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thermos

该 Skill 确定审查范围(用户请求、PR、当前分支或变更文件),收集 diff 与上下文,在同一条消息中以异步后台方式启动两个子代理:一个审查缺陷、破坏性变更、安全、开发体验回退与特性开关泄漏;另一个审查可维护性、结构、文件膨胀与抽象设计。两者完成后将发现按优先级去重汇总,重叠问题加权,分歧自行判断,并简要说明结果。

michael-denyer
热度 0.00
最近更新 2026-10-19 04:13:29
分类:开发依赖:内部调用大模型应用场景:代码审查 / 调试排错 / 工作流

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add michael-denyer/pstack-claude/thermos
Metadata
name
thermos
description
Launch both thermo-nuclear review subagents in parallel, then synthesize their findings. Use for thermos, double thermo review, or combined bug/security and code-quality branch audits.

Thermos

On Codex, read the platform mapping, including its per-skill notes, before following this skill.

On GitHub Copilot, read the platform mapping, including its per-skill notes, before following this skill.

Run the two thermo review passes as async background subagents in parallel, then synthesize their results.

Workflow

  1. Determine the review scope from the user request, PR, current branch, or relevant changed files.
  2. Gather the diff and any file/context excerpts needed for reviewers to evaluate the change without guessing.
  3. Launch both subagents in the same message with run_in_background: true:
    • subagent_type: "pstack:thermo-nuclear-review-subagent" for bugs, breakages, security, devex regressions, feature-flag leaks, and other branch-audit risks.
    • subagent_type: "pstack:thermo-nuclear-code-quality-review-subagent" for maintainability, structure, file-size growth, spaghetti, abstractions, and codebase-health risks.
  4. Pass each subagent the same scoped diff/file context and ask it to return prioritized findings with file references and evidence.
  5. After both finish, synthesize the results with findings first, deduplicated across reviewers. Weight overlapping findings more heavily, resolve disagreements with your own judgment, and keep summaries brief.

If individual background summaries are already visible to the user, do not restate them wholesale. Surface the unified verdict, the highest-signal findings, and any remaining uncertainty.