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 hnikoloski/imlazy --skill imlazy-securitygit clone --depth 1 https://github.com/hnikoloski/imlazyWrote 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/hnikoloski/imlazy/imlazy-security)<a href="https://agentmods.dev/skills/hnikoloski/imlazy/imlazy-security"><img src="https://agentmods.dev/badge/skills/hnikoloski/imlazy/imlazy-security/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/hnikoloski/imlazy/imlazy-security"><img src="https://agentmods.dev/badge/skills/hnikoloski/imlazy/imlazy-security.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 | $0.00037 | $0.03083 |
| Opus 5 | $0.00018 | $0.01541 |
| Sonnet 5 | $0.00007 | $0.00617 |
| Haiku 4.5 | $0.00004 | $0.00308 |
Grade A, and why
imlazy-security 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 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.
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.
This is a copy
95% identical to security-review — 14 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 503 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Security Review Skill
This skill ensures all code follows security best practices and identifies potential vulnerabilities.
When to Activate
- Implementing authentication or authorization
- Handling user input or file uploads
- Creating new API endpoints
- Working with secrets or credentials
- Implementing payment features
- Storing or transmitting sensitive data
- Integrating third-party APIs
Security Checklist
1. Secrets Management
FAIL: NEVER Do This
const apiKey = "sk-proj-xxxxx" // Hardcoded secret
const dbPassword = "password123" // In source code
PASS: ALWAYS Do This
const apiKey = process.env.OPENAI_API_KEY
const dbUrl = process.env.DATABASE_URL
// Verify secrets exist
if (!apiKey) {
throw new Error('OPENAI_API_KEY not configured')
}
Verification Steps
- No hardcoded API keys, tokens, or passwords
- All secrets in environment variables
-
.env.localin .gitignore - No secrets in git history
- Production secrets in hosting platform (Vercel, Railway)
2. Input Validation
Always Validate User Input
import { z } from 'zod'
// Define validation schema
const CreateUserSchema = z.object({
email: z.string().email(),
name: z.string().min(1).max(100),
age: z.number().int().min(0).max(150)
})
// Validate before processing
export async function createUser(input: unknown) {
try {
const validated = CreateUserSchema.parse(input)
return await db.users.create(validated)
} catch (error) {
if (error instanceof z.ZodError) {
return { success: false, errors: error.errors }
}
throw error
}
}
File Upload Validation
function validateFileUpload(file: File) {
// Size check (5MB max)
const maxSize = 5 * 1024 * 1024
if (file.size > maxSize) {
throw new Error('File too large (max 5MB)')
}
// Type check
const allowedTypes = ['image/jpeg', 'image/png', 'image/gif']
if (!allowedTypes.includes(file.type)) {
throw new Error('Invalid file type')
}
// Extension check
const allowedExtensions = ['.jpg', '.jpeg', '.png', '.gif']
const extension = file.name.toLowerCase().match(/\.[^.]+$/)?.[0]
if (!extension || !allowedExtensions.includes(extension)) {
throw new Error('Invalid file extension')
}
return true
}
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 · 503 lines · 37 tokens per session scan A 9d731e349a53
imlazy-security is a skill published in the GitHub repository hnikoloski/imlazy (2 stars, last pushed 1mo ago), licensed MIT. It adds 37 tokens to every session and 3,083 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 95% identical to security-review, differing in 14 lines, and is treated as a copy.
Other skills, from other repositories
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architecture-design
Use only when creating new registrable ML components that require Factory or Registry patterns.
results-analysis
This skill should be used when the user asks to "analyze experimental results", "run strict statistical analysis", "compare model performance", "generate scientific figures", "check significance", "do ablation analysis", or mentions interpreting experiment data with rigorous statistics and visualization. It focuses on…
review-response
Systematic review response workflow from comment analysis to professional rebuttal writing. Use when the user asks to "write rebuttal", "respond to reviewers", "draft review response", or "analyze review comments". Improves paper acceptance rates.
verification-loop
This skill should be used when the user asks to "verify code", "run verification", "check quality", "validate changes", or before creating a PR. Provides comprehensive verification including build, type check, lint, tests, security scan, and diff review.