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 5.5 | $0.00020 | $0.00838 |
| Sonnet 5.5 | $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 1mo 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 ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago First seen · 206 lines · 50 tokens per session scan A 50868ef6a3c5
antivibe is a skill published in the GitHub repository mohi-devhub/antivibe (1,129 stars, last pushed 2mo ago), licensed MIT. It adds 50 tokens to every session and 2,094 once invoked, about $0.0002 per session on Opus 5.5. 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.
Other skills, from other repositories
gan-zhong-xue
A learning workflow that makes an AI explain code changes through questions, evidence, and underlying principles. It is designed to help developers understand work they asked an AI to do, rather than merely accept the result.
help
Explain the agentic-study-environment plugin — what it does, the lifecycle skills it ships, the domain overlays, the session types, and the key conventions — or a specific one of those if the user names it. Use this skill whenever the user asks for help with the study harness itself rather than asking to study…
accessibility-audit
This skill should be used when evaluating a design, page, or component against accessibility standards and producing a severity-scored report. Trigger phrases include "audit accessibility", "check a11y", "is this accessible", "WCAG audit", "check color contrast", and "accessibility review before handoff". Use it to…
design-tokens
This skill should be used when a user wants to scaffold or refactor a design token system — e.g. "set up design tokens", "create a design system foundation", "extract these hardcoded colors into tokens", "add a type scale", "theming setup", or "dark mode tokens". It produces a single source of truth for color, type…
adjust-level
Adjust the difficulty level of a learning sub-project's curriculum — simplify a too-advanced curriculum into a gentler on-ramp, or deepen a too-introductory one into something with real teeth. Use whenever the user signals the curriculum's level doesn't match their starting point — phrases like "this paper is too…
bootstrap
Scaffold a new learning sub-project under the agentic-study-environment harness — create the directory, generate per-project AGENTS.md, CLAUDE.md, and PROGRESS.md from templates, and register the new project in the .studyenv/PROGRESS.md cross-project tracker. Use this skill whenever the user wants to start studying a…