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 mohitmishra786/anti-vibe-skills --skill pre-review-guidegit clone --depth 1 https://github.com/mohitmishra786/anti-vibe-skillsWrote 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/mohitmishra786/anti-vibe-skills/pre-review-guide)<a href="https://agentmods.dev/skills/mohitmishra786/anti-vibe-skills/pre-review-guide"><img src="https://agentmods.dev/badge/skills/mohitmishra786/anti-vibe-skills/pre-review-guide/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/mohitmishra786/anti-vibe-skills/pre-review-guide"><img src="https://agentmods.dev/badge/skills/mohitmishra786/anti-vibe-skills/pre-review-guide.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 | $0.00089 | $0.01300 |
| Opus 5 | $0.00044 | $0.00650 |
| Sonnet 5 | $0.00018 | $0.00260 |
| Haiku 4.5 | $0.00009 | $0.00130 |
Grade B, and why
pre-review-guide scanned grade B with 1 finding 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 12d 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.
Subtle steeringmediumPrompt injection
Instructions that bias recommendations or shape behaviour without the user noticing.
Walk the human through a structured self-review checklist by asking questions they must answer themselves — never perform the review for them, never tell them what issues exist, never approve the code for submission. How it starts
The opening of the file, as written. The whole thing — 112 lines — stays where its author put it; the contents beside it link to each section on GitHub.
pre-review-guide
Purpose
Walk the human through a structured self-review checklist by asking questions they must answer themselves — never perform the review for them, never tell them what issues exist, never approve the code for submission.
Hard Refusals
- Never perform the review — reading the code and listing issues is the AI doing the human's job. Ask questions instead.
- Never tell the human what a reviewer will say — predicting reviewer comments removes the self-review incentive.
- Never approve the PR — "this looks ready" is not a conclusion the AI draws.
- Never skip a checklist category even if the human says it doesn't apply — make the human confirm it doesn't apply and why.
- Never merge the reviewer's job and the author's job — this skill is about what the author should catch before review, not about catching everything.
Triggers
- "I'm about to open a PR / submit this for review"
- "I think this is ready — can you check it?"
- "I want to do a final pass before I send this out"
- "What should I look at before submitting?"
Workflow
1. Establish the change scope
Before the self-review begins, the human must describe what they changed.
| AI Asks | Purpose |
|---|---|
| "In two sentences: what does this change do and why?" | Forces the human to articulate the intent |
| "What files changed? What was the scope?" | Surfaces the blast radius |
| "What does this change NOT do that a reviewer might expect it to?" | Finds scope boundary clarity |
Gate 1: Human has stated change intent, scope, and explicit non-scope. Do not begin the checklist without these.
Memory note: Record the change description and scope in SKILL_MEMORY.md.
2. Correctness pass
Ask the human to verify the behavior they changed, not just that it compiles.
| AI Asks | Purpose |
|---|---|
| "Walk me through the happy path — what happens step by step?" | Forces narration of intended behavior |
| "What's the edge case most likely to break this? Did you test it?" | Surfaces boundary case coverage |
| "If this code runs in production tonight and something goes wrong, what's the most likely failure?" | Pre-mortem framing |
| "What inputs did you test with? What inputs did you NOT test with?" | Surfaces coverage gaps |
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.
- 12d ago First seen · 112 lines · 89 tokens per session scan B 34e2e5f51c9d
pre-review-guide is a skill published in the GitHub repository mohitmishra786/anti-vibe-skills (5 stars, last pushed 6mo ago), licensed MIT. It adds 89 tokens to every session and 1,300 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it B with 1 finding (subtle steering). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
refactoring-workflow
Improve the structure of existing code without changing its behaviour, in small verified steps under a green test suite. Use when the user asks to refactor, clean up, restructure or simplify code, wants to reduce duplication or coupling, is preparing a codebase for a feature it cannot currently accommodate, or when…
code-quality-review
A code-review guide for judging whether software stays easy to understand, change, test, and extend.
codebase-organizer
Universal codebase operations: analyze, organize, and architecturally deepen any repo. Two commands: /organize for read-only analysis and /deepen for multi-agent refactoring. Use when the user wants a codebase scan, deep module scoring, dependency mapping, architectural improvement, or code-to-skill conversion.…
arch-optimize
A software architecture review workflow that scans a codebase for structural risks and measures code quality. It checks issues such as overly complex code, repeated knowledge, changes spreading across many files, circular dependencies, and distorted domain models.
improve-codebase-architecture
Use when surfacing architectural friction inside a single EVOKORE bounded context and proposing deepening refactors (shallow modules, leaky seams, low locality) that turn shallow modules into deep ones — informed by ADR-0005 bounded contexts and the project's domain language.
improve-codebase-architecture
Find deepening opportunities in a codebase, informed by the domain language in CONTEXT.md and the decisions in docs/adr/. Use when the user wants to improve architecture, find refactoring opportunities, consolidate tightly-coupled modules, or make a codebase more testable and AI-navigable.