AntiVibe is a Claude Code skill that explains source code as educational lessons or architectural audits, covering its behavior, design choices, usage context, and alternatives. It helps developers learn from new, legacy, or AI-generated code, and the catalogue entry contains its Claude Code skill.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add mohi-devhub/antivibe --skill antivibegit clone --depth 1 https://github.com/mohi-devhub/antivibeWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/mohi-devhub/antivibe/antivibe)<a href="https://agentmods.dev/skills/mohi-devhub/antivibe/antivibe"><img src="https://agentmods.dev/badge/skills/mohi-devhub/antivibe/antivibe/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/mohi-devhub/antivibe/antivibe"><img src="https://agentmods.dev/badge/skills/mohi-devhub/antivibe/antivibe.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00050 | $0.02094 |
| Opus 5 | $0.00025 | $0.01047 |
| Sonnet 5 | $0.00010 | $0.00419 |
| Haiku 4.5 | $0.00005 | $0.00209 |
Grade A, and why
antivibe scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 206 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AntiVibe - Code Learning & Audit Framework
Purpose
AntiVibe generates learning-focused explanations or architectural audits of any code — AI-generated, legacy, or otherwise. It helps developers understand:
- What the code does (functionality)
- Why it was written this way (design decisions)
- When to use these patterns (context)
- What alternatives exist (broader knowledge)
Works on any codebase — you don't need recent git history or AI-authored files.
When to Use
Use AntiVibe when:
- Manual invocation: User types
/antivibeor "deep dive" - Post-task learning: After a feature/phase completes, user wants to learn from it
- Legacy codebases: User wants to understand existing code they didn't write
- Proactive: User says "explain what AI wrote", "walk me through", "audit this", or points at a file/directory
What AntiVibe Produces
Output saved to deep-dive/ folder as markdown:
deep-dive/
├── auth-system-2026-01-15.md
├── api-layer-2026-01-15.md
└── database-models-2026-01-15.md
The exact sections depend on the output mode (see Output Mode):
| Section | compact (default) |
full |
|---|---|---|
| Overview — what the code does and why it exists | ✅ | ✅ |
| Key Components / Concepts — design patterns, algorithms, CS concepts used | ✅ | ✅ |
| Code Walkthrough — file-by-file, line-by-line notes | — | ✅ |
| Learning Resources — curated docs, tutorials, videos | — | ✅ |
| Related Code — links to other files in the codebase | — | ✅ |
Configuration
Known Concepts (Skip List)
Concepts listed here will not be explained in full — the explainer will only note that they were used and in what context. Edit this list to match your current knowledge.
known_concepts:
- async/await
- React hooks
- REST APIs
Output Mode
Controls how much detail is generated per run. Default is compact to keep token costs low.
output_mode: compact
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 206 lines · 50 tokens per session scan A 50868ef6a3c5
antivibe is a skill published in the GitHub repository mohi-devhub/antivibe (1,100 stars, last pushed 1mo ago), licensed MIT. It adds 50 tokens to every session and 2,094 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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