仓库和设计上下文可能被发送给多个模型提供方
原文依据:5 处Skill 优先使用不同模型家族,并要求给子代理提供仓库路径、背景、相关文件或符号。某些候选模型可能由不同的远程提供方托管,因此同一份代码或设计信息可能跨多个服务处理。
如果提示中包含私有源代码、未公开设计、客户数据或凭据,这些内容可能进入多个提供方的处理或日志范围,扩大数据暴露面。
该 Skill 要求优先使用不同模型家族,并把仓库或制品位置、背景及相关文件/符号写入共享简报。因此,如果所选子代理由不同远程服务托管,同一项目上下文可能被多个提供方处理;源码并未说明这些模型一定是远程的,也未证明已发生传输。用户可要求只使用获准或本地模型,并限制简报中的代码、路径和敏感设计信息。
Preferred default roster for a three-member council:- Opus 4.7 or the strongest available Claude/Opus reasoning model: architecture, correctness, and edge-case analysis.- GPT 5.5 or the strongest available GPT/Codex model: implementation-grounded review, feasibility, and test strategy.- An open-source model such as Kimi 2.6, GLM 5.1, or the strongest available OSS/local model: contrarian critique, hidden assumptions, and alternative framing.If one of these exact models is unavailable in the active harness, use the closest available model from that family and note the substitution. If no open-source model is available, use a third distinct frontier model if possible; otherwise use the strongest remaining model with a deliberately adversarial or specialist angle.查看另外 4 个位置
The shared brief should include:- repository path or artifact location;- current branch or base context;- the exact question to answer;- relevant background and known concerns;- required files/symbols to inspect, if known;- constraints, especially read-only/no commits/no PRs;- expected report format.For explicit orchestration requests, briefly tell the user which council members you plan to launch and what each will investigate, then wait for approval before calling `run_agents`.Prioritize model diversity. A council should not default to three agents on the same model with different angles; use that only when the available launch configuration cannot provide multiple useful models, or when the user explicitly asks for one model. If model diversity is unavailable, say so briefly before falling back to perspective-only diversity.- Opus 4.7 or the strongest available Claude/Opus reasoning model: architecture, correctness, and edge-case analysis.- GPT 5.5 or the strongest available GPT/Codex model: implementation-grounded review, feasibility, and test strategy.- An open-source model such as Kimi 2.6, GLM 5.1, or the strongest available OSS/local model: contrarian critique, hidden assumptions, and alternative framing.