema and a structured output_schema define the scoring rule, required evidence and stopping condition > OpenAI runs the generated program > your server still executes your function tools > return each result with its original call_id and caller, then continue until the final assistant message use this for predictable read-only joins, filtering and aggregation keep adaptive judgment and approval-sensitive writes in direct calls the goal: useful evidence reaches the model without every intermediate payload filling the context start with one bounded stage. measure answer quality, tokens, latency and cost save this, then build your solo company with Dots ⭣

这条是引用着另一条写的：x.com/beamnxw/status/2105370052786565450