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 wasintoh/toh-framework --skill security-engineergit clone --depth 1 https://github.com/wasintoh/toh-frameworkWrote 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/wasintoh/toh-framework/security-engineer)<a href="https://agentmods.dev/skills/wasintoh/toh-framework/security-engineer"><img src="https://agentmods.dev/badge/skills/wasintoh/toh-framework/security-engineer/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/wasintoh/toh-framework/security-engineer"><img src="https://agentmods.dev/badge/skills/wasintoh/toh-framework/security-engineer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Privilege Escalation · line 399 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- medium MCP Rug Pull · line 302 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
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 | $0.00087 | $0.02557 |
| Opus 5.5 | $0.00035 | $0.01023 |
| Sonnet 5.5 | $0.00017 | $0.00511 |
| Haiku 4.5 | $0.00009 | $0.00256 |
Grade A, and why
security-engineer 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 — 445 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Security Engineer Skill
Overview
Security-first approach for AI-generated code auditing. Provides both quick checks (during dev/test) and comprehensive audits (full protection).
Core Philosophy
"Trust, but verify - especially AI-generated code"
- Proactive Detection - Catch issues before they become vulnerabilities
- Layer Defense - Quick checks + Full audits = Maximum coverage
- Zero False Sense - Don't trust code just because it "looks safe"
- Human-Readable Reports - Clear findings with actionable fixes
Security Check Levels
+-------------------------------------------------------------+
| LEVEL 1: Quick Check (during /toh-dev, /toh-test) |
| - Hardcoded secrets |
| - Dangerous imports/code execution |
| - Basic auth issues |
| - Obvious injection vectors |
| Duration: < 5 seconds |
+-------------------------------------------------------------+
|
v
+-------------------------------------------------------------+
| LEVEL 2: Full Audit (/toh-protect) |
| - All Level 1 checks |
| - Injection attacks (SQL, XSS, Command) |
| - Auth/Authorization flaws |
| - AI-Generated Code risks |
| - Configuration security |
| - Dependency vulnerabilities |
| Duration: 30-60 seconds |
+-------------------------------------------------------------+
Level 1: Quick Check Patterns
1.1 Hardcoded Secrets Detection
Detection Patterns:
SECRET_PATTERNS:
# API Keys
- Pattern for api_key, apikey with 20+ char values
- Pattern for sk-live, pk-live, sk-test prefixes
# AWS
- Pattern: AKIA followed by 16 alphanumeric chars
- Pattern for aws_secret values
# Database URLs
- Connection strings with embedded credentials
# Private Keys
- PEM format key headers
# JWT Secrets
- jwt_secret, secret_key patterns
# Generic passwords
- password/passwd/pwd assignments
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 · 445 lines · 87 tokens per session scan A 4fd2194bed32
security-engineer is a skill published in the GitHub repository wasintoh/toh-framework (98 stars, last pushed 1mo ago), licensed MIT. It adds 87 tokens to every session and 2,557 once invoked, about $0.0003 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.
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