Thermos
SkillSecurityLaunch 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.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Thermos skill
What this skill tells your AI
The instructions your AI receives, as published by ahonn/dotfiles in .claude/skills/thermos/SKILL.md and read by ahel’s review.
Run the two thermo review passes as async background subagents in parallel, then synthesize their results.
Workflow
- Determine the review scope from the user request, PR, current branch, or relevant changed files.
- Gather the diff and any file/context excerpts needed for reviewers to evaluate the change without guessing.
- Launch both subagents in the same message with
run_in_background: true:subagent_type: "thermo-nuclear-review-subagent"for bugs, breakages, security, devex regressions, feature-flag leaks, and other branch-audit risks.subagent_type: "thermo-nuclear-code-quality-review-subagent"for maintainability, structure, file-size growth, spaghetti, abstractions, and codebase-health risks.
- Pass each subagent the same scoped diff/file context and ask it to return prioritized findings with file references and evidence.
- 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.
Signals
- GitHub stars
- 62
- Forks
- 2
- Last commit
- Sep 2026
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thermos- Source
- github.com/ahonn/dotfiles