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 agentmods add skills/mturac/everything-openai-codex/security-reviewnpx skills add mturac/everything-openai-codex --skill security-reviewgit clone --depth 1 https://github.com/mturac/everything-openai-codexWrote 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/mturac/everything-openai-codex/security-review)<a href="https://agentmods.dev/skills/mturac/everything-openai-codex/security-review"><img src="https://agentmods.dev/badge/skills/mturac/everything-openai-codex/security-review.svg" alt="Measured on agentmods" 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 | $0.00036 | $0.03028 |
| Opus 5 | $0.00018 | $0.01514 |
| Sonnet 5 | $0.00007 | $0.00606 |
| Haiku 4.5 | $0.00004 | $0.00303 |
Grade A, and why
security-review 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 5d 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
100% identical to security-review — 0 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 — 495 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 ships with it
1 file 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.
- 5d ago First seen · 495 lines · 36 tokens per session scan A e60a179eac26
security-review is a skill published in the GitHub repository mturac/everything-openai-codex (89 stars, last pushed 12d ago), licensed MIT. It adds 36 tokens to every session and 3,028 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to security-review, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
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runbook
Generate and update feature release runbooks from existing docs and codebase. Use when: creating operational runbook, release handbook, deployment checklist, pre-release preparation. Not for: incident response (v2), code review (use codex-code-review), architecture design (use architecture).
debug
Interactive debugging workflow with hypothesis-driven probe loop. Use when: unknown bugs, script errors, silent failures, troubleshooting. Not for: known bugs (use bug-fix), GitHub issue analysis (use issue-analyze), code understanding (use code-explore). Output: debug report with probe journal + root cause + fix.
merge-prep
Pre-merge analysis and preparation. Analyzes source branch vs target branch: commit stats, conflict detection, file impact. Analysis-only v1 — outputs report + suggested commands, does not auto-merge. Use when: user says 'merge prep', 'pre-merge', 'merge analysis', or /merge-prep.
simplify
Wrap-up refactoring — simplify code, eliminate duplication, preserve behavior.
autonomous-loops
Patterns and architectures for autonomous loops — from simple sequential pipelines to RFC-driven multi-agent DAG systems. Use when setting up autonomous development workflows, choosing the right loop architecture, or building CI/CD-style continuous development pipelines.